{ "count": 174, "next": "https://svs.gsfc.nasa.gov/api/search/?limit=100&offset=100&search=Vegetation+Index", "previous": null, "results": [ { "id": 15018, "url": "https://svs.gsfc.nasa.gov/15018/", "result_type": "Visualization", "release_date": "2026-05-06T11:00:00-04:00", "title": "Agricultural Cycles in the Imperial Valley", "description": "This page features HLS (Harmonized Landsat and Sentinel-2) time series of California’s Imperial Valley near the Salton Sea. Spanning October 2024 to October 2025, these animations highlight multiple agricultural growth cycles within a single year using natural color, NDVI, and a side-by-side comparison.", "hits": 36 }, { "id": 5599, "url": "https://svs.gsfc.nasa.gov/5599/", "result_type": "Visualization", "release_date": "2026-04-21T15:00:00-04:00", "title": "PACE Data Tour - Visualizations", "description": "A tour of PACE data products", "hits": 184 }, { "id": 31365, "url": "https://svs.gsfc.nasa.gov/31365/", "result_type": "Visualization", "release_date": "2026-03-01T18:59:59-05:00", "title": "The Earth System Science Spheres", "description": "A rotating sphere shows data from recent satellites representing four of the five science spheres: Atmosphere, Biosphere, Geosphere, and Hydrosphere.", "hits": 699 }, { "id": 14894, "url": "https://svs.gsfc.nasa.gov/14894/", "result_type": "Produced Video", "release_date": "2025-09-23T13:00:00-04:00", "title": "NASA Flew Over a Fire — to Better Understand Future Ones", "description": "On April 14th-20th, 2025, NASA’s FireSense project led a multi-agency prescribed burn research operation at Fort Stewart-Hunter Army Field, Georgia, in partnership with the U.S. Department of War (DoW). The DoW led the prescribed burn activities, while NASA FireSense coordinated field and airborne sampling with academic and agency partners, including the DoW Strategic Environmental Research and Development Program (SERDP) and DoW Environmental Security Technology Certification Program (ESTCP). The campaign targeted vegetation, fire, and smoke measurements, and aims to enhance understanding of fire behavior and smoke dynamics in order to provide actionable information to practitioners.In a collaboration between NASA, the DoW, and wildland experts, NASA FireSense demonstrates how cutting-edge satellite and airborne technology is revolutionizing fire detection, prescribed fire, and ecosystem management—bringing real-time data to wildland fire managers.NASA FireSense Website || ", "hits": 65 }, { "id": 5544, "url": "https://svs.gsfc.nasa.gov/5544/", "result_type": "Visualization", "release_date": "2025-09-22T18:59:59-04:00", "title": "Near Real-Time Normalized Difference Vegetation Index (NDVI)", "description": "NRT NDVI", "hits": 0 }, { "id": 5548, "url": "https://svs.gsfc.nasa.gov/5548/", "result_type": "Visualization", "release_date": "2025-06-05T07:00:59-04:00", "title": "Global Views of PACE Land Vegetation Data", "description": "Global view of three major classes of plant pigments observed by the PACE satellite: chlorophylls, carotenoids, and anthocyanins.", "hits": 141 }, { "id": 31341, "url": "https://svs.gsfc.nasa.gov/31341/", "result_type": "Visualization", "release_date": "2025-04-11T10:30:00-04:00", "title": "2020 Iowa Derecho", "description": "NASA satellites imaged the after effects of an August 2020 derecho on Iowa crops.", "hits": 50 }, { "id": 5474, "url": "https://svs.gsfc.nasa.gov/5474/", "result_type": "Visualization", "release_date": "2025-01-20T00:00:00-05:00", "title": "Science On a Sphere: 4 Years of Biosphere", "description": "Biosphere data processed for display on Science On a Sphere (SOS)", "hits": 65 }, { "id": 14696, "url": "https://svs.gsfc.nasa.gov/14696/", "result_type": "Produced Video", "release_date": "2024-10-08T00:00:00-04:00", "title": "NASA + Smithsonian and Greenhouse Gases", "description": "Full 8K resolution. Optimized for Earth Information Center display at the National Museum of Natural History (Smithsonian).Universal Production Music France: \"Human Endeavor\" by Oliver Grim, Koka Media; \"Accuracy\" by Laurent Levesque.Universal Production Music: \"Feelings of Pride\" by Kathryn Louise Maclennan, Label-Aurora Production Music.This video can be freely shared and downloaded. While the video in its entirety can be shared without permission, some individual imagery provided by Pond5, Shutterstock and Smithsonian is obtained through permission and may not be excised or remixed in other products. For more information on NASA’s media guidelines, visit https://www.nasa.gov/multimedia/guidelines/index.htmlComplete transcript available.Watch this video on the NASA Scientific Visualization Studio YouTube channel. || Smithsonian_GHG.png (3825x1076) [2.8 MB] || Smithsonian_GHG_searchweb.png (320x180) [63.7 KB] || Smithsonian_GHG_thm.png (80x40) [6.2 KB] || GHG_Smithsonian.en_US.srt [5.8 KB] || GHG_Smithsonian.en_US.vtt [5.5 KB] || Smithsonian_GHG_v5_small.mp4 (7680x2160) [472.3 MB] || Smithsonian_GHG_v5_medium.mp4 (7680x2160) [859.9 MB] || Smithsonian_GHG_v5_h.264.mp4 (7680x2160) [4.5 GB] || ", "hits": 175 }, { "id": 14606, "url": "https://svs.gsfc.nasa.gov/14606/", "result_type": "Produced Video", "release_date": "2024-07-29T15:00:00-04:00", "title": "NASA and Fire", "description": "Wildland fires, which are natural and essential for many ecosystems, have increased in frequency and size due to longer fire seasons, climate change, and the expanding interface between communities and wild vegetation. Using fire strategically—through prescribed burns and natural ignitions—can mitigate future severe fires that might burn more intensely under hotter, drier conditions.", "hits": 194 }, { "id": 5185, "url": "https://svs.gsfc.nasa.gov/5185/", "result_type": "Visualization", "release_date": "2023-12-07T15:00:00-05:00", "title": "PACE orbit with Ocean Color Instrument (OCI) data", "description": "PACE orbiting Earth with Ocean Color Instrument (OCI) swath revealed below || pace_orbit_swath.45_OCIonly_2023-10-27_1527.08000_print.jpg (1024x576) [73.1 KB] || pace_orbit_swath.45_OCIonly_2023-10-27_1527.08000_searchweb.png (320x180) [34.6 KB] || pace_orbit_swath.45_OCIonly_2023-10-27_1527.08000_thm.png (80x40) [3.5 KB] || 3840x2160_16x9_60p (3840x2160) [0 Item(s)] || pace_orbit_swath.45_OCIonly_2023-10-27_1527_2160p60.mp4 (3840x2160) [24.0 MB] || ", "hits": 69 }, { "id": 31267, "url": "https://svs.gsfc.nasa.gov/31267/", "result_type": "Hyperwall Visual", "release_date": "2023-11-28T00:00:00-05:00", "title": "Landsat and Sentinel NDVI, 2022", "description": "The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8/9 and Sentinel-2A/B remote sensing satellites, respectively. These animations show a year's worth of HLS data near Columbus, Nebraska from 2022. One animation includes the cloudy scenes and the other has cloud-free or mostly cloud-free scenes. ||", "hits": 47 }, { "id": 40503, "url": "https://svs.gsfc.nasa.gov/gallery/hyperwall-power-playlist-earth-science/", "result_type": "Gallery", "release_date": "2023-08-28T00:00:00-04:00", "title": "Hyperwall Power Playlist - Earth Science Focus", "description": "This is a collection of our most powerful, newsworthy, and frequently used Hyperwall-ready visualizations, along with several that haven't gotten the attention they deserve. They're especially great for more general or top-level science talks, or to \"set the scene\" before a deep dive into a more focused subject or dataset. We've tried to cover the subject areas our speakers focus on most. \n\nIf you're not seeing what you're looking for, there is a huge library of visualizations more localized or specialized in subject - please use the Search function above, and filter \"Result type\" for \"Hyperwall Visual.\"\n\n If you'd like to use one of these visualizations in your Hyperwall presentation, we'll need to know which element on which page. On the visualization's web page, below the visual you'd like to use, you'll see a Link icon next to the Download button. All we need is for you to click on that icon and include that link in your presentation Powerpoint/Keynote or visualization list. Additionally, please check our Hyperwall How-To Guide for tips on designing your Hyperwall presentation, file specifications, and Powerpoint/Keynote templates.", "hits": 323 }, { "id": 40477, "url": "https://svs.gsfc.nasa.gov/gallery/greenhouse-gases-dashboard/", "result_type": "Gallery", "release_date": "2023-06-07T00:00:00-04:00", "title": "Greenhouse Gases Dashboard", "description": "NASA and its partner agencies track greenhouse gases for space, air, and ground. our scientists model the flow of these gases around our planet.\n\n\n\n\n\n\n\n", "hits": 96 }, { "id": 5095, "url": "https://svs.gsfc.nasa.gov/5095/", "result_type": "Visualization", "release_date": "2023-04-20T00:00:00-04:00", "title": "USFS/GEDI Old Growth Forest Visualizations", "description": "This visualization begins with a view of USFS Forest Inventory and Analysis (FIA) plot locations (orange dots) across the continental US. 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an example of the 2017 Thomas Fire, Southern California. || thomas_fire_FINAL_035_HD.04500_print.jpg (1024x576) [211.6 KB] || thomas_fire_FINAL_035_HD.04500_searchweb.png (320x180) [81.0 KB] || thomas_fire_FINAL_035_HD.04500_thm.png (80x40) [6.0 KB] || thomas_fire_FINAL_035_HD_1080p59.94.mp4 (1920x1080) [28.5 MB] || 1920x1080_16x9_60p (1920x1080) [256.0 KB] || thomas_fire_FINAL_035_HD_1080p59.94.webm (1920x1080) [6.9 MB] || thomas_fire_FINAL_035_4k_2160p59.94.mp4 (3840x2160) [90.0 MB] || 9600x3240_16x9_30p (9600x3240) [128.0 KB] || 3840x2160_16x9_60p (3840x2160) [256.0 KB] || ", "hits": 35 }, { "id": 5006, "url": "https://svs.gsfc.nasa.gov/5006/", "result_type": "Visualization", "release_date": "2022-11-06T00:00:00-04:00", "title": "Global Biosphere March 2017 - Feb 2022", "description": "Example composite of 5 years of Mollweide projected data of Earth's biosphere beginning March 2017 through February 2022. || newbio_v34_mollweide_comp1130_print.jpg (1024x512) [186.1 KB] || newbio_v34_mollweide_comp1130_searchweb.png (180x320) [94.2 KB] || newbio_v34_mollweide_comp1130_thm.png (80x40) [7.4 KB] || Example_Composite (2000x1000) [0 Item(s)] || newbio_v34_mollweide_comp_1000p30.mp4 (2000x1000) [40.4 MB] || newbio_v34_mollweide_comp_1000p30.webm (2000x1000) [4.5 MB] || ", "hits": 83 }, { "id": 5019, "url": "https://svs.gsfc.nasa.gov/5019/", "result_type": "Visualization", "release_date": "2022-10-14T11:00:00-04:00", "title": "PACE orbit with swaths and instrument fields of view", "description": "PACE orbiting the Earth showing OCI, HARP2, and SPEXone instument fields of view followed by instrument ground swath patterns || pace_orbit_swath.42_FINAL_HD.09000_print.jpg (1024x576) [110.6 KB] || pace_orbit_swath.42_FINAL_HD.09000.png (1920x1080) [10.1 MB] || pace_orbit_swath.42_FINAL_HD.09000_searchweb.png (320x180) [72.6 KB] || pace_orbit_swath.42_FINAL_HD.09000_thm.png (80x40) [4.6 KB] || pace_orbit_swath.42_FINAL_HD_1080p59.94.mp4 (1920x1080) [70.0 MB] || 1920x1080_16x9_60p (1920x1080) [0 Item(s)] || pace_orbit_swath.42_FINAL_HD_1080p59.94.webm (1920x1080) [20.3 MB] || 3840x2160_16x9_60p (3840x2160) [0 Item(s)] || 9600x3240_16x9_30p (9600x3240) [0 Item(s)] || pace_orbit_swath.42_FINAL_4K_2160p59.94.mp4 (3840x2160) [269.9 MB] || ", "hits": 132 }, { "id": 40447, "url": "https://svs.gsfc.nasa.gov/gallery/visualizationsfor-educators/", "result_type": "Gallery", "release_date": "2022-08-17T00:00:00-04:00", "title": "Visualizations for Educators", "description": "Phenomena are observable events that occur in nature. Data visualizations can offer new ways for students to experience and explore Earth and space phenomena that happen over large scales of time and at great distances. This gallery includes visualizations of phenomena that support topics that are taught in middle and high school and are aligned with select Next Generation Science Standards.