{ "count": 113, "next": "https://svs.gsfc.nasa.gov/api/search/?keywords=Vegetation&limit=100&offset=100", "previous": null, "results": [ { "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": 121 }, { "id": 14898, "url": "https://svs.gsfc.nasa.gov/14898/", "result_type": "Produced Video", "release_date": "2025-09-15T15:00:00-04:00", "title": "Our Home In Space Series", "description": "The heliosphere, the massive bubble created by our Sun, is like our “house” in space. It shelters us from harsh weather outside and regulates the environment inside. Without our heliosphere, Earth may never have developed life at all. But there’s a lot we still don’t know about our cosmic home. How big is it, and what is it shaped like? How does it compare to the “houses” created by other stars? A new NASA mission will soon unlock answers to these questions and more. Launching as early as Sept. 23, NASA’s Interstellar Mapping and Acceleration Probe will help us construct the “blueprints” or our home in space. This three-part series explores how we learn about our heliosphere, how it protects us, and how it advances the search for life elsewhere in the Universe. || ", "hits": 174 }, { "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": 134 }, { "id": 14850, "url": "https://svs.gsfc.nasa.gov/14850/", "result_type": "Produced Video", "release_date": "2025-06-05T00:00:00-04:00", "title": "Leaf Year: Seeing Plants in Hyperspectral Color", "description": "Music: \"Natural Perfection,\" \"Drops of Ins piration,\" \"Andriod,\" \"Tiny Moving Parts,\" Universal Production Music.1:06 - 1:53; 2:59 - 3:10; 3:31 - 3:47, footage provided by Pond5.comComplete transcript available. || PACE_Land_Thumb_v1.png (1280x720) [1.1 MB] || PACE_Land_Thumb_v1_print.jpg (1024x576) [266.1 KB] || PACE_Land_Thumb_v1_searchweb.png (320x180) [115.1 KB] || PACE_Land_Thumb_v1_thm.png (80x40) [8.0 KB] || PACE_Leaf_Year_Final_ProRes.webm (1920x1080) [32.4 MB] || PACE_Leaf_Year_Final_YT.mp4 (1920x1080) [308.4 MB] || PACE_Veg_Final.en_US.srt [7.0 KB] || PACE_Veg_Final.en_US.vtt [6.6 KB] || PACE_Leaf_Year_Final_ProRes.mov (1920x1080) [4.0 GB] || ", "hits": 50 }, { "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": 85 }, { "id": 14804, "url": "https://svs.gsfc.nasa.gov/14804/", "result_type": "Produced Video", "release_date": "2025-03-27T14:00:00-04:00", "title": "Global Biomass - GEDI and ICESat-2", "description": "Global visualization of forest biomass using GEDI and ICESat-2 data. || biomass_gedi_icesat2_global_4k_colorbar.00001_print.jpg (1024x576) [82.0 KB] || biomass_gedi_icesat2_global_4k_colorbar.00001_searchweb.png (320x180) [28.6 KB] || biomass_gedi_icesat2_global_4k_colorbar.00001_web.png (320x180) [28.6 KB] || biomass_gedi_icesat2_global_4k_colorbar.00001_thm.png [3.0 KB] || biomass_gedi_icesat2_global_4k_colorbar.webm (3840x2160) [18.0 MB] || biomass_gedi_icesat2_global_4k_colorbar.mp4 (3840x2160) [748.8 MB] || ", "hits": 145 }, { "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": 108 }, { "id": 31239, "url": "https://svs.gsfc.nasa.gov/31239/", "result_type": "Hyperwall Visual", "release_date": "2023-08-29T00:00:00-04:00", "title": "MODIS and VIIRS images of Northeastern US", "description": "Smoke from fires in Alberta/Northern Canada is blown down over the Midwest and Northeastern United States. Terra MODIS 20230801 1600. || terra_modis_true_color_20230801_1600_print.jpg (1024x576) [229.4 KB] || terra_modis_true_color_20230801_1600.png (3840x2160) [11.6 MB] || terra_modis_true_color_20230801_1600_searchweb.png (320x180) [111.8 KB] || terra_modis_true_color_20230801_1600_thm.png (80x40) [7.5 KB] || terra_modis_true_color_20230801_1600.hwshow [121 bytes] || ", "hits": 18 }, { "id": 5031, "url": "https://svs.gsfc.nasa.gov/5031/", "result_type": "Visualization", "release_date": "2023-03-01T11:00:00-05:00", "title": "Continental scale carbon stocks of individual trees in African drylands", "description": "Using commercial, high-resolution satellite images and artificial intelligence, a team of NASA-funded scientists mapped almost 10 billion individual trees in Africa’s drylands in order to assess the amount of carbon stored outside of major forests. The result is the first comprehensive estimate of carbon density in the Saharan, Sahel, and Sudanian zones of Africa. Complete transcript available. || Untitled-1.jpg (2096x1415) [1.8 MB] || Approved_final_exportmp4.webm (1920x1080) [39.1 MB] || Approved_final_exportmp4.mp4 (1920x1080) [719.1 MB] || tree_counting.en_US.srt [5.3 KB] || tree_counting.en_US.vtt [5.3 KB] || ", "hits": 80 }, { "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": 439 }, { "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": 151 }, { "id": 4826, "url": "https://svs.gsfc.nasa.gov/4826/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Brazil and Novo Progresso Land Use Data Over Time", "description": "This animation begins by showing the similar sizes between the country of Brazil and the United States. It then cycles through over three decades of classification data for the entire Northern half of Brazil. We then zoom down to the town of Novo Progresso and compare its relative size to the San Francisco Bay region. Next we cycle through over three decades of transformation in the region showing how the north/south corridor of this region changed over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || novo_progressov_finalcomp.2009_print.jpg (1024x576) [287.1 KB] || novo_progressov_finalcomp.2009_searchweb.png (180x320) [105.7 KB] || novo_progressov_finalcomp.2009_thm.png (80x40) [7.3 KB] || novo_progressov_finalcomp_1080p30.mp4 (1920x1080) [48.9 MB] || example_composite (1920x1080) [0 Item(s)] || novo_progressov_finalcomp_1080p30.webm (1920x1080) [7.9 MB] || novo_progressov_finalcomp_1080p30.mp4.hwshow [199 bytes] || ", "hits": 96 }, { "id": 4827, "url": "https://svs.gsfc.nasa.gov/4827/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Novo Progresso Surrounding Region Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Novo Progresso and compare its relative size to the San Francisco Bay region. Next we cycle through over three decades of transformation in the region showing how the north/south corridor of this area opened up over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || novo_wide_finalcomp.2009_print.jpg (1024x576) [387.4 KB] || novo_wide_finalcomp.1116_print.jpg (1024x576) [221.0 KB] || novo_wide_finalcomp_1080p30_2.mp4 (1920x1080) [30.2 MB] || novo_wide_finalcomp_1080p30_2.webm (1920x1080) [3.7 MB] || Example_Composite (1920x1080) [0 Item(s)] || novo_wide_finalcomp_1080p30_2.mp4.hwshow [195 bytes] || ", "hits": 102 }, { "id": 4828, "url": "https://svs.gsfc.nasa.gov/4828/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Colider Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Colider and compares its relative size to Northern California. Next we cycle through over three decades of land use transformation showing cropland a pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || colider_finalcomp.2009_print.jpg (1024x576) [548.1 KB] || colider_finalcomp.2009_searchweb.png (320x180) [144.4 KB] || colider_finalcomp.2009_thm.png (80x40) [8.4 KB] || colider_finalcomp_1080p30.mp4 (1920x1080) [40.2 MB] || colider_finalcomp_1080p30.webm (1920x1080) [4.0 MB] || Example_Composite (1920x1080) [0 Item(s)] || colider_finalcomp_1080p30.mp4.hwshow [191 bytes] || ", "hits": 40 }, { "id": 4829, "url": "https://svs.gsfc.nasa.gov/4829/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Ji-Paraná Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Ji Parana and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation showing cropland a pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || ji_parana_finalcomp.2009_print.jpg (1024x576) [412.8 KB] || ji_parana_finalcomp.2009_searchweb.png (320x180) [133.8 KB] || ji_parana_finalcomp.2009_thm.png (80x40) [8.2 KB] || ji_parana_finalcomp_1080p30.mp4 (1920x1080) [34.0 MB] || Example_Composite (1920x1080) [0 Item(s)] || ji_parana_finalcomp_1080p30.webm (1920x1080) [3.8 MB] || ji_parana_finalcomp_1080p30.mp4.hwshow [193 bytes] || ", "hits": 104 }, { "id": 4830, "url": "https://svs.gsfc.nasa.gov/4830/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Rio Branco Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Rio Branco and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation showing pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || rio_branco_finalcomp.2009_print.jpg (1024x576) [331.8 KB] || rio_branco_finalcomp.2009_searchweb.png (320x180) [108.8 KB] || rio_branco_finalcomp.2009_thm.png (80x40) [7.4 KB] || rio_branco_finalcomp_1080p30.mp4 (1920x1080) [24.0 MB] || rio_branco_finalcomp_1080p30.webm (1920x1080) [3.4 MB] || Example_Composite (1920x1080) [0 Item(s)] || rio_branco_finalcomp_1080p30.mp4.hwshow [194 bytes] || ", "hits": 132 }, { "id": 4831, "url": "https://svs.gsfc.nasa.gov/4831/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Uatumã Biological Reserve Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the Uatumã Biological Reserve and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation to show the lake formation over time as well as the increased pasture and croplands to the west of the lake. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || dam_finalcomp.2009_print.jpg (1024x576) [216.7 KB] || dam_finalcomp.2009_searchweb.png (320x180) [80.9 KB] || dam_finalcomp.2009_thm.png (80x40) [5.9 KB] || dam_finalcomp_1080p30.mp4 (1920x1080) [22.1 MB] || Example_Composite (1920x1080) [0 Item(s)] || dam_finalcomp_1080p30.webm (1920x1080) [3.3 MB] || dam_finalcomp_1080p30.mp4.hwshow [187 bytes] || ", "hits": 28 }, { "id": 4832, "url": "https://svs.gsfc.nasa.gov/4832/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Itaituba and Uruara Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region between Itaituba and Uruara and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation showing pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || ruropolis_finalcomp.2009_print.jpg (1024x576) [345.6 KB] || ruropolis_finalcomp.2009_searchweb.png (320x180) [116.9 KB] || ruropolis_finalcomp.2009_thm.png (80x40) [7.6 KB] || ruropolis_finalcomp_1080p30.mp4 (1920x1080) [29.5 MB] || Sample_Composite (1920x1080) [0 Item(s)] || ruropolis_finalcomp_1080p30.webm (1920x1080) [3.5 MB] || ruropolis_finalcomp_1080p30.mp4.hwshow [193 bytes] || ", "hits": 35 }, { "id": 4833, "url": "https://svs.gsfc.nasa.gov/4833/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Northern Brazil Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. While zooming in a little closer an image of the United States fades in to get the relative size of the region. Next we cycle through over three decades of transformation in the region showing land use change over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || brazil_wide_finalcomp.2009_print.jpg (1024x576) [451.8 KB] || brazil_wide_finalcomp.2009_searchweb.png (320x180) [128.6 KB] || brazil_wide_finalcomp.2009_thm.png (80x40) [8.1 KB] || brazil_wide_finalcomp_1080p30.mp4 (1920x1080) [31.3 MB] || Sample_Composite (1920x1080) [0 Item(s)] || brazil_wide_finalcomp_1080p30.webm (1920x1080) [3.8 MB] || brazil_wide_finalcomp_1080p30.mp4.hwshow [195 bytes] || ", "hits": 82 }, { "id": 4900, "url": "https://svs.gsfc.nasa.gov/4900/", "result_type": "Visualization", "release_date": "2021-04-19T00:00:00-04:00", "title": "Novo Progresso Deforestation Soccer Field Comparison", "description": "Animation begins with a stylized bright green soccer field. Soccer fields then fall into place over a recently deforested field showing the estimated size of the newly cleared field. The camera then pulls back to reveal all the recently deforested areas (shown in bright green) around Novo Progresso from 2017 to 2018. || soccer_comp.0700_print.jpg (1024x576) [161.5 KB] || soccer_comp.0700_searchweb.png (320x180) [85.8 KB] || soccer_comp.0700_thm.png (80x40) [14.1 KB] || soccer_2017_2018_1080p30.mp4 (1920x1080) [28.6 MB] || 2017_to_2018 (1920x1080) [0 Item(s)] || soccer_2017_2018_1080p30.webm (1920x1080) [5.7 MB] || soccer_2017_2018_1080p30.mp4.hwshow [190 bytes] || ", "hits": 119 }, { "id": 4865, "url": "https://svs.gsfc.nasa.gov/4865/", "result_type": "Visualization", "release_date": "2020-10-16T09:00:00-04:00", "title": "An unexpectedly large count of trees in the West African Sahara and Sahel", "description": "Visualization showing study region, climate zones, close up of high res satellite data with machine learning-based tree crown regions, counting of trees, and overall tree counts and areaThis video is also available on our YouTube channel. || tree_counting_030_1080p59.94.02760_print.jpg (1024x576) [202.7 KB] || tree_counting_030_1080p59.94.02760_searchweb.png (320x180) [111.6 KB] || tree_counting_030_1080p59.94.02760_thm.png (80x40) [7.4 KB] || tree_counting_030_1080p59.94.mp4 (1920x1080) [37.1 MB] || tree_counting_030_1080p59.94.webm (1920x1080) [11.1 MB] || english (3840x2160) [0 Item(s)] || captions_silent.30076.en_US.srt [43 bytes] || tree_counting_030_2160p59.94.mp4 (3840x2160) [116.2 MB] || ", "hits": 137 }, { "id": 13723, "url": "https://svs.gsfc.nasa.gov/13723/", "result_type": "Produced Video", "release_date": "2020-09-22T11:00:00-04:00", "title": "Arctic Greening Driven by Warmer Temperatures", "description": "Data from NASA/USGS Landsat satellites show that during 1985-2016, vegetation in the arctic tundra showed a 38% increase in greenness – representing plants growing more, becoming denser, and/or shrubs encroaching on typical tundra grasses and moss.Complete transcript available.Music: The Rework, by Josslin Bordat [SACEM], published by Koka Media [SACEM], available from Universal Production Music || 13723_ArcticGreening-468.jpg (1421x800) [140.8 KB] || 13723_ArcticGreening-468_searchweb.png (320x180) [87.7 KB] || 13723_ArcticGreening-468_thm.png (80x40) [11.2 KB] || 13723_ArcticGreening-v2.mp4 (1920x1080) [110.1 MB] || 13723_ArcticGreening-v2-twitter.mp4 (1920x1080) [34.0 MB] || 13723_ArcticGreening-v2.webm (1920x1080) [12.0 MB] || 13723_ArcticGreening-v2.en_US.srt [2.0 KB] || 13723_ArcticGreening-v2.en_US.vtt [2.0 KB] || ", "hits": 71 }, { "id": 4800, "url": "https://svs.gsfc.nasa.gov/4800/", "result_type": "Visualization", "release_date": "2020-03-19T14:00:00-04:00", "title": "JPSS Green Vegetation Fraction (GVF)", "description": "The visualization depicts Green Vegetation Fraction (GVF) based on data collected by the VIIRS instrument aboard the NOAA-20 satellite. || gvf_18.0550_print.jpg (1024x576) [90.7 KB] || gvf_18.0550_searchweb.png (320x180) [56.2 KB] || gvf_18.0550_thm.png (80x40) [6.0 KB] || jpss_gvf_02_1080p30.mp4 (1920x1080) [22.7 MB] || jpss_gvf_02_1080p30.webm (1920x1080) [5.3 MB] || jpss_gvf_02_2160p30.mp4 (3840x2160) [72.9 MB] || JPSS_Greening_02 (3840x2160) [0 Item(s)] || jpss_gvf_02_1080p30.mp4.hwshow [185 bytes] || ", "hits": 198 }, { "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": 44 }, { "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": 49 }, { "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": 41 }, { "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": 250 }, { "id": 13090, "url": "https://svs.gsfc.nasa.gov/13090/", "result_type": "Produced Video", "release_date": "2018-10-09T08:00:00-04:00", "title": "GEDI Media Resources", "description": "The Global Ecosystem Dynamics Investigation (GEDI) uses laser pulses to give a view of the 3D structure of the Earth. GEDI’s precise measurements of the height and vertical structure of forest canopy, along with the surface elevation, will greatly advance our ability to characterize important carbon and water cycling processes, biodiversity, and habitat. The mission is led by the University of Maryland, College Park, and the instrument was built and tested at NASA's Goddard Space Flight Center.GEDI observes nearly all tropical and temperate forests using a self-contained laser altimeter on the International Space Station. GEDI has the highest resolution and densest sampling of any lidar ever put in orbit. This has required a number of innovative technologies to be developed at NASA Goddard.GEDI has three lasers that produce 8 parallel tracks of observations. Each laser fires 242 times per second and illuminates a 25-meter footprint on the surface over which 3D structure