\n\n\nThis gallery was curated by Anne Arundle County Science Teachers Margaret Graham and Jeremy Milligan with support from Dr. Rachel Connolly during the summer of 2022. A video showing how Jeremy Milligan uses SVS resources to develop a phenomena-based lesson is also available.", "hits": 256 }, { "id": 4915, "url": "https://svs.gsfc.nasa.gov/4915/", "result_type": "Visualization", "release_date": "2021-08-09T00:00:00-04:00", "title": "A Global view of Normalized Difference Vegetation Index (NDVI) Anomaly in crop-growing regions from 2000 to 2021", "description": "This visualization shows the NDVI anomaly from the year 2000 to 2021 in areas where maize, rice, soybeans, spring wheat or winter wheat are grown. Green colors indicate more than average vegetatation while orange colors indicate less productive areas.Coming soon to our YouTube channel. || NDVI_anomaly_2000-2021.11770.png (1920x1080) [897.2 KB] || NDVI_anomaly_2000-2021.11770_print.jpg (1024x576) [79.6 KB] || NDVI_anomaly_2000-2021.11770_searchweb.png (320x180) [39.8 KB] || NDVI_anomaly_2000-2021.11770_thm.png (80x40) [4.5 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || NDVI_anomaly_2000-2021_1080p30.webm (1920x1080) [60.4 MB] || NDVI_anomaly_2000-2021_1080p30.mp4 (1920x1080) [146.7 MB] || 3840x2160_16x9_30p (3840x2160) [0 Item(s)] || captions_silent.31356.en_US.srt [43 bytes] || NDVI_Anomaly_2000_2021_4k_2160p30.mp4 (3840x2160) [608.3 MB] || NDVI_anomaly_2000-2021_1080p30.mp4.hwshow [196 bytes] || ", "hits": 340 }, { "id": 4916, "url": "https://svs.gsfc.nasa.gov/4916/", "result_type": "Visualization", "release_date": "2021-08-09T00:00:00-04:00", "title": "Normalized Difference Vegetation Index (NDVI) Anomaly in crop-growing regions for selected years", "description": "This visualization shows the NDVI anomaly in areas where maize, rice, soybeans, spring wheat or winter wheat are grown over the United States, Australia, Russia, Europe and southern Africa during certain years. Green colors indicate more than average vegetatation while orange colors indicate less productive areas.Coming soon to our YouTube channel. || NDVI_anomaly_regions.1020_print.jpg (1024x576) [140.2 KB] || NDVI_anomaly_regions.1020_searchweb.png (320x180) [72.6 KB] || NDVI_anomaly_regions.1020_thm.png (80x40) [5.9 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || NDVI_anomaly_regions_1080p30.mp4 (1920x1080) [110.9 MB] || captions_silent.31363.en_US.srt [43 bytes] || NDVI_anomaly_regions_1080p30.mp4.hwshow [194 bytes] || ", "hits": 101 }, { "id": 4813, "url": "https://svs.gsfc.nasa.gov/4813/", "result_type": "Visualization", "release_date": "2020-04-21T00:00:00-04:00", "title": "Earth Day 2020: Biosphere", "description": "Global Biosphere data from 1997 through 2017 with corresponding colorbars and date stamp.This video is also available on our YouTube channel. || earthday_bio_comp.0000_print.jpg (1024x576) [95.0 KB] || earthday_bio_comp.0000_searchweb.png (320x180) [51.5 KB] || earthday_bio_comp.0000_thm.png (80x40) [5.0 KB] || earthday_biosphere_composite (1920x1080) [0 Item(s)] || earthday_bio_comp_1080p30.webm (1920x1080) [17.9 MB] || earthday_bio_comp_1080p30.mp4 (1920x1080) [106.0 MB] || captions_silent.29351.en_US.srt [43 bytes] || earthday_bio_comp_1080p30.mp4.hwshow [191 bytes] || ", "hits": 51 }, { "id": 4816, "url": "https://svs.gsfc.nasa.gov/4816/", "result_type": "Visualization", "release_date": "2020-04-20T00:00:00-04:00", "title": "Earth Day 2020: Normalized Difference Vegetation Index (NDVI) Seasonal Cycles", "description": "NDVI Seasonal Cycles, With LabelsThis video is also available on our YouTube channel. || ndvi_w_labels.00001_print.jpg (1024x576) [66.3 KB] || ndvi_w_labels.00001_searchweb.png (320x180) [42.2 KB] || ndvi_w_labels.00001_thm.png (80x40) [3.9 KB] || ndvi_w_labels.webm (1920x1080) [6.8 MB] || ndvi_w_labels.mp4 (1920x1080) [111.8 MB] || captions_silent.29562.en_US.srt [43 bytes] || ndvi_w_labels.mp4.hwshow [373 bytes] || ", "hits": 54 }, { "id": 40413, "url": "https://svs.gsfc.nasa.gov/gallery/earth-science-playlist/", "result_type": "Gallery", "release_date": "2020-04-01T00:00:00-04:00", "title": "Earth Science Playlist", "description": "No description available.", "hits": 12 }, { "id": 4782, "url": "https://svs.gsfc.nasa.gov/4782/", "result_type": "Visualization", "release_date": "2020-03-04T00:00:00-05:00", "title": "Vegetation Index Anomalies and Rift Valley fever (RVF) outbreaks in South Africa region: 2008-2011", "description": "This visualization with corresponding data dashboard shows the relationship between vegetation index anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal vegetaion over land (green) and RVF outbreak locations (orange pins). || NDVI_RVF_SAfrica_Composite_3840x2160_2657_print.jpg (1024x576) [102.7 KB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657_searchweb.png (320x180) [57.8 KB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657_thm.png (80x40) [5.0 KB] || NDVI_RVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [35.6 MB] || NDVI_RVF_SAfrica_Composite_1920x1080p30.webm (1920x1080) [7.1 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || NDVI_RVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [72.6 MB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657.tif (3840x2160) [31.6 MB] || ", "hits": 29 }, { "id": 4783, "url": "https://svs.gsfc.nasa.gov/4783/", "result_type": "Visualization", "release_date": "2020-02-27T00:00:00-05:00", "title": "Precipitation Anomaly and Rift Valley fever (RVF) outbreaks in South Africa: 2008-2011", "description": "This visualization with corresponding data dashboard shows the relationship between precipitation anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal precipitation over land (blue) and RVF outbreak locations (orange pins). || PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg (1024x576) [97.8 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_searchweb.png (320x180) [57.6 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_thm.png (80x40) [5.2 KB] || PrecipRVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [31.5 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || PrecipRVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [68.2 MB] || PrecipRVF_SAfrica_Composite_3840x2160_3422.tif (3840x2160) [4.0 MB] || PrecipRVF_SAfrica_Composite_3840x2160_p30.webm (3840x2160) [14.1 MB] || ", "hits": 39 }, { "id": 4724, "url": "https://svs.gsfc.nasa.gov/4724/", "result_type": "Visualization", "release_date": "2020-02-21T00:00:00-05:00", "title": "Vegetation index anomalies and Rift Valley fever (RVF) outbreaks in Africa and Middle East during 2000-2018", "description": "Data visualization featuring vegetation index anomalies over Africa and Middle East and locations of Rift Valley Fever (RVF) outbreaks (orange pins) during the period of 2000-2018. Frames are provided in 4K resolution. || Africa_NDVIRVF_2000_2018_3840x2160_2430_print.jpg (1024x576) [78.8 KB] || Africa_NDVIRVF_2000_2018_3840x2160_2430_searchweb.png (320x180) [48.8 KB] || Africa_NDVIRVF_2000_2018_3840x2160_2430_thm.png (80x40) [4.4 KB] || Africa_NDVIRVFComposite_2000_2018_3840x2160_1080p30.mp4 (1920x1080) [88.7 MB] || Africa_NDVIRVFComposite_2000_2018_3840x2160_1080p30.webm (1920x1080) [25.5 MB] || Africa_NDVIRVF_2000_2018_Composite (3840x2160) [0 Item(s)] || Africa_NDVIRVF_2000_2018_3840x2160_2430.tif (3840x2160) [6.0 MB] || Africa_NDVIRVFComposite_2000_2018_3840x2160_p30.mp4 (3840x2160) [283.2 MB] || ", "hits": 30 }, { "id": 4747, "url": "https://svs.gsfc.nasa.gov/4747/", "result_type": "Visualization", "release_date": "2020-02-21T00:00:00-05:00", "title": "Vegetation index anomalies and Rift Valley fever (RVF) outbreaks in South Africa during 2009-2011", "description": "This visualization shows the relationship between vegetation index anomalies (Normalized Difference Vegetation Index - NDVI) data and outbreak locations of Rift Valley fever (RVf) during 2008 and 2011. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa slowly to take a closer look at the above normal vegetation (green) and RVF outbreak locations (orange pins). Frames are provided in 4K resolution. || SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg (1024x576) [86.2 KB] || SAfrica_NDVIRVFwDates_3840x2160_1263_searchweb.png (320x180) [56.0 KB] || SAfrica_NDVIRVFwDates_3840x2160_1263_thm.png (80x40) [4.5 KB] || SAfrica_NDVIRVFComposite_1080p30.mp4 (1920x1080) [31.6 MB] || SAfrica_NDVIRVFComposite_1080p30.webm (1920x1080) [7.0 MB] || Composite (3840x2160) [0 Item(s)] || SAfrica_NDVIRVFwDates_3840x2160_1263.tif (3840x2160) [7.6 MB] || SAfrica_NDVIRVFComposite_3840x2160_p30.mp4 (3840x2160) [96.4 MB] || ", "hits": 22 }, { "id": 4784, "url": "https://svs.gsfc.nasa.gov/4784/", "result_type": "Visualization", "release_date": "2020-02-21T00:00:00-05:00", "title": "ENSO Teleconnections and Rift Valley fever (RVF) Outbreaks", "description": "During the 2008-2011 period, ENSO events brought changes to weather conditions across the globe that triggered infectious disease outbreaks, such as mosquito-borne Rift Valley fever (RVF) in South Africa. This visualization with corresponding data dashboard shows how Sea Surface Temperature (SST) anomalies in the equatorial Pacific Ocean (left) gave rise to Precipitation (center) and Vegetation (right) Index Anomalies in South Africa. During La Niña events, Southern Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus. However, in rare cases there is a departure from this canonical response, as we can observe in 2009-2010, when a mild El Niño event resulted in above normal vegetaton and a large RVF outbreak in South Africa. || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960_print.jpg (1024x576) [107.8 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png (320x180) [63.0 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_thm.png (80x40) [6.5 KB] || ENSO_Teleconnections (1920x1080) [0 Item(s)] || SST_Precip_NDVI_Dashboard_2008_2011_1920x1080_p30.mp4 (1920x1080) [22.7 MB] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.mp4 (3840x2160) [56.0 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.webm (3840x2160) [10.2 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960.tif (3840x2160) [3.4 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525.tif (3840x2160) [3.4 MB] || ", "hits": 43 }, { "id": 4785, "url": "https://svs.gsfc.nasa.gov/4785/", "result_type": "Visualization", "release_date": "2020-01-09T00:00:00-05:00", "title": "Sea Surface Temperature Anomalies and Patterns of Global Disease Outbreaks: 2009-2018 (4K version)", "description": "This webpage provides the 4K version of: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated), released on January 6, 2020.Content has been created for 4K display systems that can handle finer resolution and details. It is recommended to use content from this version for HD (1920x1080) and lower resolutions. || ", "hits": 65 }, { "id": 4781, "url": "https://svs.gsfc.nasa.gov/4781/", "result_type": "Visualization", "release_date": "2020-01-06T00:00:00-05:00", "title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated)", "description": "This visualization shows the variability in global sea surface temperature anomalies, the associated ENSO index timeline and locations of infectious disease outbreaks over the global land surface. || CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg (1024x576) [135.9 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_searchweb.png (320x180) [82.6 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_thm.png (80x40) [7.1 KB] || Composite_StrongElNino (1920x1080) [0 Item(s)] || Composite_StrongElNino (1920x1080) [0 Item(s)] || CompositeWLabel_2009_2018_1920x1080_p30.mp4 (1920x1080) [22.1 MB] || CompositeWLabel_2009_2018_1920x108060fps_1705.tif (1920x1080) [1.3 MB] || CompositeWLabel_2009_2018_1920x1080_p30.webm (1920x1080) [4.6 MB] || CompositeWLabel_2009_2018_1920x1080_p30.mp4.hwshow [205 bytes] || ", "hits": 113 }, { "id": 4765, "url": "https://svs.gsfc.nasa.gov/4765/", "result_type": "Visualization", "release_date": "2019-12-10T00:00:00-05:00", "title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018", "description": "El Niño is an irregularly recurring climate pattern characterized by warmer than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions. This visualization captures monthly Sea Surface Temperature (SST) anomalies around the world from 2009-2018, along with locations of global disease outbreaks and a corresponding timeline showcasing the Niño 3.4 Index. The Niño 3.4 Index represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the above average El Niño years, in which sea surface temperature anomalies peaked during 2015-2016. || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg (1024x576) [130.6 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_searchweb.png (320x180) [79.7 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_thm.png (80x40) [7.0 KB] || Composite (1920x1080) [0 Item(s)] || Composite (1920x1080) [0 Item(s)] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4 (1920x1080) [23.0 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769.tif (1920x1080) [1.3 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.webm (1920x1080) [4.7 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4.hwshow [211 bytes] || ", "hits": 117 }, { "id": 31053, "url": "https://svs.gsfc.nasa.gov/31053/", "result_type": "Hyperwall Visual", "release_date": "2019-12-02T00:00:00-05:00", "title": "Global Vegetation Index, Terra MODIS", "description": "One of the primary interests of NASA's Earth Sciences Program is to study the role of terrestrial vegetation in large-scale processes with the goal of understanding how our world functions as a system. These maps show Normalized Difference Vegetation Index (NDVI) values—a measure of the \"greenness\" of Earth's landscapes—from February 2000 to the present. The values, derived using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite, range from -0.1 to 0.9 and have no unit. Rather, they are index values in which higher values (0.4 to 0.9) show lands covered by green, leafy vegetation and lower values (0 to 0.4) show lands where there is little or no vegetation. Dark green areas show where there was a lot of green leaf growth; light greens show where there was some green leaf growth; and tan areas show little or no growth. Black means no data. || ", "hits": 193 }, { "id": 40388, "url": "https://svs.gsfc.nasa.gov/gallery/nasaearth-science/", "result_type": "Gallery", "release_date": "2019-09-13T10:53:37-04:00", "title": "NASA Earth Science", "description": "NASA’s Earth Science Division (ESD) missions help us to understand our planet’s interconnected systems, from a global scale down to minute processes. Working in concert with a satellite network of international partners, ESD can measure precipitation around the world, and it can employ its own constellation of small satellites to look into the eye of a hurricane. ESD technology can track dust storms across continents and mosquito habitats across cities.\n\nFor more information:\nhttps://science.nasa.gov/earth-science", "hits": 197 }, { "id": 4695, "url": "https://svs.gsfc.nasa.gov/4695/", "result_type": "Visualization", "release_date": "2019-02-28T09:00:00-05:00", "title": "Niño 3.4 Index and Sea Surface Temperature Anomaly Timeline: 1982-2017", "description": "This visualization captures Sea Surface Temperature (SST) anomalies around the world from 1982 to 2017, along with a corresponding timeplot graph focusing on the Niño 3.4 SST Index region (5N-5S, 120W-170W), which represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the El Niño years, in which sea surface temperature anomalies peaked: 1982-1983, 1997-1998, and 2015-2016. || NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg (1024x576) [104.9 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_searchweb.png (320x180) [72.1 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_thm.png (80x40) [6.8 KB] || SST_Nino3.4Index_1982_2017_Composite (1920x1080) [0 Item(s)] || NINO3.4SST_FlatMapComposite_1920x1080_p30.mp4 (1920x1080) [57.2 MB] || NINO3.4SST_FlatMapComposite_1920x1080_00932.tif (1920x1080) [1.4 MB] || NINO3.4SST_FlatMapComposite_1920x1080_p30.webm (1920x1080) [9.3 MB] || SSTNino3.4Index_1982_2017_Composite (3840x2160) [0 Item(s)] || ", "hits": 664 }, { "id": 4700, "url": "https://svs.gsfc.nasa.gov/4700/", "result_type": "Visualization", "release_date": "2018-12-05T09:00:00-05:00", "title": "PACE - Studying Plankton, Aerosols, Clouds, and the Ocean Ecosystem", "description": "The visualization starts close on the PACE spacecraft. A representative data swath is shown, depicting biosphere plankton data. The camera then pulls out to show the spacecraft's polar orbit. Complete global coverage is achieved after approximately two days of orbits. Over time, the data swath cycles between biosphere, aerosol, and cloud data, representing PACE's collective mission to study Earth's ocean and atmosphere. This version end with animated biosphere data. || pace_v2_4k_0245_print.jpg (1024x576) [36.4 KB] || pace_v2_4k_0245_searchweb.png (320x180) [39.7 KB] || pace_v2_4k_0245_thm.png (80x40) [3.7 KB] || pace_v3_1080p30.mp4 (1920x1080) [30.0 MB] || pace_comp3_animated-biosphere (3840x2160) [0 Item(s)] || pace_v3_2160p30.mp4 (3840x2160) [94.4 MB] || pace_v3_2160p30.webm (3840x2160) [19.1 MB] || 600-science-overview-003.hwshow || ", "hits": 45 }, { "id": 4634, "url": "https://svs.gsfc.nasa.gov/4634/", "result_type": "Visualization", "release_date": "2018-06-28T09:00:00-04:00", "title": "Global Fire Weather Database", "description": "The Global Fire WEather Database (GFWED) integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. It is based on the Fire Weather Index (FWI) System, which tracks the dryness of three general fuel classes, and the potential behavior of a fire if it were to start. Each day, FWI values are calculated from global weather data, including satellite rainfall data from the Global Precipitation Measurement (GPM) mission.The FWI System is the most widely used fire danger rating system in the world, and has been adopted for different boreal, temperate and tropical fire environments. GFWED provides a globally consistent fire weather dataset for fire researchers and managers to apply locally. The Fire Weather Index component is suitable as a general index of fire danger. Globally, shifts in continental-scale fire activity follow seasonal changes in the FWI. Over South America and Africa, regions of high FWI and active agricultural burning shift with the tropical rain belts, seen in the GPM precipitation overlay. Over North America and Eurasia, the FWI will ‘activate’ in the spring, and shows how week-to-week surges in fire activity can be driven by high FWI values. || ", "hits": 91 }, { "id": 12667, "url": "https://svs.gsfc.nasa.gov/12667/", "result_type": "Produced Video", "release_date": "2018-06-28T00:00:00-04:00", "title": "NASA Rainfall Data and Global Fire Weather", "description": "Additional footage courtesy of Greenpeace.Music: \"Vulnerable Moment,\" John Ashton Thomas, Atmosphere Music Ltd.; \"Inducing Waves,\" Ben Niblett and Jon Cotton, Atmosphere Music Ltd.Complete transcript available. || fires_thumb_print.jpg (1024x578) [88.2 KB] || fires_thumb_searchweb.png (320x180) [93.8 KB] || fires_thumb_thm.png (80x40) [7.0 KB] || Fires_GPM_prores.mov (1920x1080) [3.7 GB] || Fires_GPM_facebook_720.mp4 (1280x720) [385.5 MB] || Fires_GPM_large.mp4 (1920x1080) [271.4 MB] || Fires_GPM_twitter_720.mp4 (1280x720) [60.4 MB] || Fires_GPM_youtube_720.mp4 (1280x720) [513.6 MB] || Fires_GPM_youtube_1080.mp4 (1920x1080) [526.2 MB] || Fires_GPM_prores.webm (1920x1080) [30.3 MB] || 12667_Fires.en_US.srt [5.2 KB] || 12667_Fires.en_US.vtt [5.2 KB] || ", "hits": 29 }, { "id": 40348, "url": "https://svs.gsfc.nasa.gov/gallery/esddatafor-societal-benefits/", "result_type": "Gallery", "release_date": "2018-04-24T00:00:00-04:00", "title": "ESD data for Societal Benefit", "description": "No description available.", "hits": 176 }, { "id": 12770, "url": "https://svs.gsfc.nasa.gov/12770/", "result_type": "Produced Video", "release_date": "2018-03-19T18:00:00-04:00", "title": "Harmonized Landsat 8 and Sentinel-2 Data", "description": "Landsat 8 and Sentinel-2 satellites have spectral and spatial similarities that make using their data together possible. When the data are used together observations can be more timely and accurate. The HLS project is an effort to \"harmonize\" the data of the two satellite programs so that they can be more easily used in unison. The ultimate goal is to obtain seamless 2-3 day global surface reflectance coverage at 30 meters that removes residual differences between the sensors due to spectral bandpass and view geometry. Currently the v1.3 HLS data set encompasses 82 global test sites that cover about 7% of the global land area.Using the processing power of the NASA Earth Exchange (NEX) computer cluster at NASA Ames, the HLS workflow atmospherically corrects data from the satellites, geographically tiles the Landsat data in a manor matching the Sentinel-2 tiling, and then corrects for different sensor view angles (Bidirectional Reflectance Distribution Function, or BRDF) and does a slight band pass adjustment for the Sentinel-2 data to create the harmonized 30-meter product.The HLS team includes researchers from NASA Goddard Space Flight Center, the University of Maryland, and NASA Ames Research Center. || ", "hits": 63 }, { "id": 4597, "url": "https://svs.gsfc.nasa.gov/4597/", "result_type": "Visualization", "release_date": "2017-11-16T15:00:00-05:00", "title": "Earth: Our Living Planet (Updated)", "description": "Twenty years of global biosphere data mapped on a slowly spinning globe. || slow_spin_4k.5542_print.jpg (1024x576) [83.1 KB] || slow_spin_4k.5542_searchweb.png (320x180) [48.3 KB] || slow_spin_4k.5542_thm.png (80x40) [4.4 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || slow_spin_1080p30.webm (1920x1080) [17.8 MB] || slow_spin_1080p30.mp4 (1920x1080) [119.2 MB] || 3840x2160_16x9_30p (3840x2160) [0 Item(s)] || slow_spin_4k.mp4 (3840x2160) [397.0 MB] || ", "hits": 67 }, { "id": 4596, "url": "https://svs.gsfc.nasa.gov/4596/", "result_type": "Visualization", "release_date": "2017-11-14T17:00:00-05:00", "title": "20 Years of Global Biosphere (updated)", "description": "This Mollweide projected data visualization shows 20 years of Earth's biosphere starting in September 1997 going through September 2017. Data for this visualization was collected from multiple satellites over the past twenty years. || biosphere7_mollweide.4507_print.jpg (576x1024) [192.2 KB] || biosphere7_mollweide.4507_searchweb.png (180x320) [91.0 KB] || biosphere7_mollweide.4507_thm.png (80x40) [7.4 KB] || mollweide_annotated (1920x1080) [0 Item(s)] || biosphere7_mollweide_1080p30.webm (1920x1080) [17.8 MB] || biosphere7_mollweide_1080p30.mp4 (1920x1080) [264.8 MB] || biosphere7_mollweide_1080p30.mp4.hwshow || ", "hits": 131 }, { "id": 4590, "url": "https://svs.gsfc.nasa.gov/4590/", "result_type": "Visualization", "release_date": "2017-10-27T00:00:00-04:00", "title": "Southern Africa Drought", "description": "When a giant swell of warm water, known as El Niño emerged in the Pacific Ocean in 2015, scientists knew to look for impacts. As El Niño changed global weather patterns Southern Africa went into severe drought. On top of already dry conditions, the region experienced its lowest rainfall in 35 years.With the Soil Moisture Active Passive (SMAP) mission, launched in 2015, NASA has dedicated soil moisture measurements for the first time – and could see this severe drought emerging. SMAP's highly sensitive microwave radiometer detects the energy emitted by soil depending on how wet or how dry it is. The old gardener's trick is to squeeze a handful of dirt in your hand and see whether it clumps or falls apart. Think of SMAP doing the same thing – with a lot more precision, all around the world, every 3 days.SMAP allowed us to see a connection between Pacific Ocean water temperatures and the moisture of the soil in Southern Africa. These measurements are now being put to operational use more than ever. SMAP's data was fed into the USDA's global crop yield forecasts – the Foreign Agriculture Service reports that help drive multi-billion dollar commodity markets around the world. In fact, the Foreign Ag Service scientist for this region said that with SMAP they now have the first reliable soil moisture data in 30 years.As crops failed and soils were left bare, we used the Terra and Aqua satellites to assess these effects on the vegetation from a local to regional scale. The Normalized Differential Vegetation Index (NDVI) reflects the health of vegetation on the land surface.As this drought spread across Southern Africa, nearly 30 million people were at risk of drastic food shortages. Four out of 10 people did not have access to clean drinking water.The analyses and data provided by NASA scientists are also critical to a USAID program called the Famine Early Warning Systems Network. As food crises arise, the global view provided by NASA scientists informs decisions about where governments and relief agencies should send help.In Southern Africa in 2015 and 2016, nearly 350 million dollars of emergency water and food aid were delivered, in part based on NASA data, to aid millions of people.As the peak of the drought hits in January 2016, the animations show the low soil moisture conditions in Zambia, Zimbabwe, and Botswana. Correspondingly the low vegetation appears in that region as well. || ", "hits": 22 }, { "id": 40323, "url": "https://svs.gsfc.nasa.gov/gallery/applied-science/", "result_type": "Gallery", "release_date": "2017-03-30T00:00:00-04:00", "title": "Applied Science", "description": "Discovering innovative and practical uses of Earth observations\n\nappliedsciences.nasa.gov", "hits": 83 }, { "id": 40317, "url": "https://svs.gsfc.nasa.gov/gallery/vcearth-video-wall/", "result_type": "Gallery", "release_date": "2017-02-02T00:00:00-05:00", "title": "VC Earth Video Wall", "description": "list of videos to display on video wall in Earth science exhibit at Goddard Visitor Center", "hits": 8 }, { "id": 40415, "url": "https://svs.gsfc.nasa.gov/gallery/whats-newwith-earth-today/", "result_type": "Gallery", "release_date": "2015-01-04T00:00:00-05:00", "title": "What's New with Earth Today", "description": "Explore the latest visualizations of NASA's Earth Observing satellites and the data they collect. NASA researchers are constantly tracking remote-sensing data and modeling processes to better understand our home planet.", "hits": 178 }, { "id": 10280, "url": "https://svs.gsfc.nasa.gov/10280/", "result_type": "Produced Video", "release_date": "2014-12-17T05:30:00-05:00", "title": "Vegetation Response to Lower Colorado River pulse flow in 2014", "description": "Using data from NASA/USGS satellite Landsat 8, scientists have measured how vegetation in the Colorado River Delta has responded to the pulse of water released in March 2014 as part of the Minute 319 bi-national agreement.For complete transcript, click here.Watch this video on the NASA Goddard YouTube channel. || G2014-108_Colorado_Pulse.png (1280x720) [1.6 MB] || G2014-108_Colorado_Pulse_web.png (320x180) [107.0 KB] || G2014-108_Colorado_Pulse-youtube.mov (1280x720) [122.1 MB] || G2014-108_Colorado_Pulse-youtube_appletv.m4v (960x540) [56.2 MB] || G2014-108_Colorado_Pulse_MASTER_prores.mov (1280x720) [2.0 GB] || G2014-108_Colorado_Pulse-youtube_1280x720.wmv (1280x720) [64.6 MB] || G2014-108_Colorado_Pulse-youtube_appletv_subtitles.m4v (960x540) [56.1 MB] || G2014-108_Colorado_Pulse-youtube_720x480.webm (720x480) [15.5 MB] || G2014-108_Colorado_Pulse-youtube_nasaportal.mov (640x360) [55.5 MB] || G2014-108_Colorado_Pulse-youtube_ipod_lg.m4v (640x360) [22.7 MB] || G2014-108_Colorado_Pulse-youtube_720x480.wmv (720x480) [57.5 MB] || G2014-108_Colorado_Pulse-captions.en_US.vtt [2.4 KB] || G2014-108_Colorado_Pulse-captions.en_US.srt [2.4 KB] || G2014-108_Colorado_Pulse-youtube_ipod_sm.mp4 (320x240) [12.4 MB] || ", "hits": 25 }, { "id": 4205, "url": "https://svs.gsfc.nasa.gov/4205/", "result_type": "Visualization", "release_date": "2014-09-24T09:00:00-04:00", "title": "Earth Science Heads-up Display", "description": "On September 10, 2014, NASA's Earth Observing System (EOS) was celebrated in an evening event at the Smithsonian National Air and Space Museum in Washington DC. The title of this event was \"Vital Signs: Taking the Pulse of Our Planet\", and the speakers at this event included several Earth Scientists from Goddard Space Flight Center. This animation was used in the beginning of the event to illustrate the interconnectedness of the many Earth-based data sets that NASA has produced over the last decade or so. The animation simulates a view of the Earth from the International Space Station, over which interconnected data sets are displayed as if on a head-up display. || ", "hits": 60 }, { "id": 30515, "url": "https://svs.gsfc.nasa.gov/30515/", "result_type": "Hyperwall Visual", "release_date": "2014-06-30T13:00:00-04:00", "title": "Simulated Atmospheric Carbon Concentrations", "description": "Carbon exists in many forms—e.g., carbon dioxide (CO2), carbon monoxide (CO)—and continually cycles through Earth’s atmosphere, ocean, and terrestrial ecosystems. This visualization, created using data from the 7-km GEOS-5 Nature Run model, shows average column concentrations of atmospheric CO2 (colored shades) and CO (white shades underneath) from January 1, 2006 to December 31, 2006.CO2 variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and pink shades represent regions where CO2 concentrations are enhanced by carbon sources, mainly from human activities. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of CO2 through photosynthesis, thus removing CO2 from the atmosphere. Atmospheric CO, a pollutant harmful to human health, is produced mainly from fossil fuel combustion and biomass burning. Here, high concentrations of CO (white) are mainly from fire activity in Africa, South America, and Australia. Scientists use model output data such as these to help answer important questions about Earth’s climate and to help design future satellite missions.These model simulations use fossil fuel emissions estimates provided by the Emissions Database for Global Atmospheric Research (EDGAR). NASA’s Quick Fire Emissions Dataset (QFED) estimates fire emissions using MODIS fire radiative power observations. Additional, observationally constrained estimates of CO2 flux between the atmosphere and land and ocean carbon reservoirs were produced as part of NASA’s Carbon Monitoring System Flux Pilot Project (http://carbon.nasa.gov/cgi-bin/cms/inv_pgp.pl?pgid=581). Land biosphere fluxes come from the Carnegie-Ames-Stanford Approach Global Fire Emissions Database (CASA-GFED) model which incorporates MODIS vegetation classification and AVHRR Normalized Difference Vegetation Index (NDVI) data. Ocean fluxes are produced by the NASA Ocean Biogeochemical Model (NOBM) which incorporates MODIS chlorophyll observations. || ", "hits": 57 }, { "id": 4162, "url": "https://svs.gsfc.nasa.gov/4162/", "result_type": "Visualization", "release_date": "2014-04-23T10:00:00-04:00", "title": "Drought may take a toll on Congo Rainforest, NASA Satellites Show", "description": "A new analysis of NASA satellite data shows that Africa's Congo rainforest, the second-largest tropical rainforest in the world, has undergone a large-scale decline in greenness over the past decade.The study, lead by Liming Zhou of University at Albany, State University of New York, shows that between 2000 and 2012, the decline affected an increasing amount of forest area and intensified. The research, published April 23 in Nature, is one of the most comprehensive observational studies to explore the effects of long-term drought on Congolese rainforests using several independent satellite sensors.Scientists use the satellite-derived \"greenness\" of forest regions as one indicator of a forest's health. While this study looks specifically at the impact of a persistent drought in the Congo region since 2000, researchers say that a continued drying trend might alter the composition and structure of the Congo rainforest, affecting its biodiversity and carbon storage.\"It's important to understand these changes because most climate models predict that tropical forests may be under stress due to increasing severe water shortages in a warmer and drier 21st century climate,\" Zhou said.Previous research used satellite-based measurements of vegetation greenness to investigate changes in the Amazon rainforest, notably the effects of severe short-term droughts in 2005 and 2010. Until now, little attention has been paid to African rainforests, where ground measurements are even sparser than in the Amazon and where droughts are less severe but last longer.To clarify the impact of long-term drought on the Congo rainforest, Zhou and colleagues set out to see if they could detect a trend in a satellite measure of vegetation greenness called the Enhanced Vegetation Index. This measure is developed from data produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Terra satellite. The scientists focused their analysis on intact, forested regions in the Congo basin during the months of April, May and June each year - the first of the area's two peak rainy and growing seasons each year.The study found a gradually decreasing trend in Congo rainforest greenness, sometimes referred to as \"browning,\" suggesting a slow adjustment to the long-term drying trend. This is in contrast to the more immediate response seen in the Amazon, such as large-scale tree mortality, brought about by more episodic drought events.The browning of the forest canopy is consistent with observed decreases in the amount of water available to plants, whether that's in the form of rainfall, water stored in the ground, water in near-surface soils, or water within the vegetation. || ", "hits": 80 }, { "id": 4100, "url": "https://svs.gsfc.nasa.gov/4100/", "result_type": "Visualization", "release_date": "2013-11-08T11:00:00-05:00", "title": "Fluorescence Visualizations in High-Resolution (Comparison to NDVI)", "description": "During photosynthesis, plants fluoresce. This faint glow is in the infrared part of the spectrum, not visible to the naked eye but detectable by satellites orbiting hundreds of miles above Earth. NASA scientists established a method to turn this satellite data into global maps of the subtle phenomenon in more detail than ever before.The new maps, released in 2013, provide a 16-fold increase in spatial resolution and a 3-fold increase in temporal resolution over the first proof-of-concept maps released in 2011. This lets scientists use fluorescence to observe, for example, variation in the length of the growing season.These visualizations of the phenomenon shows global land plant fluorescence data collected from 2007 to 2011, combined to depict a single average year. Darker greens indicates regions with little or no fluorescence; lighter greens and white indicate regions of high fluorescence.Fluorescence and Normalized Difference Vegetation Index (NDVI) are compared. A visualization is provided comparing the northern hemisphere of both data sets. Individual visualizations are also provided in a standard cylindrical equidistant projection for wrapping to a globe. The same color bars are used for both data sets for easier comparison. || ", "hits": 33 }, { "id": 30375, "url": "https://svs.gsfc.nasa.gov/30375/", "result_type": "Hyperwall Visual", "release_date": "2013-10-24T12:00:00-04:00", "title": "16-Day Vegetation Index", "description": "One of the primary interests of NASA's Earth Sciences Program is to study the role of terrestrial vegetation in large-scale processes with the goal of understanding how our world functions as a system. These maps show 16-day Normalized Difference Vegetation Index (NDVI) values—a measure of the \"greenness\" of Earth's landscapes—from February 18, 2000 to the present. The values, derived using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite, range from -0.1 to 0.9 and have no unit. Rather, they are index values in which higher values (0.4 to 0.9) show lands covered by green, leafy vegetation and lower values (0 to 0.4) show lands where there is little or no vegetation. Dark green areas show where there was a lot of green leaf growth; light greens show where there was some green leaf growth; and tan areas show little or no growth. Black means no data. || ", "hits": 75 }, { "id": 30376, "url": "https://svs.gsfc.nasa.gov/30376/", "result_type": "Hyperwall Visual", "release_date": "2013-10-24T12:00:00-04:00", "title": "Monthly Vegetation Index", "description": "One of the primary interests of NASA's Earth Sciences Program is to study the role of terrestrial vegetation in large-scale processes with the goal of understanding how our world functions as a system. These maps show monthly Normalized Difference Vegetation Index (NDVI) values—a measure of the \"greenness\" of Earth's landscapes—from February 2000 to the present. The values, derived using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite, range from -0.1 to 0.9 and have no unit. Rather, they are index values in which higher values (0.4 to 0.9) show lands covered by green, leafy vegetation and lower values (0 to 0.4) show lands where there is little or no vegetation. Dark green areas show where there was a lot of green leaf growth; light greens show where there was some green leaf growth; and tan areas show little or no growth. Black means no data. || ", "hits": 40 }, { "id": 30377, "url": "https://svs.gsfc.nasa.gov/30377/", "result_type": "Hyperwall Visual", "release_date": "2013-10-24T12:00:00-04:00", "title": "16-Day Vegetation Anomaly", "description": "The map is based on the Normalized Difference Vegetation Index (NDVI), a measure of how plant leaves absorb visible light and reflect infrared light. Drought-stressed vegetation reflects more visible light and less infrared than healthy vegetation. The vegetation index helps us see how much or how little live plant material is out there. || ", "hits": 27 }, { "id": 30379, "url": "https://svs.gsfc.nasa.gov/30379/", "result_type": "Hyperwall Visual", "release_date": "2013-10-24T12:00:00-04:00", "title": "Monthly Leaf Area Index", "description": "Have you ever wondered how many leaves there are in a forest? Today, scientists use NASA satellites to map leaf area index—images processed to show how much of an area is covered by leaves. For example, a leaf area index of 1 means the area is entirely covered by one layer of leaves. These maps show monthly leaf area index from February 2000 to the present, produced using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite. The colors in this palette range from tan, showing little or no leaf cover, to light green, indicating the area is entirely covered by one layer of leaves, to dark green showing thick forest canopies, where seven or more layers of leaves cover an area. Black means no data. Knowing the total area covered by leaves helps scientists monitor how much water, carbon, and energy the trees and plants are exchanging with the air above and the ground below. || ", "hits": 56 }, { "id": 3877, "url": "https://svs.gsfc.nasa.gov/3877/", "result_type": "Visualization", "release_date": "2013-10-01T00:00:00-04:00", "title": "Dynamic Earth Dome Show - Biosphere", "description": "This visualization was a prototype affiliated with the 'Dynamic Earth', an Earth science planetarium show. The visualization shows the global biosphere and NDVI from the SeaWiFS instrument with MODIS ice and snow overlayed.The images were rendered using a fish eye technique so that they would project properly onto a planetarium dome.Earth scientists are able to measure many of the Earth's 'vital signs', and just like a doctor measures our vital signs to see how healthy we are. Scientists will use these measurements of the Earth to better understand how the Earth functions, how the different systems on Earth interact and how those interactions have set the stage upon which life flourishes. The visualization shows a timeseries of images of SeaWiFS Global Biosphere - the ocean's long-term average phytoplankton chlorophyll concentration acquired between September 1997 and September 2007 combined with the SeaWiFS-derived Normalized Difference Vegetation Index over land. On land, the dark greens show where there is abundant vegetation and tans show relatively sparse plant cover. In the oceans, red, yellow, and green pixels show dense phytoplankton blooms, those regions of the ocean that are the most productive over time, while blues and purples show where there is very little of the microscopic marine plants called phytoplankton. Remote sensing, especially using satellite-mounted colour scanners (SeaWiFS and similar platforms), is advocated for broad-based monitoring of chlorophyll once appropriate algorithms have been developed and proved. The concentration of the photosynthetic pigment chlorophyll a (referred to as chlorophyll) in marine waters is a proven indicator of the biomass of phytoplankton, the organisms that constitute the base of the marine food web. Fluorometry provides an estimate of chlorophyll levels in sea water and thus an estimate of primary productivity in the upper part of the water column.For more information on monitoring the Earth from Space with SeaWIFS see http://oceancolor.gsfc.nasa.gov/SeaWiFS/TEACHERS/. || ", "hits": 36 }, { "id": 4071, "url": "https://svs.gsfc.nasa.gov/4071/", "result_type": "Visualization", "release_date": "2013-05-08T12:00:00-04:00", "title": "Normalized Differential Vegetation Index critical to Agricultural Monitoring in Ukraine, Russia, and Kazakhstan", "description": "On April 29-30, 2012 the G8 International Conference on Open Data for Agriculture brought together open data and agriculture experts along with the U.S. Agriculture Secretary U.S. Chief Technology Officer, and the World Bank Vice President for Sustainable Development to explore more opportunities for open data and knowledge sharing. Governments want to help their farmers protect crops from pests and extreme weather, monitor water supplies and anticipate planting seasons that are shifting due to climate change. New satellite technologies offer enhanced capabilities for early forecasting of food production at national, regional, and global scales. The Group on Earth Observations (GEO) Global Agricultural Monitoring (GEOGLAM) program aims to strengthen national capacity in all countries from freely available data.These visuals show MODIS' satellite-derived crop NDVI Anomaly relative to average (2000-2011). Orange and brown indicate crop with below average conditions. Green indicates crop with above averate conditions. || ", "hits": 33 }, { "id": 4072, "url": "https://svs.gsfc.nasa.gov/4072/", "result_type": "Visualization", "release_date": "2013-05-08T12:00:00-04:00", "title": "Normalized Differential Vegetation Index critical to Agricultural Monitoring in the United States", "description": "On April 29-30, 2012 the G8 International Conference on Open Data for Agriculture brought together open data and agriculture experts along with the U.S. Agriculture Secretary U.S. Chief Technology Officer, and the World Bank Vice President for Sustainable