is measured. Each footprint is separated by 60 meters along the track, with an across-track distance of about 600 m between each of the 8 tracks. GEDI is expected to produce about 10 billion cloud-free observations during its nominal 24-month mission length.With these observations, GEDI will provide answers to how deforestation has contributed to atmospheric CO2 concentrations, how much carbon forests will absorb in the future, and how habitat degradation will affect global biodiversity. This data is of immense value for forest and water resource management, carbon cycle science, and weather prediction.For more information about GEDI: https://gedi.umd.edu || ", "hits": 268 }, { "id": 13056, "url": "https://svs.gsfc.nasa.gov/13056/", "result_type": "Produced Video", "release_date": "2018-09-27T11:00:00-04:00", "title": "EPIC New Science from 1 Million Miles Away", "description": "NASA's Earth Polychromatic Imaging Camera (EPIC) sits onboard NOAA's Deep Space Climate Observatory (DSCOVR) satellite at the Lagrange point 1, a million miles away from Earth. EPIC has been imaging the sunlit side of Earth between 13 and 22 times a day since 2015. Now, scientists have developed ways to use these images to study specific elements of our home planet's atmosphere and plant life, like ozone in the stratosphere, the makeup of clouds and the health of vegetation on land. || ", "hits": 78 }, { "id": 13053, "url": "https://svs.gsfc.nasa.gov/13053/", "result_type": "Produced Video", "release_date": "2018-09-12T12:00:00-04:00", "title": "GLOBE Adopt a Pixel", "description": "Music Provided by Killer Tracks\"Feet on the Ground\" by Elliot Nash [PRS] and Jackson Buckley [PRS].Stock Video provided by Pond5 and Artbeats. || Screen_Shot_2018-09-11_at_4.42.53_PM_print.jpg (1024x574) [126.6 KB] || Screen_Shot_2018-09-11_at_4.42.53_PM.png (3824x2144) [8.5 MB] || Screen_Shot_2018-09-11_at_4.42.53_PM_searchweb.png (320x180) [94.1 KB] || Screen_Shot_2018-09-11_at_4.42.53_PM_thm.png (80x40) [7.4 KB] || GLOBE_Final.mov (1920x1080) [760.0 MB] || GLOBE_Final.mp4 (1920x1080) [59.7 MB] || GLOBE_Final.webm (1920x1080) [6.2 MB] || GLOBE_Final.en_US.srt [1003 bytes] || GLOBE_Final.en_US.vtt [1015 bytes] || ", "hits": 20 }, { "id": 30979, "url": "https://svs.gsfc.nasa.gov/30979/", "result_type": "Hyperwall Visual", "release_date": "2018-07-31T00:00:00-04:00", "title": "ECOSTRESS Installation and First Data", "description": "The first light image from ECOSTRESS, showing the Nile river valley. || ecostress_first_light_PIA22590.png (1920x1080) [1.3 MB] || ecostress_first_light_PIA22590_print.jpg (1024x576) [99.0 KB] || ecostress_first_light_PIA22590_searchweb.png (320x180) [55.4 KB] || ecostress_first_light_PIA22590_thm.png (80x40) [4.5 KB] || ecostress_first_light_PIA22590.hwshow [228 bytes] || ", "hits": 165 }, { "id": 4530, "url": "https://svs.gsfc.nasa.gov/4530/", "result_type": "Visualization", "release_date": "2018-06-12T11:00:00-04:00", "title": "50 Kilometers of Brazilian Forest Canopy", "description": "This visualization shows an airplane collecting a 50 kilometer swath of lidar data over the Brazilian rainforest. For ground level features, colors range from deep brown to tan. Vegetation heights are depicted in shades of green, where dark greens are closest to the ground and light greens are the highest. || transect2014.17900_print.jpg (1024x576) [106.2 KB] || transect2014.17900_searchweb.png (320x180) [44.6 KB] || transect2014.17900_thm.png (80x40) [4.1 KB] || transect2014_720p30.webm (1280x720) [71.4 MB] || transect2014_720p30.mp4 (1280x720) [132.4 MB] || transect2014_1080p30.mp4 (1920x1080) [311.2 MB] || transect2014_360p30.mp4 (640x360) [30.3 MB] || transect2014 (3840x2160) [0 Item(s)] || transect2014_2160p30_3.mp4 (3840x2160) [1.2 GB] || transect2014_1080p30.mp4.hwshow [212 bytes] || ", "hits": 96 }, { "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": 81 }, { "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": 33 }, { "id": 30899, "url": "https://svs.gsfc.nasa.gov/30899/", "result_type": "Hyperwall Visual", "release_date": "2017-09-20T00:00:00-04:00", "title": "Hurricane Irma Turns Caribbean Islands Brown", "description": "The U.S. Virgin Islands before and after Hurricane Irma || virgin_islands_print.jpg (1024x653) [141.3 KB] || virgin_islands.png (3608x2304) [23.8 MB] || virgin_islands_searchweb.png (320x180) [85.6 KB] || virgin_islands_thm.png (80x40) [5.8 KB] || hurricane-irma-turns-caribbean-islands-brown-virgin-islands.hwshow [241 bytes] || ", "hits": 32 }, { "id": 30786, "url": "https://svs.gsfc.nasa.gov/30786/", "result_type": "Hyperwall Visual", "release_date": "2016-06-18T00:00:00-04:00", "title": "MODIS Ocean Bioproductivity", "description": "This visualization, derived using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, shows a daily running weighted 31 day average of sea surface chlorophyll from January 2010 through May 2016. The MODIS data have also been smoothed with a spatial filter to fill in areas of missing data caused by clouds.The second image below shows a typical day's worth of data from one MODIS instrument. In addition to gaps caused by the instrument's scan width, there are many areas where clouds obstruct its view of the ocean. To make a movie of ocean color that plays more smoothly, the missing values are filled in with averages from pixels nearby in space or time. For this visualization, data from up to +-15 days and up to 2 degrees away spatially were used to fill in missing values. Pixels closer in time or space are given more weight in the average to prevent the result from appearing too smoothed. Even with this relatively large amount of data filling, there are still areas with missing data - for example over the Arabian Sea during the summer monsoon.The source data for this visualization are the daily MODIS Chlorophyll concentration files available at oceancolor.gsfc.nasa.gov. || ", "hits": 109 }, { "id": 30709, "url": "https://svs.gsfc.nasa.gov/30709/", "result_type": "Hyperwall Visual", "release_date": "2015-11-06T00:00:00-05:00", "title": "Yearly Cycle of Earth's Biosphere", "description": "animation with traditional colors for chl || yearly_biosphere_color2_1080p.00001_print.jpg (1024x576) [164.5 KB] || yearly_biosphere_color2_1080p.00001_searchweb.png (180x320) [86.0 KB] || yearly_biosphere_color2_1080p.00001_thm.png (80x40) [6.9 KB] || yearly_biosphere_color2_1080p.mp4 (1920x1080) [17.2 MB] || yearly_biosphere_color2_1080p.webm (1920x1080) [1.3 MB] || yearly_biosphere_color2_1080p.hwshow [94 bytes] || ", "hits": 250 }, { "id": 30555, "url": "https://svs.gsfc.nasa.gov/30555/", "result_type": "Hyperwall Visual", "release_date": "2014-12-05T11:00:00-05:00", "title": "Projected Suitable Habitats for Whitebark Pine", "description": "Projected changes in suitable habitats for whitebark pine from 2010-2099. || proj_suitable_habitats_whitebark_pine_print.jpg (1024x576) [127.0 KB] || proj_suitable_habitats_whitebark_pine_searchweb.png (320x180) [91.3 KB] || proj_suitable_habitats_whitebark_pine_web.png (320x180) [91.3 KB] || proj_suitable_habitats_whitebark_pine_thm.png (80x40) [6.2 KB] || proj_suitable_habitats_whitebark_pine.webm (1280x720) [8.1 MB] || 4104x2304_16x9_30p (4104x2304) [256.0 KB] || proj_suitable_habitats_whitebark_pine.mp4 (1280x720) [201.0 MB] || Projected_Hab_Whitebark_pine_4096x2304.mp4 (4104x2304) [284.3 MB] || proj_suitable_habitats_whitebark_pine.pptx [202.2 MB] || proj_suitable_habitats_whitebark_pine.key [205.0 MB] || projected-suitable-habitats-for-whitebark-pine.hwshow [243 bytes] || ", "hits": 15 }, { "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": 36 }, { "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": 98 }, { "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": 67 }, { "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": 31 }, { "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": 91 }, { "id": 30380, "url": "https://svs.gsfc.nasa.gov/30380/", "result_type": "Hyperwall Visual", "release_date": "2013-10-24T12:00:00-04:00", "title": "Monthly Net Primary Productivity", "description": "Plants play an important role in the movements of carbon dioxide