Development to explore more opportunities for open data and knowledge sharing. Governments want to help their farmers protect crops from pests and extreme weather, monitor water supplies and anticipate planting seasons that are shifting due to climate change. New satellite technologies offer enhanced capabilities for early forecasting of food production at national, regional, and global scales. The Group on Earth Observations (GEO) Global Agricultural Monitoring (GEOGLAM) program aims to strengthen national capacity in all countries from freely available data.These visuals show MODIS' satellite-derived crop NDVI Anomaly relative to average (2000-2011). Orange and brown indicate crop with below average conditions. Green indicates crop with above averate conditions. The visual compares the crop conditions or NDVI anomaly from year 2011-2012 to year 2012-2013. In the 2012-2013 year 7,342 more metric tons (MT) of wheat were produced then in the previous year, but 40,086 fewer metric tons of corn were produced. || ", "hits": 144 }, { "id": 4055, "url": "https://svs.gsfc.nasa.gov/4055/", "result_type": "Visualization", "release_date": "2013-03-19T00:00:00-04:00", "title": "Seasonal Vegetation and Snow Change", "description": "To determine the density of green on a patch of land, researchers must observe the wavelengths of visible and near-infrared sunlight reflected by the plants. The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from 0.4 um - 0.7 um). Vegetation strongly reflects near-infrared light (from 0.7 -1.0 um). The more healthy leaves a plant has, the more the the visible light will be absorbed and the near-infrared will be reflected. In this animation, dark green indicates dense, healthy vegetation, whereas beige areas represent bare soil. Snow from the MODIS instruments is overlaid on top. || ", "hits": 63 }, { "id": 4044, "url": "https://svs.gsfc.nasa.gov/4044/", "result_type": "Visualization", "release_date": "2013-02-27T00:00:00-05:00", "title": "The Distributed Water Balance of the Nile Basin", "description": "This visualization shows how satellite data and NASA models are being applied to study the hydrology of the Nile basin. The Tropical Rainfall Measurement Mission (TRMM) Multisensor Precipitation Analysis (TMPA) provides three-hourly estimates of rainfall rate across much of the globe. Here we see the seasonal cycle of monthly precipitation derived from TMPA for Africa, including the Nile Basin. The annual migration of the Intertropical Convergence Zone (ITCZ) from the Nile Equatorial Lakes region around Lake Victoria, source of the White Nile, northward into Sudan and the highlands of Ethiopia, headwaters of the Blue Nile, and back is evident in the seasonal cycle in precipitation. This precipitation cycle drives flow through the Nile River system. The Nile basin, however, is intensely evaporative, and the majority of the water that falls as rain leaves the basin as evaporation rather than river flow—either from the humid headwaters regions or from large reservoirs and irrigation developments in Egypt and Sudan. The Atmosphere Land Exchange Inverse (ALEXI) evapotranspiration product, developed by USDA scientists, uses satellite data to map daily evapotranspiration across the entire Nile basin, providing unprecedented information on water consumption. The balance of rainfall and evapotranspiration can be seen in seasonal patterns of soil moisture, as simulated by the NASA Nile Land Data Assimilation System (LDAS), which merges satellite information with a physically-based land surface model to simulate variability in soil moisture—a critical variable for rainfed agriculture and natural ecosystems. Finally, the twin satellites of the Gravity Recovery and Climate Experiment (GRACE) can be used to monitor variability in total water storage, including surface water, soil moisture, and groundwater. The annual cycle in GRACE estimates of water storage anomalies clearly shows the seasonal movement of water storage due to precipitation patterns and the movement of surface waters from headwaters regions into the wetlands of South Sudan and the reservoirs of the lower Nile basin.The Nile is the longest river in the world and its basin is shared by 11 countries. Reliable, spatially distributed estimates of hydrologic storage and fluxes can provide critical information for water managers contending with multiple resource demands, a variable and changing climate, and the risk of damaging floods and droughts. NASA observations and modeling systems offer unique capabilities to meet these information needs. || ", "hits": 82 }, { "id": 4015, "url": "https://svs.gsfc.nasa.gov/4015/", "result_type": "Visualization", "release_date": "2012-12-05T00:00:00-05:00", "title": "Drought 2010-2012", "description": "The Evaporative Stress Index (ESI) provides objective, high-resolution information about the evaporation of water from land surface. The ESI model combines satellite data with other meteorological factors to determine how much water is used by crops and vegetation. The resulting data helps to detect drought.This visualization shows ESI data for 2010, 2011, and 2012. 2010 was a relatively wet year despite occasional drought. In 2011, the ESI shows extremely dry conditions across all of Texas, Louisiana, and Oklahoma, tracking one of the country's most devastating droughts. In 2012, the ESI shows plant stress in the Corn Belt region as early as May. These warning signs later developed into a full drought that impacted the world's corn and soy been supply.The kind of early-warning detection system ESI provides will enhance the US arsenal of drought monitoring tools and help farmers adapt to drought before it evolves. || ", "hits": 24 }, { "id": 4011, "url": "https://svs.gsfc.nasa.gov/4011/", "result_type": "Visualization", "release_date": "2012-11-28T00:00:00-05:00", "title": "United States Active Fires 2012", "description": "Records maintained by the National Interagency Fire Center (NIFC) and NASA both indicate that 2012 was an extraordinary year for wildfires in the United States.NIFC statistics show that more than 9.1 million acres had burned as of November 30, 2012—the third highest total in a record that dates back to 1960. Also notable: despite the high number of acres burned in 2012, the total number of fires—55,505—was low, the least on the NIFC record. Average fire size in 2012 was the highest on the record.The visualizations depict fires that burned between January 1 and October 31, 2012, as detected by the MODIS instruments. The fires are displayed over MODIS' vegetation and snow cover data. Yellow and orange indicates fires that were more intense and had a larger area of active burning. Most of these intense fires occurred in the western United States, where lightning and human activity often sparks blazes that firefighters cannot contain. Many of the lower intensity fires shown in red were prescribed fires, lit for either agricultural or ecosystem management purposes.The Terra and Aqua Moderate Resolution Imaging Spectrometer (MODIS) can routinely detect both flaming and smoldering fires that are aproximately 1000 square meters in size. Under pristine and extremely rare observing conditions even smaller flaming fires that are aproximately 50 square meters can be detected. Each active fire location represents the center of a 1 km pixel that is flagged by the algorithm as containing a fire within the pixel. For more information on the fire data, see the MODIS Collection 5 Active Fire Product User's Guide. For more information on the algorithm, see Giglio, L., J. Descloitres, C. O. Justice, and Y. J. Kaufman. 2003. An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment, 87:273-282 || ", "hits": 35 }, { "id": 3947, "url": "https://svs.gsfc.nasa.gov/3947/", "result_type": "Visualization", "release_date": "2012-07-08T00:00:00-04:00", "title": "Watching the Earth Breathe:
An Animation of Seasonal Vegetation and its effect on Earth's Global Atmospheric Carbon Dioxide", "description": "In this animation, NASA instruments show the seasonal cycle of vegetation and the concentration of carbon dioxide in the atmosphere. The animation begins on January 1, when the northern hemisphere is in winter and the southern hemisphere is in summer. At this time of year, the bulk of living vegetation, shown in green, hovers around the equator and below it, in the southern hemisphere.As the animation plays forward through mid-April, the concentration of carbon dioxide, shown in orange-yellow, in the middle part of Earth's lowest atmospheric layer, the troposphere, increases and spreads throughout the northern hemisphere, reaching a maximum around May. This blooming effect of carbon dioxide follows the seasonal changes that occur in northern latitude ecosystems, in which deciduous trees lose their leaves, resulting in a net release of carbon dioxide through a process called respiration. Carbon dioxide is also released in early spring as soils begin to warm. Almost 10 percent of atmospheric carbon dioxide passes through soils each year.After April, the northern hemisphere moves into late spring and summer and plants begin to grow, reaching a peak in the late summer. The process of plant photosynthesis removes carbon dioxide from the air. The animation shows how carbon dioxide is scrubbed out of the atmosphere by the large volume of new and growing vegetation. Following the peak in vegetation, the drawdown of atmospheric carbon dioxide due to photosynthesis becomes apparent, particularly over the boreal forests.Note that there is roughly a three-month lag between the state of vegetation at Earth's surface and its effect on carbon dioxide in the middle troposphere.Data like these give scientists a new opportunity to better understand the relationships between carbon dioxide in Earth's middle troposphere and the seasonal cycle of vegetation near the surface.Creating the AnimationThis animation was created with data taken from two NASA spaceborne instruments. The concentration of carbon dioxide data from the Atmospheric Infrared Sounder (AIRS), a weather and climate instrument that flies aboard NASA's Aqua spacecraft, is overlain on measurements of vegetation index from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on NASA's Aqua spacecraft, to better understand how photosynthesis and respiration influences the atmospheric carbon dioxide cycle over the globe. The animation runs from January through December and repeats. The AIRS tropospheric carbon dioxide seasonal cycle values were made by averaging AIRS data collected between 2003 and 2010, from which the annual carbon dioxide growth trend of 2 parts per million per year has been removed. For example, the data used for January 1 is actually an average of eight years of AIRS carbon dioxide data taken each year on January 1. The vegetation values were made using data averaged over a four-year period, from 2003 to 2006.Further DetailAIRS uses infrared technology to determine the concentration of atmospheric water vapor and several important trace gases as well as information about temperature and clouds. AIRS orbits Earth from pole-to-pole at an altitude of 438 miles (705 kilometers), measuring Earth's infrared spectrum in 3,278 channels spanning a wavelength range from 3.74 microns to 15.4 microns. Originally designed to improve weather forecasts, AIRS has improved operational five-day weather forecasts more than any other single instrument over the past decade. AIRS has also been found to be sensitive to atmospheric carbon dioxide in the middle troposphere, at an altitude of 5 to 10 kilometers or 3 to 6 miles. AIRS is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena. For further information, access the AIRS projectThe MODIS instrument is managed by NASA's Goddard Space Flight Center, Greenbelt, Md. For further information, access the MODIS project. || ", "hits": 169 }, { "id": 3905, "url": "https://svs.gsfc.nasa.gov/3905/", "result_type": "Visualization", "release_date": "2012-04-13T09:00:00-04:00", "title": "Mapping Diseases", "description": "The print-resolution still images were created for the February 2012 issue of The Scientist (print and online). In an article in the same issue, NASA scientist Assaf Anyamba explains how he can predict diseases with remote-sensing data.The data used are: 1. NDVI is an index that quantifies the photosynthetic capacity of vegetation. It is derived from visible and near-infrared reflectance measurements made by Advanced Very High Resolution Radiometer (AVHRR) sensors onboard NOAA's polar orbiting satellites (in this case NOAA-17). Taken as time series measurements, NDVI indicates the response of vegetation to seasonal and interannual variations in climate.2. SST data are a blend of direct observations from ships, buoys, satellite imagery also from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) instruments, and SSTs simulated by sea-ice cover. The monthly optimum interpolated fields were derived by a linear interpolation of the weekly fields to daily fields, and then averaging daily values over a month.All anomaly fields (as shown here) are derived by subtracting the monthly values from the respective long-term monthly means. || ", "hits": 27 }, { "id": 10851, "url": "https://svs.gsfc.nasa.gov/10851/", "result_type": "Produced Video", "release_date": "2011-10-20T16:00:00-04:00", "title": "A Look Back at a Decade of Fires", "description": "For more than a decade, instruments on Terra and Aqua, two of NASA's flagship Earth-observing satellites, have scanned the surface of our planet for fires four times a day. The instruments, both Moderate Resolution Imaging Spectroradiometers (MODIS), have revolutionized what scientists know about fire's role in land cover change, ecosystem processes, and the global carbon cycle by allowing researchers to map the characteristics and global distribution of fires in remarkable detail. The collection of videos below provides perspective on how global fires impact humans and our planet. || ", "hits": 59 }, { "id": 3870, "url": "https://svs.gsfc.nasa.gov/3870/", "result_type": "Visualization", "release_date": "2011-10-18T23:00:00-04:00", "title": "African Fire Observations and MODIS NDVI", "description": "From space, we can understand fires in ways that are impossible from the ground. The MODIS instrument onboard the Terra and Aqua satellite, was specifically designed to detect fires. As a result, it can see both smaller fires and a wide range of fires from cool grass fires to raging forest fires. Burning carbon particles both on the tiny soot particles in the flame and on the fuel itself emit a very specific wavelength of light, 3.8 to 4 microns. NASA research has contributed to much improved detection of fire for scientific purposes using satellite remote sensing and geographic information systems. This has helped advance our understanding of the impacts of fire in many areas of earth science, including atmospheric chemistry and the impacts on protected areas. This research has led to the development of a rapid response system widely used throughout the world for both natural resource management and for firefighting by providing near real-time information. The visualization shows fires detected in Africa from July 2002 through July 2011. Africa has more abundant burning than any other continent. MODIS observations have shown that some 70 percent of the world's fires occur in Africa alone. \"It's incredibly satisfying to see such a long record of fires visualized,\" said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. \"It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth.\"More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/. || ", "hits": 37 }, { "id": 3869, "url": "https://svs.gsfc.nasa.gov/3869/", "result_type": "Visualization", "release_date": "2011-10-18T19:00:00-04:00", "title": "Boreal Forest Fire Observations and MODIS NDVI", "description": "NASA has released a series of new visualizations that show the locations of the millions of fires detected by key fire-monitoring instruments on NASA satellites over the last decade. This visualization shows fire observations made by the MODerate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites in Europe and Asia from July 2002 through July 2011. \"It's incredibly satisfying to see such a long record of fires visualized,\" said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. \"It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth.\"More information on the Fire Information for Resource Management System (FIRMS) is available at https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms. || ", "hits": 29 }, { "id": 3871, "url": "https://svs.gsfc.nasa.gov/3871/", "result_type": "Visualization", "release_date": "2011-10-18T19:00:00-04:00", "title": "Australia Fire Observations and MODIS NDVI", "description": "From space, we can understand fires in ways that are impossible from the ground. The MODIS instrument onboard the Terra and Aqua satellite, was specifically designed to detect fires. This visualization shows fire detections from July 2002 through July 2011. The visualization also includes vegetation and snow cover data to show how fires respond to seasonal changes. The tour begins in Australia in 2002 by showing a network of massive grassland fires spreading across interior Australia as well as the greener Eucalyptus forests in the northern and eastern part of the continent.More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/. || ", "hits": 23 }, { "id": 3872, "url": "https://svs.gsfc.nasa.gov/3872/", "result_type": "Visualization", "release_date": "2011-10-18T19:00:00-04:00", "title": "South American Fire Observations and MODIS NDVI", "description": "From space, we can understand fires in ways that are impossible from the ground. NASA research has contributed to much improved detection of fire for scientific purposes using satellite remote sensing and geographic information systems. This visualization of South America shows fire observations made by MODerate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites . South America exhibits a steady flickering of fire across much of the Amazon rainforest with peaks of activity in September and November. Almost all of the fires in the Amazon are the direct result of human activity, including slash-and-burn agriculture, because the high moisture levels in the region prevent inhibit natural fires from occurring.More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/. || ", "hits": 47 }, { "id": 3873, "url": "https://svs.gsfc.nasa.gov/3873/", "result_type": "Visualization", "release_date": "2011-10-18T19:00:00-04:00", "title": "United States Fire Observations and MODIS NDVI", "description": "From space, we can understand fires in ways that are impossible from the ground. NASA has released a series of new visualizations that show fires detected by key fire-monitoring instruments on NASA satellites over the last decade. The visualizations show fire observations made by MODerate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites. The visualization also includes vegetation and snow cover data to show how fires respond to seasonal changes. \"It's incredibly satisfying to see such a long record of fires visualized,\" said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. \"It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth.\" North America is a region where fires are comparatively rare. North American fires make up just 2 percent of the world's burned area each year. The fires that receive the most attention in the United States, the uncontrolled forest fires in the West, are less visible than the wave of agricultural fires prominent in the Southeast and along the Mississippi River Valley, but some of the large wildfires that struck Texas earlier this spring are visible.More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/. || ", "hits": 23 }, { "id": 3868, "url": "https://svs.gsfc.nasa.gov/3868/", "result_type": "Visualization", "release_date": "2011-10-18T01:00:00-04:00", "title": "Global Fire Observations and MODIS NDVI", "description": "This visualization leads viewers on a narrated global tour of fire detections beginning in July 2002 and ending July 2011. The visualization also includes vegetation and snow cover data to show how fires respond to seasonal changes. The tour begins in Australia in 2002 by showing a network of massive grassland fires spreading across interior Australia as well as the greener Eucalyptus forests in the northern and eastern part of the continent. The tour then shifts to Asia where large numbers of agricultural fires are visible first in China in June 2004, then across a huge swath of Europe and western Russia in August, and then across India and Southeast Asia through the early part of 2005. It moves next to Africa, the continent that has more abundant burning than any other. MODIS observations have shown that some 70 percent of the world's fires occur in Africa alone. In what's a fairly average burning season, the visualization shows a huge outbreak of savanna fires during the dry season in Central Africa in July, August, and September of 2006, driven mainly by agricultural activities but also by the fact that the region experiences more lightning than anywhere else in the world. The tour shifts next to South America where a steady flickering of fire is visible across much of the Amazon rainforest with peaks of activity in September and November of 2009. Almost all of the fires in the Amazon are the direct result of human activity, including slash-and-burn agriculture, because the high moisture levels in the region prevent inhibit natural fires from occurring. It concludes in North America, a region where fires are comparatively rare. North American fires make up just 2 percent of the world's burned area each year. The fires that receive the most attention in the United States, the uncontrolled forest fires in the West, are less visible than the wave of agricultural fires prominent in the Southeast and along the Mississippi River Valley, but some of the large wildfires that struck Texas earlier this spring are visible. More information on the Fire Information for Resource Management System (FIRMS) is available at http://maps.geog.umd.edu/firms/. || ", "hits": 42 }, { "id": 3807, "url": "https://svs.gsfc.nasa.gov/3807/", "result_type": "Visualization", "release_date": "2011-08-31T00:00:00-04:00", "title": "Predicting Disease Outbreaks from Space", "description": "These visualizations were created for the May 18, 2012 Library of Congress Talk Predictiding Disease Outbreaks from Space. In this talk NASA scientist Assaf Anyamba, will present how using remote-sensing data we can see links among weather, diseases and famine.An early warning system more than a decade in development successfully predicted the 2006-2007 outbreak of the deadly Rift Valley Fever (RVF) in East Africa and subsequent outbreaks in Sudan (2007) and South Africa (2008-2011). RVF is a deadly hemorrhagic disease transmitted by mosquitoes that infects livestock and human populations episodically. An international team of research scientists, public-health professionals, agricultural specialists and military personnel had worked for a decade to successfully predict when and where an outbreak of RVF would occur. || ", "hits": 21 }, { "id": 3764, "url": "https://svs.gsfc.nasa.gov/3764/", "result_type": "Visualization", "release_date": "2010-08-19T14:00:00-04:00", "title": "How Much Carbon do Plants Take from the Atmosphere?", "description": "Plant life converts atmospheric carbon dioxide into biomass through photosynthesis, a process called 'fixing'. This is one of the main ways in which carbon dioxide is removed from the atmosphere and is a major part of the carbon cycle. The amount of carbon removed is called the gross primary productivity (GPP), and the change in GPP due to rising global temperatures is very important factor in the response of the Earth to climate change.Data from the MODIS instrument on NASA's Terra satellite has been recently used to calculate the GPP for the whole world for the last 10 years. This animation shows a time sequence of GPP on land as measured by MODIS during the years 2000 through 2009. Two things to note are the year-long productivity of the tropical regions and the large seasonal productivity in the northern hemisphere. A close look at the animation also reveals major urban areas for which the productivity is negligible.For a look at why the decade from 2000 through 2009 meant lower productivity, see the page 'How has the Atmospheric Carbon Uptake from Plants Changed in the Last Decade?' || ", "hits": 337 }, { "id": 3765, "url": "https://svs.gsfc.nasa.gov/3765/", "result_type": "Visualization", "release_date": "2010-08-19T14:00:00-04:00", "title": "How has the Atmospheric Carbon Uptake from Plants Changed in the Last Decade?", "description": "Plant life converts atmospheric carbon dioxide into biomass through photosynthesis. This process, called fixing, is one of the main ways in which carbon dioxide is removed from the atmosphere and is a major part of the carbon cycle. Plants release a fraction of this fixed carbon by respiration in order to get energy to live and to move carbon to other organs. The amount of carbon removed minus the amount of carbon respired is called the net primary productivity (NPP) and is the amount of carbon turned into biomass.The change in NPP due to rising global temperatures is a very important factor in the response of the Earth to climate change. Measurements of radiation and leaf area from the MODIS instrument on NASA's Terra satellite have recently been used to calculate the change in NPP for the whole world for the last 10 years. This animation shows a time sequence of annual NPP deviation from normal (or 'anomaly') on land as measured by MODIS during the years 2000 through 2009. Annual NPP, especially its departures from a long-term mean condition, will demonstrate the effects of environmental drivers such as ENSO (El Niño) events, climate change, droughts, pollution episodes, land degradation, and agricultural expansion.Earlier studies of productivity between 1982 and 1999 showed that prouctivity went up as global temperatures rose, because longer, warmer growing seasons were better for plant growth. This new study indicates that this is still true in the northern hemisphere, but that increased temperatures have meant increased drought and dryness in the tropics and the southern hemisphere. As a result, the global net productivity has actually decreased in the period from 2000 through 2009.Regionally, negative annual NPP anomalies were mainly caused by large-scale droughts. In 2000, droughts reduced NPP in North America and China; in 2002, droughts reduced NPP in North America and Australia; in 2003, drought caused by a major heat wave reduced NPP in Europe; in 2005, severe droughts in the Amazon, Africa, and Australia greatly reduced both regional and global NPP; from 2007 through 2009 over large parts of Australia, continuous droughts reduced continental NPP.For an animation of daily productivity, see the page How Much Carbon do Plants Take from the Atmosphere?. || ", "hits": 113 }, { "id": 10605, "url": "https://svs.gsfc.nasa.gov/10605/", "result_type": "Produced Video", "release_date": "2010-07-02T00:00:00-04:00", "title": "Know Your Earth: Earth Observing Fleet Studies Climate", "description": "This animated video shares a series of fascinating facts about how climate change affects oceans, land, the atmosphere, and ice sheets around the world. With the help of an animated astronaut touring the Earth, the video explains how NASA's