throughout Earth's environment. Living plants both take in carbon dioxide from the air and put out carbon dioxide to the air. Called net primary productivity, these maps show where and how much carbon dioxide is taken in by vegetation during photosynthesis minus how much carbon dioxide is released when plants respire on a monthly basis, from February 2000 to the present. Created using data from the Moderate Resolutions Imaging Spectroradiometer (MODIS) instrument onboard NASA’s Terra satellite, the colors on these maps indicate how fast carbon was taken in for every square meter of land. Values range from -1.0 grams of carbon per square meter per day (tan) to 6.5 grams per square meter per day (dark green). A negative value means decomposition or respiration overpowered carbon absorption; more carbon was released to the atmosphere than the plants took in. Maps such as these allow scientists to routinely monitor plants' role in the global carbon cycle. || ", "hits": 306 }, { "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": 123 }, { "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": 214 }, { "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": 237 }, { "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": 128 }, { "id": 10630, "url": "https://svs.gsfc.nasa.gov/10630/", "result_type": "Produced Video", "release_date": "2010-08-19T14:00:00-04:00", "title": "Plant Productivity in a Warming World", "description": "The past decade is the warmest on record since instrumental measurements began in the 1880s. Previous research suggested that in the '80s and '90s, warmer global temperatures and higher levels of precipitation — factors associated with climate change — were generally good for plant productivity. An updated analysis published this week in Science indicates that as temperatures have continued to rise, the benefits to plants are now overwhelmed by longer and more frequent droughts. High-resolution data from the Moderate Resolution Imaging Spectroradiometer, or MODIS, indicate a net decrease in NPP from 2000-2009, as compared to the previous two decades. || ", "hits": 28 }, { "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": 166 }, { "id": 3709, "url": "https://svs.gsfc.nasa.gov/3709/", "result_type": "Visualization", "release_date": "2010-05-01T00:00:00-04:00", "title": "Five Spheres - Biosphere", "description": "Satellite data can be used to monitor the health of the biosphere from space. This animation of seasonal changes to the biosphere is match framed to animation entries 3707, 3708, 3710, and 3711. The SeaWiFS instrument is carried aboard the satellite OrbView-2, providing important information about the oceans, the land, and the life within them. 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. For most of the world's oceans, the most important things that influence its color are phytoplankton. Phytoplankton are very small, single-celled plants, generally smaller than the size of a pinhead that contain a green pigment called chlorophyll. All plants (on land and in the ocean) use chlorophyll to capture energy from the sun and through the process known as photosynthesis convert water and carbon dioxide into new plant material and oxygen. Although microscopic, phytoplankton can bloom in such large numbers that they can change the color of the ocean to such a degree that we can measure that change from space. The basic principle behind the remote sensing of ocean color from space is this: the more phytoplankton in the water, the greener it is...the less phytoplankton, the bluer it is. For more information, visit http://oceancolor.gsfc.nasa.gov/SeaWiFS/. || ", "hits": 85 }, { "id": 3710, "url": "https://svs.gsfc.nasa.gov/3710/", "result_type": "Visualization", "release_date": "2010-05-01T00:00:00-04:00", "title": "Five Spheres - Cryosphere", "description": "Sea ice is frozen seawater floating on the surface of the ocean. Some sea ice is semi-permanent, persisting from year to year, and some is seasonal, melting and refreezing from season to season. The sea ice cover reaches its minimum extent at the end of each summer and the remaining ice is called the perennial ice cover. The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA Earth Observing System (EOS) Aqua satellite, provides data mapped to a polar stereographic grid at 12.5 km spatial resolution. This satellite data can be used to monitor the health of the cryosphere from space. This animation of sea ice changes in the Arctic is match framed to animation entries 3707, 3708, 3709, and 3711. Over the water, Arctic sea ice changes from day to day showing a running 3-day maximum sea ice concentration in the region where the concentration is greater than 15%. The blueish white color of the sea ice is derived from a 3-day running maximum of the AMSR-E 89 GHz brightness temperature. Over the terrain, monthly data from the seasonal Blue Marble Next Generation fades slowly from month to month.For more information about sea ice see http://nsidc.org/data/amsre or http://modis-snow-ice.gsfc.nasa.gov. || ", "hits": 30 }, { "id": 3697, "url": "https://svs.gsfc.nasa.gov/3697/", "result_type": "Visualization", "release_date": "2010-04-21T14:15:00-04:00", "title": "SDO/HMI Magnetogram Full Disk View - March 29, 2010", "description": "This early sequence of images from the HMI imager is processed to reveal the magnetic field structure (magnetogram). White locations represent a positive magnetic field value (north polarity) while black represents a negative magnetic field value (south polarity). Grey is zero magnetic field.The black and white region slightly above the center corresponds to a visible sunspot. Weaker magnetic regions are visible around the disk. || ", "hits": 46 }, { "id": 3687, "url": "https://svs.gsfc.nasa.gov/3687/", "result_type": "Visualization", "release_date": "2010-03-24T00:00:00-04:00", "title": "Greenland Ice Sheet Mass Changes from NASA GSFC GRACE Mascon Solutions with Banded Color Scale", "description": "Luthcke, S.B., D.D. Rowlands, J.J. McCarthy, A. Arendt, T. Sabaka, J.P. Boy, F.G. Lemoine, \"Recent Changes of the Earth's Land Ice from GRACE, \" presented at 2009 Fall AGU, H13G-02 (693337), Dec. 14, 2009.The mass changes of the Greenland Ice Sheet (GIS) are computed from the Gravity Recovery and Climate Experiment (GRACE) inter-satellite range-rate observations for the period April 5, 2003 - July 25, 2009. The mass of the GIS has been computed at 10-day intervals and 200km spatial resolution from a regional high-resolution mascon solution (Luthcke and others, 2008 and 2006). The animation shows the change in mass referenced from April 5, 2003. The spatial variation in surface mass is shown in centimeters equivalent height of water. The time variation of the GIS mass is shown in the x-y plot insert with units of Gigatons.Corresponding author:Scott B. LuthckeNASA GSFCPlanetary Geodynamics Laboratory, Code 698Scott.B.Luthcke@nasa.gov || ", "hits": 18 }, { "id": 3676, "url": "https://svs.gsfc.nasa.gov/3676/", "result_type": "Visualization", "release_date": "2010-01-05T00:00:00-05:00", "title": "28 Year Arctic Winter Seasonal Temperature Trend", "description": "The Arctic region has been an area of scientific interest because it is expected that global warming signals will be amplified in the region because of ice-albedo feedback effect. Such effect is associated with the high albedo of snow and sea ice covered areas compared to that of ice free ocean and land areas. This animation depicts the 28-year winter seasonal surface temperature trend over the Arctic region determined from data collected during the months of December, January and February between 1981 and 2009. In this animation, the warming and cooling regions are revealed in steps of .02 degrees change per year starting with the regions of greatest change and progressing to the areas of least change. Blue hues indicate cooling regions while red hues depict warming. The neutral region of -.01 to +.01 degrees is shown in white. Brighter regions indicate greater temperature change while light regions indicate less. On the left side, the colarbar shows cooling temperatures