Earth observing satellite fleet enables scientists to gather accurate data and understand those changes.For complete transcript, click here. || G2010-072_Know_Your_Earth_youtube_hq.02196_print.jpg (1024x576) [105.9 KB] || G2010-072_Know_Your_Earth_youtube_hq_web.png (320x180) [281.3 KB] || G2010-072_Know_Your_Earth_youtube_hq_thm.png (80x40) [17.6 KB] || G2010-072_Know_Your_Earth_appletv.webmhd.webm (960x540) [41.1 MB] || G2010-072_Know_Your_Earth_appletv.m4v (960x540) [99.6 MB] || G2010-072_Know_Your_Earth_prores.mov (1280x720) [2.9 GB] || G2010-072_Know_Your_Earth_Final.wmv (1280x720) [89.9 MB] || G2010-072_Know_Your_Earth_youtube_hq.mov (1280x720) [105.0 MB] || G2010-072_Know_Your_Earth_ipod_lg.m4v (640x360) [33.5 MB] || G2010-072_Know_Your_Earth.m4v (320x240) [18.1 MB] || G2010-072_Know_Your_Earth_SVS.mpg (512x288) [27.1 MB] || ", "hits": 102 }, { "id": 3707, "url": "https://svs.gsfc.nasa.gov/3707/", "result_type": "Visualization", "release_date": "2010-05-01T00:00:00-04:00", "title": "Five Spheres - Land Changes through NDVI", "description": "Satellite data can be used to monitor the health of plant life from space. The Normalized Difference Vegetation Index (NDVI) provides a simple numerical indicator of the health of vegetation which can be used to monitoring changes in vegetation over time. This animation shows the seasonal changes in vegetation by fading between average monthly NDVI data from 2004. This animation of land changes is match framed to animation id a003708, a003709, a003710, and a003711. || ", "hits": 87 }, { "id": 40026, "url": "https://svs.gsfc.nasa.gov/gallery/nasaand-agriculture-old/", "result_type": "Gallery", "release_date": "2010-03-03T00:00:00-05:00", "title": "NASA and Agriculture", "description": "NASA's fleet of satellites has been watching over Earth for more than half a century, collecting valuable data about the crops that make up our food supply and the water it takes to grow them. This wealth of information allows scientists to monitor farmland – tracking the overall food supply, where specific crops are grown, and how much water it takes to grow them with data from the Landsat satellites and others.", "hits": 14 }, { "id": 10574, "url": "https://svs.gsfc.nasa.gov/10574/", "result_type": "Produced Video", "release_date": "2010-02-22T00:00:00-05:00", "title": "Piecing Together the Temperature Puzzle", "description": "The decade from 2000 to 2009 was the warmest in the modern record. \"Piecing Together the Temperature Puzzle\" illustrates how NASA satellites enable us to study possible causes of climate change. The video explains what role fluctuations in the solar cycle, changes in snow and cloud cover, and rising levels of heat-trapping gases may play in contributing to climate change. For complete transcript, click here. || Temperature_Puzzle_fullres.01252_print.jpg (1024x576) [113.2 KB] || Temperature_Puzzle_fullres_web.png (320x180) [207.8 KB] || Temperature_Puzzle_fullres_thm.png (80x40) [16.9 KB] || Temperature_Puzzle_AppleTV.webmhd.webm (960x540) [83.9 MB] || Temperature_Puzzle_fullres.mov (1280x720) [166.2 MB] || Temperature_Puzzle_AppleTV.m4v (960x720) [211.4 MB] || Temperature_Puzzle__Youtube.mov (1280x720) [87.7 MB] || Temperature_Puzzle_iPod_small.m4v (640x360) [67.9 MB] || Temperature_Puzzle_iPod_large.m4v (320x180) [27.9 MB] || Temperature_Puzzle_svs.mpg (512x288) [136.6 MB] || Temperature_Puzzle_portal.wmv (346x260) [38.8 MB] || ", "hits": 79 }, { "id": 3651, "url": "https://svs.gsfc.nasa.gov/3651/", "result_type": "Visualization", "release_date": "2009-10-07T12:00:00-04:00", "title": "World Droughts From 2005 to 2009 Versus Where Crops are Grown", "description": "The Global Inventory Monitoring and Modeling Studies (GIMMS) group at NASA Goddard Space Flight Center (NASA/GSFC) provides United States Department of Agriculture/Foreign Agricultural Service (USDA/FAS) with global data stream of NDVI that spans over two decades (1981-present). The GIMMS NDVI is derived from measurements made by the Advanced Very High Resolution Radiometer (AVHRR), Global Area Coverage (GAC) data from the National Atmospheric Oceanic Administration (NOAA) polar orbiting series of satellites. GIMMS has inter-calibrated the data from the NOAA-AVHRR satellite series and performed atmospheric correction to minimize the effects of volcanic aerosols to produce and maintain a consistent NDVI archive. The NDVI archive from GIMMS provides the historic database for monitoring the response of vegetation to climatic conditions.Linking the MODIS data to the long-term GIMMS AVHRR/NDVI, archive and SPOT Vegetation sensor data is a critical component of this project providing a consistent multi-source long-term data record for agricultural monitoring. This allows FAS analysts to compare current data with the spatial extent and severity of NDVI anomalies associated with heat stress, droughts and floods associated with crop failures. || ", "hits": 15 }, { "id": 3629, "url": "https://svs.gsfc.nasa.gov/3629/", "result_type": "Visualization", "release_date": "2009-10-05T12:00:00-04:00", "title": "Crop Intensity", "description": "The U.S. Department of Agriculture (USDA) and the National Aeronautics and Space Administration (NASA) signed a Memorandum of Understanding (MOU) to strengthen collaboration. In support of this collaboration, NASA and the USDA Foreign Agricultural Service (FAS) jointly funded a new project to assimilate NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data and products into an existing decision support system (DSS) operated by the International Production Assessment Division (IPAD) of FAS. To meet its objectives, FAS/IPAD uses satellite data and data products to monitor agriculture worldwide and to locate and keep track of natural disasters such as short and long term droughts, floods and persistent snow cover which impair agricultural productivity. FAS is the largest user of satellite imagery in the non-military sector of the U.S. government. For the last 20 years FAS has used a combination of Landsat and NOAA-AVHRR satellite data to monitor crop condition and report on episodic events.To successfully monitor worldwide agricultural regions and provide accurate agricultural production assessments, it is important to understand the spatial distribution of croplands. To do this a global croplands mask to identify all sites used for crop production. Croplands are highly variable both temporally and spatially. Croplands vary from year to year due to events such as drought and fallow periods, and they vastly differ across the globe in accordance with characteristics such as cropping intensity and field size. A flexible crop likelihood mask is used to help depict these varying characteristics of global crop cover. Regions featuring intensive agro-industrial farming practices such as the Maize Triangle in South Africa will have higher confidence values in the crop mask as compared to less intensively farmed regions in parts of Sub-Saharan Africa where cropland identification is partly confounded with natural background vegetation phenologies. Thus, a customized threshold can be employed to examine areas of varying cropping intensification. || ", "hits": 32 }, { "id": 3646, "url": "https://svs.gsfc.nasa.gov/3646/", "result_type": "Visualization", "release_date": "2009-10-05T12:00:00-04:00", "title": "2009 Crop Intensity, 2009 Producers, and 2050 Projected Population", "description": "The U.S. Department of Agriculture (USDA) and the National Aeronautics and Space Administration (NASA) signed a Memorandum of Understanding (MOU) to strengthen collaboration. In support of this collaboration, NASA and the USDA Foreign Agricultural Service (FAS) jointly funded a new project to assimilate NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data and products into an existing decision support system (DSS) operated by the International Production Assessment Division (IPAD) of FAS. To meet its objectives, FAS/IPAD uses satellite data and data products to monitor agriculture worldwide and to locate and keep track of natural disasters such as short and long term droughts, floods and persistent snow cover which impair agricultural productivity. FAS is the largest user of satellite imagery in the non-military sector of the U.S. government. For the last 20 years FAS has used a combination of Landsat and NOAA-AVHRR satellite data to monitor crop condition and report on episodic events.To successfully monitor worldwide agricultural regions and provide accurate agricultural production assessments, it is important to understand the spatial distribution of croplands. To do this a global croplands mask to identify all sites used for crop production. Croplands are highly variable both temporally and spatially. Croplands vary from year to year due to events such as drought and fallow periods, and they vastly differ across the globe in accordance with characteristics such as cropping intensity and field size. A flexible crop likelihood mask is used to help depict these varying characteristics of global crop cover. Regions featuring intensive agro-industrial farming practices such as the Maize Triangle in South Africa will have higher confidence values in the crop mask as compared to less intensively farmed regions in parts of Sub-Saharan Africa where cropland identification is partly confounded with natural background vegetation phenologies. Thus, a customized threshold can be employed to examine areas of varying cropping intensification. || ", "hits": 13 }, { "id": 10490, "url": "https://svs.gsfc.nasa.gov/10490/", "result_type": "Produced Video", "release_date": "2009-09-22T23:00:00-04:00", "title": "Science For a Hungry World: Introduction", "description": "As the first of six episodes, Science for a Hungry World: Part 1 sets the groundwork for explaining why NASA data is critical to ensure a stable global food system. This video reveals how satellite remote sensing data provide the world with essential information like the Normalized Difference Vegetation Index, or NDVI, which allows scientists and governments to see the health of crops on a global scale. This video reinforces the idea that a unique perspective from space is essential for continuous global agricultural monitoring and accurate forecasting.For complete transcript, click here. || Science_for_a_Hungry_World_Part_1_320x240.01627_print.jpg (1024x576) [111.9 KB] || Science_for_a_Hungry_World_Part_1_320x240_thm.png (80x40) [17.4 KB] || Science_for_a_Hungry_World_Part_1_320x240_web.png (180x320) [152.7 KB] || Science_for_a_Hungry_World_Part_1_AppleTV.webmhd.webm (960x540) [68.9 MB] || Science_for_a_Hungry_World_Part_1_AppleTV.m4v (960x540) [174.3 MB] || Science_for_a_Hungry_World_Part_1_H264_1280x720.mov (1280x720) [194.6 MB] || Science_for_a_Hungry_World_Part_1_640x480_ipod.m4v (640x360) [57.4 MB] || Science_for_a_Hungry_World_Part_1_for_Rob.m4v (640x360) [39.4 MB] || Science_for_a_Hungry_World_Part_1_320x240.mp4 (320x180) [22.5 MB] || Science_for_a_Hungry_World_Part_1.wmv (320x236) [37.8 MB] || bigmovie-science_for_a_hungry_world_1-introduction.hwshow || ", "hits": 27 }, { "id": 3619, "url": "https://svs.gsfc.nasa.gov/3619/", "result_type": "Visualization", "release_date": "2009-09-01T18:00:00-04:00", "title": "A Tour of the Cryosphere 2009", "description": "The cryosphere consists of those parts of the Earth's surface where water is found in solid form, including areas of snow, sea ice, glaciers, permafrost, ice sheets, and icebergs. In these regions, surface temperatures remain below freezing for a portion of each year. Since ice and snow exist relatively close to their melting point, they frequently change from solid to liquid and back again due to fluctuations in surface temperature. Although direct measurements of the cryosphere can be difficult to obtain due to the remote locations of many of these areas, using satellite observations scientists monitor changes in the global and regional climate by observing how regions of the Earth's cryosphere shrink and expand.This animation portrays fluctuations in the cryosphere through observations collected from a variety of satellite-based sensors. The animation begins in Antarctica, showing some unique features of the Antarctic landscape found nowhere else on earth. Ice shelves, ice streams, glaciers, and the formation of massive icebergs can be seen clearly in the flyover of the Landsat Image Mosaic of Antarctica. A time series shows the movement of iceberg B15A, an iceberg 295 kilometers in length which broke off of the Ross Ice Shelf in 2000. Moving farther along the coastline, a time series of the Larsen ice shelf shows the collapse of over 3,200 square kilometers ice since January 2002. As we depart from the Antarctic, we see the seasonal change of sea ice and how it nearly doubles the apparent area of the continent during the winter.From Antarctica, the animation travels over South America showing glacier locations on this mostly tropical continent. We then move further north to observe daily changes in snow cover over the North American continent. The clouds show winter storms moving across the United States and Canada, leaving trails of snow cover behind. In a close-up view of the western US, we compare the difference in land cover between two years: 2003 when the region received a normal amount of snow and 2002 when little snow was accumulated. The difference in the surrounding vegetation due to the lack of spring melt water from the mountain snow pack is evident.As the animation moves from the western US to the Arctic region, the areas affected by permafrost are visible. As time marches forward from March to September, the daily snow and sea ice recede and reveal the vast areas of permafrost surrounding the Arctic Ocean.The animation shows a one-year cycle of Arctic sea ice followed by the mean September minimum sea ice for each year from 1979 through 2008. The superimposed graph of the area of Arctic sea ice at this minimum clearly shows the dramatic decrease in Artic sea ice over the last few years.While moving from the Arctic to Greenland, the animation shows the constant motion of the Arctic polar ice using daily measures of sea ice activity. Sea ice flows from the Arctic into Baffin Bay as the seasonal ice expands southward. As we draw close to the Greenland coast, the animation shows the recent changes in the Jakobshavn glacier. Although Jakobshavn receded only slightly from 1964 to 2001, the animation shows significant recession from 2001 through 2009. As the animation pulls out from Jakobshavn, the effect of the increased flow rate of Greenland costal glaciers is shown by the thinning ice shelf regions near the Greenland coast.This animation shows a wealth of data collected from satellite observations of the cryosphere and the impact that recent cryospheric changes are making on our planet.For more information on the data sets used in this visualization, visit NASA's EOS DAAC website.Note: This animation is an update of the animation 'A Short Tour of the Cryosphere', which is itself an abridged version of the animation 'A Tour of the Cryosphere'. The popularity of the earlier animations and their continuing relevance prompted us to update the datasets in parts of the animation and to remake it in high definition. In certain cases, our experiences in using the earlier work have led us to tweak the presentation of some of the material to make it clearer. Our thanks to Dr. Robert Bindschadler for suggesting and supporting this remake. || ", "hits": 39 }, { "id": 3601, "url": "https://svs.gsfc.nasa.gov/3601/", "result_type": "Visualization", "release_date": "2009-06-27T12:00:00-04:00", "title": "Global Agricultural Monitoring", "description": "The U.S. Department of Agriculture (USDA) and the National Aeronautics and Space Administration (NASA) signed a Memorandum of Understanding (MOU) to strengthen collaboration. In support of this collaboration, NASA and the USDA Foreign Agricultural Service (FAS) jointly funded a new project to assimilate NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data and products into an existing decision support system (DSS) operated by the International Production Assessment Division (IPAD) of FAS. To meet its objectives, FAS/IPAD uses satellite data and data products to monitor agriculture worldwide and to locate and keep track of natural disasters such as short and long term droughts, floods and persistent snow cover which impair agricultural productivity. FAS is the largest user of satellite imagery in the non-military sector of the U.S. government. For the last 20 years FAS has used a combination of Landsat and NOAA-AVHRR satellite data to monitor crop condition and report on episodic events. || ", "hits": 27 }, { "id": 3598, "url": "https://svs.gsfc.nasa.gov/3598/", "result_type": "Visualization", "release_date": "2009-06-24T12:00:00-04:00", "title": "Monitoring Agricultural Production from Space", "description": "Normalized Difference Vegetation Index (NDVI) maps allow comparisons of the spatial and temporal variability in the amount and condition of vegetation. The time series satellite derived NDVI was used to monitor and analyze changes in vegetation patterns in the major wheat production domain area in Australia. The NDVI comparison was done during the growing season, April through November, for 2002, 2005, and 2006 and it found that significant differences in vegetation growth production. These data and utilities are fundamental for crop yield forecasts and can serve as an early warning system for regions suffering from crop loss and food shortages. Wheat is Australia's most important crop, with a seasonal gross value approaching 3 billion Australian dollars. Australia contributes between and 8 and 15% of world's wheat trade, making it the fourth largest exporter after the United States, Canada and the European Union. Severe drought in Australia not only decimating crops, but it also curtails exports and causes major price and trade impacts on global markets. In 2006, wheat exports dropped by a third from the year before which caused worldwide prices to soar to the highest levels in a decade. || ", "hits": 12 }, { "id": 3584, "url": "https://svs.gsfc.nasa.gov/3584/", "result_type": "Visualization", "release_date": "2009-06-05T00:00:00-04:00", "title": "A Global View of Seasonal NDVI", "description": "Satellite data can be used to monitor the health of plant life from space. The Normalized Difference Vegetation Index (NDVI) provides a simple numerical indicator of the health of vegetation which can be used to monitoring changes in vegetation over time. This animation shows the seasonal changes in vegetation by fading between average monthly NDVI data from 2004. The loop begins on September 24 and repeats six times during one full rotation of the globe at a rate of one frame per day. The fade for each month is complete on the 15th of each month. || ", "hits": 59 }, { "id": 3454, "url": "https://svs.gsfc.nasa.gov/3454/", "result_type": "Visualization", "release_date": "2007-11-05T00:00:00-05:00", "title": "SeaWiFS Biosphere Data over the North Pacific", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. || ", "hits": 18 }, { "id": 3471, "url": "https://svs.gsfc.nasa.gov/3471/", "result_type": "Visualization", "release_date": "2007-10-05T00:00:00-04:00", "title": "SeaWiFS Biosphere Data over the North Pacific (Slow Version)", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land.This animation is essentially the same as animation #3454 with a few minor changes and runs at a slower speed. || ", "hits": 12 }, { "id": 3494, "url": "https://svs.gsfc.nasa.gov/3494/", "result_type": "Visualization", "release_date": "2007-10-05T00:00:00-04:00", "title": "SeaWiFS Biosphere Data over Australia", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. || ", "hits": 11 }, { "id": 3451, "url": "https://svs.gsfc.nasa.gov/3451/", "result_type": "Visualization", "release_date": "2007-04-23T12:00:00-04:00", "title": "Global Rotation of SeaWiFS Biosphere Decadal Average with Land", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation shows an average of 10 years worth of SeaWiFS data. Dark blue represents warmer areas where there tends to be a lack of nutrients, and greens and reds represent cooler nutrient-rich areas which support life. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. || ", "hits": 16 }, { "id": 3383, "url": "https://svs.gsfc.nasa.gov/3383/", "result_type": "Visualization", "release_date": "2007-03-17T12:00:00-04:00", "title": "Sequence of Clouds, Snow Cover, Sea Ice, Sea Surface Temperature and Biosphere", "description": "This animation is part of an NSF-funded, international project, Exploring Time. The two-hour television special, broadcast on the Discovery Channel in the spring of 2007, explores how the world changes over different timescales ... from billionths of seconds to billions of years. This animation portrays a variety of remotely sensed data elements at different temporal resolutions.Initially, the animation shows cloud cover in motion over North America in half-hour increments from Nov. 26 to Dec. 7, 2005. The temporal pace quickens to show a 5-day moving average of daily MODIS snow cover along with daily AMSR-E sea ice from Dec. 7, 2005 to Mar. 15, 2006. As the view swings south over the Gulf of Mexico, the AMSR-E Sea Surface Temperature reveals warming ocean temperatures from March through August, 2006. As it passes over the Atlantic Ocean, the biosphere fades into view, showing both chlorophyll concentration in the ocean along with Normalized Difference Vegetation Index over the land areas. The biosphere animates over time while the view pans over northern Africa and Europe, showing data collected from September 2002 through February 2006.This program was also broadcast in Japan through a partnership with the NHK international broadcasting service and in France through a partnership with the ARTE television network. || ", "hits": 17 }, { "id": 3450, "url": "https://svs.gsfc.nasa.gov/3450/", "result_type": "Visualization", "release_date": "2006-12-05T00:00:00-05:00", "title": "SeaWiFS Biosphere Data over the North Atlantic", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. || ", "hits": 22 }, { "id": 3468, "url": "https://svs.gsfc.nasa.gov/3468/", "result_type": "Visualization", "release_date": "2006-12-05T00:00:00-05:00", "title": "SeaWiFS Biosphere Data over the North Atlantic (Slow Version)", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land.This animation is essentially the same as animation #3450 with a few minor changes and runs at half the speed. || ", "hits": 9 }, { "id": 3599, "url": "https://svs.gsfc.nasa.gov/3599/", "result_type": "Visualization", "release_date": "2006-12-05T00:00:00-05:00", "title": "Phytoplankton Blooms through the Eyes of SeaWiFS Data", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. Dark gray indicate areas where no data was collected. || ", "hits": 28 }, { "id": 3331, "url": "https://svs.gsfc.nasa.gov/3331/", "result_type": "Visualization", "release_date": "2006-02-15T00:00:00-05:00", "title": "Creating the Tamarisk Habitat Suitability Map (for Science Presentations)", "description": "The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being addressed by NASA's Science Mission Directorate through a national application partnership with the US Geological Survey. NASA and USGS are working together to develop a National Invasive Species Forecasting System (ISFS) for the management and control of invasive species on Department of Interior and adjacent lands. The system provides a framework for using USGS's early detection and monitoring protocols and predictive models to process MODIS, ETM+, ASTER, and commercial remote sensing data, and create on-demand, regional-scale assessments of invasive species patterns and vulnerable habitats.The first step in this process is to collect relevant satellite data which can then be used to derive a Tamarisk Habitat Suitability Map. By combining daily Normalized Differential Vegetation Index (NDVI), daily Enhanced Vegetation Index (EVI), and MODIS Land Cover Classification data the likely Tamarisk habitat suitability map can be derived. || ", "hits": 4 }, { "id": 3332, "url": "https://svs.gsfc.nasa.gov/3332/", "result_type": "Visualization", "release_date": "2006-02-15T00:00:00-05:00", "title": "Deriving the Tamarisk Suitability Map: The Complete Story", "description": "The spread of invasive species is one of the most daunting environmental, economic, and human-health problems facing the United States and the World today. It is one of several grand challenge environmental problems being addressed by NASA's Science Mission Directorate through a national application partnership with the US Geological Survey. NASA and USGS are working together to develop a National Invasive Species Forecasting System (ISFS) for the management and control of invasive species on Department of Interior and adjacent lands. The system provides a framework for using USGS's early detection and monitoring protocols and predictive models to process MODIS, ETM+, ASTER and commercial remote sensing data. It can also be used to create on-demand, regional-scale assessments of invasive species patterns and vulnerable habitats. Tamarisk (Salt Ceder) is an invasive plant that typically grows near water and crowds out native species. Tamarisk reflective properties differ from those of its neighboring vegetation throughout the annual life cycle. These different reflective properties can be seen by the naked eye (as in the accompanying seasonal photographs), and can also be seen by satellite sensors. Current Tamarisk infestations and suitable habitats for future growth can be derived from various data sets, including EVI, NDVI, and land cover classifications. || ", "hits": 5 }, { "id": 3309, "url": "https://svs.gsfc.nasa.gov/3309/", "result_type": "Visualization", "release_date": "2005-12-31T00:00:00-05:00", "title": "Missing Carbon: Global Biosphere with Carbon Dioxide Growth Overlaid", "description": "This animation shows the global biosphere in the background and corresponding carbon dioxide graph in the foreground. The biosphere is represented as phytoplankton concentrations over the ocean and vegetation index over land. The carbon dioxide concentrations are from Mauna Loa, Hawaii measurements. As each year progresses, notice how the greening of the land moves south to north, then north to south. Also, notice how this corresponds to the carbon dioxide graph. As the northern hemisphere greens up, the carbon dioxide decreases due to the fact that the plants are absorbing more carbon dioxide. As the northern hemisphere gets less green, the carbon dioxide increases. These are annual oscillations in the carbon dioxide graph; however, the overall carbon dioxide trend from 1980 to 2005 is upward. || ", "hits": 40 }, { "id": 3116, "url": "https://svs.gsfc.nasa.gov/3116/", "result_type": "Visualization", "release_date": "2005-03-02T12:00:00-05:00", "title": "Mount St. Helens Before, During, and After (WMS)", "description": "Mount St. Helens erupted on May 18, 1980, devastating more than 150 square miles of forest in southwestern Washington state. This animation shows Landsat images of the Mount St. Helens area in 1973, 1983, and 2000, illustrating the destruction and regrowth of the forest. The 1983 image clearly shows the new crater on the northern slope where the eruption occurred, the rivers and lakes covered with ash, and the regions of deforestation. The 2000 image, taken twenty years after the eruption, still shows the changed crater, but much of the devastated area is covered by new vegetation growth. || ", "hits": 135 } ] }