ranging from -0.42 to zero degrees Kelvin, while the colorbar on the right shows warming temperatures ranging from zero to +0.42 degrees Kelvin per year. A moving bar beside each colorbar indicates the range of data values being displayed. || ", "hits": 131 }, { "id": 3677, "url": "https://svs.gsfc.nasa.gov/3677/", "result_type": "Visualization", "release_date": "2010-01-05T00:00:00-05:00", "title": "28 Year Arctic Spring Seasonal Temperature Trend", "description": "The Arctic region has been an area of scientific interest because it is expected that global warming signals will be amplified in the region because of ice-albedo feedback effect. Such effect is associated with the high albedo of snow and sea ice covered areas compared to that of ice free ocean and land areas. This animation depicts the 28-year spring seasonal surface temperature trend over the Arctic region determined from data collected during the months of March, April and May between 1982 and 2009.In this animation, the warming and cooling regions are revealed in steps of .02 degrees change per year starting with the regions of greatest change and progressing to the areas of least change. Blue hues indicate cooling regions while red hues depict warming. The neutral region of -.01 to +.01 degrees is shown in white. Brighter regions indicate greater temperature change while light regions indicate less. On the left side, the colarbar shows cooling temperatures ranging from -0.42 to zero degrees Kelvin, while the colorbar on the right shows warming temperatures ranging from zero to +0.42 degrees per year. An animated bar beside each colorbar brackets the range of data values being displayed. || ", "hits": 32 }, { "id": 3678, "url": "https://svs.gsfc.nasa.gov/3678/", "result_type": "Visualization", "release_date": "2010-01-05T00:00:00-05:00", "title": "28 Year Arctic Summer Seasonal Temperature Trend", "description": "The Arctic region has been an area of scientific interest because it is expected that global warming signals will be amplified in the region because of ice-albedo feedback effect. Such effect is associated with the high albedo of snow and sea ice covered areas compared to that of ice free ocean and land areas. This animation depicts the 28-year summer seasonal surface temperature trend over the Arctic region determined from data collected during the months of June, July and August between 1982 and 2009.In this animation, the warming and cooling regions are revealed in steps of .02 degrees change per year starting with the regions of greatest change and progressing to the areas of least change. Blue hues indicate cooling regions while red hues depict warming. The neutral region of -.01 to +.01 degrees is shown in white. Brighter regions indicate greater temperature change while light regions indicate less. On the left side, the colarbar shows cooling temperatures ranging from -0.42 to zero degrees Kelvin, while the colorbar on the right shows warming temperatures ranging from zero to +0.42 degrees per year. An animated bar beside each colorbar brackets the range of data values being displayed. || ", "hits": 77 }, { "id": 3679, "url": "https://svs.gsfc.nasa.gov/3679/", "result_type": "Visualization", "release_date": "2010-01-05T00:00:00-05:00", "title": "28 Year Arctic Autumn Seasonal Temperature Trend", "description": "The Arctic region has been an area of scientific interest because it is expected that global warming signals will be amplified in the region because of ice-albedo feedback effect. Such effect is associated with the high albedo of snow and sea ice covered areas compared to that of ice free ocean and land areas. This animation depicts the 28-year autumn seasonal surface temperature trend over the Arctic region determined from data collected during the months of September, October and November between 1981 and 2008.In this animation, the warming and cooling regions are revealed in steps of .02 degrees change per year starting with the regions of greatest change and progressing to the areas of least change. Blue hues indicate cooling regions while red hues depict warming. The neutral region of -.01 to +.01 degrees is shown in white. Brighter regions indicate greater temperature change while light regions indicate less. On the left side, the colarbar shows cooling temperatures ranging from -0.42 to zero degrees Kelvin, while the colorbar on the right shows warming temperatures ranging from zero to +0.42 degrees per year. An animated bar beside each colorbar brackets the range of data values being displayed. || ", "hits": 37 }, { "id": 3673, "url": "https://svs.gsfc.nasa.gov/3673/", "result_type": "Visualization", "release_date": "2009-12-11T00:00:00-05:00", "title": "Poster of Greenland Ice Sheet Mass Changes from NASA GSFC GRACE Mascon Solutions", "description": "Luthcke, S.B., D.D. Rowlands, J.J. McCarthy, A. Arendt, T. Sabaka, J.P. Boy, F.G. Lemoine, \"Recent Changes of the Earth's Land Ice from GRACE, \" presented at 2009 Fall AGU, H13G-02 (693337), Dec. 14, 2009.The mass changes of the Greenland Ice Sheet (GIS) are computed from the Gravity Recovery and Climate Experiment (GRACE) inter-satellite range-rate observations for the period April 5, 2003 - July 25, 2009. The mass of the GIS has been computed at 10-day intervals and 200 km spatial resolution from a regional high-resolution mascon solution (Luthcke and others, 2008 and 2006). The poster shows the change in mass during February, April, July and October from 2003 through 2009 as referenced from April 5, 2003. The spatial variation in surface mass is shown in centimeters equivalent height of water. The chart shown in the upper left corner presents total ice loss in Greenland over the same time period measured in gigatons. Corresponding author:Scott B. LuthckeNASA GSFCPlanetary Geodynamics Laboratory, Code 698Scott.B.Luthcke@nasa.gov || ", "hits": 32 }, { "id": 3625, "url": "https://svs.gsfc.nasa.gov/3625/", "result_type": "Visualization", "release_date": "2009-08-26T00:00:00-04:00", "title": "Honey Bees Weigh In on Climate", "description": "This animation illustrates the relationship between the annual vegetation cycle and seasonal variations in the weights of honey bee hives. The weight of a hive increases in the spring as bees bring back nectar from flowering plants. The change in hive weight over time can be compared with satellite measurements of vegetation. Tracking a large number of hives this way can reveal the effects of changing climate and land use on the interaction of plants and pollinators. Data from this hive in Highland, Maryland and others suggests that for some locations in the U.S., spring is arriving earlier by as much as half a day per year, probably due to a combination of climate and the warming effect of urbanization.This animation has been incorporated into the video \"Feeling the Sting of Climate Change,\" which provides more background and introduces HoneyBeeNet, a central repository for hive weight data from across the U.S. || ", "hits": 85 }, { "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": 78 }, { "id": 10394, "url": "https://svs.gsfc.nasa.gov/10394/", "result_type": "Produced Video", "release_date": "2009-02-19T00:00:00-05:00", "title": "Scanning Electron Microscope Still Image of Pollen Particles", "description": "Aerosols are complex particles that come from a variety of sources. They occur in nature, but can also be generated by human activity. Pollen grains are an example of short-lived aerosols that are difficult to detect but are found near the Earth's surface. Pollen effect human health, but researchers do not consider these aerosols to be part of the climatologically important population of tropospheric aerosols. This Scanning Electron Microscopic image reveals pollen grains from a variety of common plants: sunflower (Helianthus annuus), morning glory (Ipomoea purpurea ), prairie hollyhock (Sidalcea malviflora), oriental lily (Lilium auratum ), evening primrose (Oenothera fruticosa), and castor bean (Ricinus communis). || ", "hits": 291 }, { "id": 10264, "url": "https://svs.gsfc.nasa.gov/10264/", "result_type": "Produced Video", "release_date": "2008-10-14T00:00:00-04:00", "title": "Earth Science Week 2008", "description": "Keep your eyes glued to the Goddard Web site through the week of October 12 for daily videos that answer several questions about our home planet. The videos are all part of Earth Science Week: 2008, themed 'No Child Left Inside.' || ", "hits": 13 }, { "id": 3523, "url": "https://svs.gsfc.nasa.gov/3523/", "result_type": "Visualization", "release_date": "2008-01-07T00:00:00-05:00", "title": "Seasonal Landcover for Science On a Sphere", "description": "The Blue Marble Next Generation (BMNG) data set provides a monthly global cloud-free true-color picture of the Earth's land cover at a 500-meter spatial resolution. This series of images fades from month to month showing seasonal variations such as snowfall, spring greening and droughts in a seamless fashion. The data set,derived from monthly data collected in 2004, is shown on a flat cartesian grid. The ocean color is derived from applying a depth shading to the bathymetry data. Where available, the Antarctica coverage shown is the Landsat Image Mosaic of Antarctica (LIMA). || ", "hits": 43 }, { "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": 23 }, { "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": 16 }, { "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": 12 }, { "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": 18 }, { "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": 43 }, { "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": 29 }, { "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": 14 }, { "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": 36 }, { "id": 2925, "url": "https://svs.gsfc.nasa.gov/2925/", "result_type": "Visualization", "release_date": "2006-06-13T12:00:00-04:00", "title": "Daily Snow over North America 2002-2003 with Permafrost Map", "description": "This animation shows daily snow cover over North America from September 1, 2002 through June 30, 2003. A permafrost map shown in frost-green indicates where the ground is frozen throughout the year. The sea ice climatology indicates the average extent of the sea ice during each month. || ", "hits": 33 }, { "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": 10 }, { "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": 9 }, { "id": 3110, "url": "https://svs.gsfc.nasa.gov/3110/", "result_type": "Visualization", "release_date": "2005-02-16T12:00:00-05:00", "title": "Vegetation Images Show Drought in Western US (WMS)", "description": "Satellite data can gauge the health of plants, which is a good indicator of drought. The Normalized Difference Vegetation Index (NDVI) measures how dense and green plant leaves are. NDVI images are useful as a measure of drought when compared to 'normal' plant health. Scientists calculate average NDVI values for an area to find out what is normal at a particular time of year. This animation uses satellite imagery to show changes in vegetation between 1999 and 2003. In 2002, drought had settled across the Midwest. Large dark brown sections of eastern Colorado show where vegetation was less lush and healthy than normal. This version of the visualization is a wide view showing the western United States. The data were measured by the vegetation instrument on Europe's SPOT-4 satellite, and were provided by DigitalGlobe/SPOT under agreement with the U.S. Department of Agriculture Foreign Agricultural Service (USDA/FAS). || ", "hits": 18 }, { "id": 3027, "url": "https://svs.gsfc.nasa.gov/3027/", "result_type": "Visualization", "release_date": "2005-01-12T12:00:00-05:00", "title": "Snow Cover over North America during the Winter of 2001-2002 (WMS)", "description": "The amount of snow covering the land has both short and long term effects on the environment. From season to season, snow coverage and depth affect soil moisture and water availability, which directly influence agriculture, wildfire occurrences, and drought. In the long term, the part of the Earth's surface covered by snow reflects up to 80 or 90 percent of the incoming solar radiation as opposed to the 10 or 20 percent that uncovered land reflects, and this has important consequences for the Earth's climate. Satellites identify the snow cover precisely by looking at the difference between light reflected off snow in the visible and the infrared wavelengths. This visualization shows the snow cover over North America from October, 2001, through April, 2002, as measured by the MODIS instrument on the Terra satellite. Since this instrument cannot measure snow cover through clouds, this visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than 50% snow coverage in that area. This area is assumed to be covered in snow until the instrument takes a valid measurement showing less than 40% coverage in that same area. In this animation, snow coverage is measured every 8 days. || ", "hits": 16 }, { "id": 2932, "url": "https://svs.gsfc.nasa.gov/2932/", "result_type": "Visualization", "release_date": "2004-12-31T12:00:00-05:00", "title": "Daily Snow over North America 2002-2003 without Permafrost Map", "description": "This animation shows daily snow cover over North America from September 1, 2002 through June 30, 2003. The sea ice climatology indicates the average extent of the sea ice during each month. || ", "hits": 17 }, { "id": 2981, "url": "https://svs.gsfc.nasa.gov/2981/", "result_type": "Visualization", "release_date": "2004-09-25T12:00:00-04:00", "title": "Global Daily Snow and Sea Ice Surface Temperature", "description": "This animation shows the global advance and retreat of daily snow cover along with daily sea ice surface temperature over the Northern Hemisphere from September 2002 through May 2003. The snow cover was measured by the MODIS instrument on the Terra satellite, while the sea ice surface temperature was measured by the MODIS instrument on the Aqua satellite. Since these instruments cannot take measurements through clouds, in cloud-covered regions or areas with suspect data quality, the prior day's value is retained until a valid data reading is obtained. This visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than ~50% snow coverage in that area. This area is assumed to be snow covered until the instrument takes a valid measurement showing less than 40% snow coverage in that same area. A color bar indicates the sea ice surface temperature values. The satellite instruments are unable to collect data through darkness. The region in polar darkness is shown as a gray cap over the pole that grows and shrinks seasonally. A date slider indicates the progression of time. SeaWiFS Land Reflectance shows the seasonal changes in land cover. || ", "hits": 31 }, { "id": 2982, "url": "https://svs.gsfc.nasa.gov/2982/", "result_type": "Visualization", "release_date": "2004-09-25T12:00:00-04:00", "title": "Daily Snow and Sea Ice Temperature over the North Pole", "description": "This animation shows the global advance and retreat of daily snow cover along with daily sea ice surface temperature over the Northern Hemisphere from September 2002 through May 2003. The snow cover was measured by the MODIS instrument on the Terra satellite, while the sea ice surface temperature was measured by the MODIS instrument on the Aqua satellite. Since these instruments cannot take measurements through clouds, in cloud-covered regions or areas with suspect data quality, the prior day's value is retained until a valid data reading is obtained. This visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than ~50% snow coverage in that area. This area is assumed to be snow covered until the instrument takes a valid measurement showing less than 40% snow coverage in that same area. A color bar indicates the sea ice surface temperature values. The satellite instruments are unable to collect data through darkness. The region in polar darkness is shown as a gray cap over the pole that grows and shrinks seasonally. A date slider indicates the progression of time. SeaWiFS Land Reflectance shows the seasonal changes in land cover. || ", "hits": 71 }, { "id": 2983, "url": "https://svs.gsfc.nasa.gov/2983/", "result_type": "Visualization", "release_date": "2004-09-25T12:00:00-04:00", "title": "Daily Snow and Sea Ice Temperature over North America", "description": "This animation shows the global advance and retreat of daily snow cover along with daily sea ice surface temperature over North America from September 2002 through May 2003. The snow cover was measured by the MODIS instrument on the Terra satellite, while the sea ice surface temperature was measured by the MODIS instrument on the Aqua satellite. Since these instruments cannot take measurements through clouds, in cloud-covered regions or areas with suspect data quality, the prior day's value is retained until a valid data reading is obtained. This visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than ~50% snow coverage in that area. This area is assumed to be snow covered until the instrument takes a valid measurement showing less than 40% snow coverage in that same area. A color bar indicates the sea ice surface temperature values. The satellite instruments are unable to collect data through darkness. The region in polar darkness is shown as a gray cap over the pole that grows and shrinks seasonally. A date slider indicates the progression of time. SeaWiFS Land Reflectance shows the seasonal changes in land cover. || ", "hits": 38 }, { "id": 2984, "url": "https://svs.gsfc.nasa.gov/2984/", "result_type": "Visualization", "release_date": "2004-09-25T12:00:00-04:00", "title": "Daily Snow and Sea Ice Temperature over Europe", "description": "This animation shows the global advance and retreat of daily snow cover along with daily sea ice surface temperature over Europe from September 2002 through May 2003. The snow cover was measured by the MODIS instrument on the Terra satellite, while the sea ice surface temperature was measured by the MODIS instrument on the Aqua satellite. Since these instruments cannot take measurements through clouds, in cloud-covered regions or areas with suspect data quality, the prior day's value is retained until a valid data reading is obtained. This visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than ~50% snow coverage in that area. This area is assumed to be snow covered until the instrument takes a valid measurement showing less than 40% snow coverage in that same area. A color bar indicates the sea ice surface temperature values. The satellite instruments are unable to collect data through darkness. The region in polar darkness is shown as a gray cap over the pole that grows and shrinks seasonally. A date slider indicates the progression of time. SeaWiFS Land Reflectance shows the seasonal changes in land cover. || ", "hits": 39 }, { "id": 2985, "url": "https://svs.gsfc.nasa.gov/2985/", "result_type": "Visualization", "release_date": "2004-09-25T12:00:00-04:00", "title": "Daily Snow and Sea Ice Temperature over Asia", "description": "This animation shows the global advance and retreat of daily snow cover along with daily sea ice surface temperature over Asia from September 2002 through May 2003. The snow cover was measured by the MODIS instrument on the Terra satellite, while the sea ice surface temperature was measured by the MODIS instrument on the Aqua satellite. Since these instruments cannot take measurements through clouds, in cloud-covered regions or areas with suspect data quality, the prior day's value is retained until a valid data reading is obtained. This visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than ~50% snow coverage in that area. This area is assumed to be snow covered until the instrument takes a valid measurement showing less than 40% snow coverage in that same area. A color bar indicates the sea ice surface temperature values. The satellite instruments are unable to collect data through darkness. The region in polar darkness is shown as a gray cap over the pole that grows and shrinks seasonally. A date slider indicates the progression of time. SeaWiFS Land Reflectance shows the seasonal changes in land cover. || ", "hits": 39 }, { "id": 2903, "url": "https://svs.gsfc.nasa.gov/2903/", "result_type": "Visualization", "release_date": "2004-02-12T12:00:00-05:00", "title": "Ozone Measurements from 2000 through 2003 (WMS)", "description": "This visualization shows the total ozone concentrations for the Earth from January 1, 2000 through December 31, 2003, as measured by theTOMS instrument on the Earth Probe satellite. Low ozone (less than 200 Dobson units) is depicted as regions of dark blue, with high ozone (greater that 330 Dobson units) depicted as yellow and red. The most visible and dynamic feature of the ozone distribution is the ozone hole that forms over Antarctica during September of each year. The amount of ozone in the stratosphere over Antarctica is reduced during this period due to unique atmospheric conditions which chemically reduce the amount of ozone in the region and prevent that ozone from mixing with the higher ozone concentrations just outside the hole. Ozone blocks harmful ultraviolet 'B' rays, and loss of statospheric ozone has been linked to skin cancer in humans and other adverse biological effects in plants and animals. This visualization explicitly shows the TOM ozone data coverage and does not interpolate data into regions of the Earth that the instrument did not observe. Since TOMS measures ozone by observing the characteristics of sunlight reflected from the Earth's surface, no measurements are available for the poles during the polar winter, i.e., around January for the North Pole and July for the South Pole. Also, there is an unobserved region between successive satellite orbits around the equator. Finally, the instrument has periods where technical issues make measurement impossible for a matter of hours or days. This visualization shows that the dynamics of the ozone layer remain visible despite these measurement issues. || ", "hits": 38 }, { "id": 2904, "url": "https://svs.gsfc.nasa.gov/2904/", "result_type": "Visualization", "release_date": "2004-02-12T12:00:00-05:00", "title": "Global Ozone from 2000 through 2003 (WMS)", "description": "This visualization shows the total ozone concentrations for the Earth from January 1, 2000 through December 31, 2003. Low ozone (less than 200 Dobson units) is depicted as regions of dark blue, with high ozone (greater than 330 Dobson units) depicted as yellow and red. The most visible and dynamic feature of the ozone distribution is the ozone hole that forms over Antarctica during September of each year. The amount of ozone in the stratosphere over Antarctica is reduced during this period due to unique atmospheric conditions which chemically reduce the amount of ozone in the region and prevent that ozone from mixing with the higher ozone concentrations just outside the hole. Ozone blocks harmful ultraviolet 'B' rays, and loss of statospheric ozone has been linked to skin cancer in humans and other adverse biological effects in plants and animals. The 2000 Antarctic ozone hole reached 11.5 million square miles on September 10, 2000, the largest hole ever recorded, slightly larger than the North American continent. The 2002 ozone hole was much smaller than normal, dividing into two parts on September 24 before dissipating completely, while the 2003 hole was the second largest observed, reaching 10.9 million square miles on September 11. This data was measured by the TOMS instrument on the Earth Probe satellite. TOMS experienced some days during this period for which data was not measured due to instrument problems. || ", "hits": 103 }, { "id": 2899, "url": "https://svs.gsfc.nasa.gov/2899/", "result_type": "Visualization", "release_date": "2004-02-11T12:00:00-05:00", "title": "Snow Cover over the Northern Hemisphere During the Winter of 2002-2003 (WMS)", "description": "The amount of snow covering the land has both short and long term effects on the environment. From season to season, snow coverage and depth affect soil moisture and water availability, which directly influence agriculture, wildfire occurrences, and drought. In the long term, the part of the Earth's surface covered by snow reflects up to 80 or 90 percent of the incoming solar radiation as opposed to the 10 or 20 percent that uncovered land reflects, and this has important consequences for the Earth's climate. Satellites identify the snow cover precisely by looking at the difference between light reflected off snow in the visible and the infrared wavelengths. This visualization shows the snow cover in the Northern Hemisphere from September, 2002, through June, 2003, as measured by the MODIS instrument on the Terra satellite. Since this instrument cannot measure snow cover through clouds, this visualization designates an area as covered by snow when the instrument takes a valid measurement showing greater than 50% snow coverage in that area. This area is assumed to be snow covered until the instrument takes a valid measurement showing less than 40% snow coverage in that same area. It is possible to see topographic features in the snow cover such as the Rocky Mountains and the Himalayas, and large snow coverage paths from storms that cross the plains of the United States and Russia can also be seen. || ", "hits": 19 }, { "id": 2625, "url": "https://svs.gsfc.nasa.gov/2625/", "result_type": "Visualization", "release_date": "2002-10-15T12:00:00-04:00", "title": "Global Sea Surface Temperature with Land Vegetation", "description": "Visualization of global surface temperature. || Sea surface temperature with land vegetation || SeaSurTemp_Veg_0594.jpg (4096x2048) [2.0 MB] || SeaSurTemp_Veg_0594_web.jpg (320x160) [17.4 KB] || SeaSurTemp_Veg_0594_thm.png (80x40) [5.7 KB] || SeaSurTemp_Veg_0594_web_searchweb.jpg (320x180) [20.9 KB] || SeaSurTemp_Veg_0594.tif (4096x2048) [6.6 MB] || ", "hits": 49 }, { "id": 2317, "url": "https://svs.gsfc.nasa.gov/2317/", "result_type": "Visualization", "release_date": "2001-12-20T12:00:00-05:00", "title": "Global EVI from Spring to Winter", "description": "Traditional satellite-based mapping of vegetation vigor and amount is based on the way vegetation interacts with red and infrared light. Occasionally, however, those two signals are not enough. MODIS measures light reflected from Earth at a variety of wavelengths, and the Arizona researchers incorporate the additional information into their Enhanced Vegetation Index (EVI). The EVI has increased sensitivity within very dense vegetation, and it has built-in corrections for several factors that can interfere with the satellite-based vegetation mapping, like smoke and background noise caused by light reflecting off soil. The bi-weekly and monthly vegetation index maps have wide usability by biologists, natural resources managers, and climate modelers. They can track naturally occurring fluctuations in vegetation, such as seasonal changes, as well as those that result from land use change, such as deforestation. The EVI can also monitor changes in vegetation resulting from climate change, such as expansion of deserts or extension of growing seasons. || ", "hits": 47 }, { "id": 1180, "url": "https://svs.gsfc.nasa.gov/1180/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Seasonal NDVI for North America: 1981-2000 Averaged, With Month Notation", "description": "Seasonal NDVI for North America. 1981-2000 averaged with month notation. 15 frames/month || Seasonal NDVI movie for North America. || a001180.00005_print.png (720x480) [493.7 KB] || a001180_pre.jpg (320x242) [10.4 KB] || a001180_thm.png (80x40) [5.4 KB] || a001180_pre_searchweb.jpg (320x180) [63.8 KB] || a001180.webmhd.webm (960x540) [1.4 MB] || a001180.dv (720x480) [41.0 MB] || a001180.mp4 (640x480) [2.0 MB] || a001180.mpg (352x240) [1.4 MB] || ", "hits": 9 }, { "id": 1181, "url": "https://svs.gsfc.nasa.gov/1181/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Seasonal NDVI for North America: 1981-2000 Averaged, Without Month Notation", "description": "Seasonal NDVI for North America. 1981-2000 averaged without month notation. 15 frames/month || Movie of seasonal NDVI for North America || a001181.00005_print.png (720x480) [489.1 KB] || a001181_pre.jpg (320x242) [10.2 KB] || a001181_thm.png (80x40) [5.4 KB] || a001181_pre_searchweb.jpg (320x180) [63.8 KB] || a001181.webmhd.webm (960x540) [1.3 MB] || a001181.dv (720x480) [41.0 MB] || a001181.mp4 (640x480) [2.0 MB] || a001181.mpg (352x240) [1.4 MB] || ", "hits": 11 }, { "id": 1182, "url": "https://svs.gsfc.nasa.gov/1182/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Monthly NDVI for North America: July 1981-July 2000", "description": "Monthly NDVI for North America. July 1981-July 2000. 5 frames/month || Monthly NDVI for North America || a001182.00005_print.png (720x480) [529.0 KB] || a001182_pre.jpg (320x242) [10.5 KB] || a001182_thm.png (80x40) [5.4 KB] || a001182_pre_searchweb.jpg (320x180) [68.4 KB] || a001182.webmhd.webm (960x540) [11.6 MB] || a001182.dv (720x480) [151.4 MB] || a001182.mp4 (640x480) [7.8 MB] || a001182.mpg (352x240) [5.9 MB] || ", "hits": 6 }, { "id": 1183, "url": "https://svs.gsfc.nasa.gov/1183/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Monthly NDVI Anomaly for North America: July 1981-July 2000", "description": "Monthly NDVI Anomaly for North America. July 1981-July 2000. 5 frames/month || Montly NDVI anomaly at 5 frames-month || a001183.00005_print.png (720x480) [559.0 KB] || a001183_pre.jpg (320x242) [12.9 KB] || a001183.webmhd.webm (960x540) [12.1 MB] || a001183.dv (720x480) [151.4 MB] || a001183.mp4 (640x480) [7.5 MB] || a001183.mpg (352x240) [5.8 MB] || ", "hits": 11 }, { "id": 1184, "url": "https://svs.gsfc.nasa.gov/1184/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Seasonal NDVI for Africa: 1981-2000 Averaged, With Month Notation", "description": "Seasonal NDVI for Africa. 1981-2000 averaged with month notation. 15 frames/month || Seasonal NDVI for Africa. || a001184.00005_print.png (720x480) [400.4 KB] || a001184_pre.jpg (320x242) [6.6 KB] || a001184_thm.png (80x40) [4.2 KB] || a001184_pre_searchweb.jpg (320x180) [40.5 KB] || a001184.webmhd.webm (960x540) [676.3 KB] || a001184.dv (720x480) [41.0 MB] || a001184.mp4 (640x480) [2.1 MB] || a001184.mpg (352x240) [1.4 MB] || ", "hits": 12 }, { "id": 1185, "url": "https://svs.gsfc.nasa.gov/1185/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Seasonal NDVI for Africa: 1981-2000 Averaged Without Month Notation", "description": "Seasonal NDVI for Africa. 1981-2000 averaged without month notation. 15 frames/month || Seasonally averaged NDVI for Africa || a001185.00005_print.png (720x480) [401.6 KB] || a001185_pre.jpg (320x242) [6.5 KB] || a001185_thm.png (80x40) [4.3 KB] || a001185_pre_searchweb.jpg (320x180) [40.5 KB] || a001185.webmhd.webm (960x540) [653.1 KB] || a001185.dv (720x480) [41.0 MB] || a001185.mp4 (640x480) [2.1 MB] || a001185.mpg (352x240) [1.4 MB] || ", "hits": 11 }, { "id": 1186, "url": "https://svs.gsfc.nasa.gov/1186/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Monthly NDVI for Africa: July 1981-July 2000", "description": "Monthly NDVI for Africa. July 1981-July 2000. 5 frames/month || Monthly NDVI for Africa over 20 years. || a001186.00005_print.png (720x480) [411.0 KB] || a001186_pre.jpg (320x242) [6.7 KB] || a001186_thm.png (80x40) [4.4 KB] || a001186_pre_searchweb.jpg (320x180) [43.0 KB] || a001186.webmhd.webm (960x540) [6.2 MB] || a001186.dv (720x480) [153.0 MB] || a001186.mp4 (640x480) [7.9 MB] || a001186.mpg (352x240) [5.9 MB] || ", "hits": 10 }, { "id": 1187, "url": "https://svs.gsfc.nasa.gov/1187/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Monthly NDVI Anomaly for Africa: July 1981-July 2000", "description": "Monthly NDVI Anomaly for Africa. July 1981-July 2000. 5 frames/month || Montly averaged NDVI anomalies in Africa for 20 years. || a001187.00005_print.png (720x480) [411.9 KB] || a001187_pre.jpg (320x242) [6.8 KB] || a001187_thm.png (80x40) [4.4 KB] || a001187_pre_searchweb.jpg (320x180) [45.3 KB] || a001187.webmhd.webm (960x540) [7.3 MB] || a001187.dv (720x480) [151.4 MB] || a001187.mp4 (640x480) [7.6 MB] || a001187.mpg (352x240) [5.8 MB] || ", "hits": 19 }, { "id": 1188, "url": "https://svs.gsfc.nasa.gov/1188/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "North America NDVI Average August", "description": "Average NDVI in North America for August, based off data collected over the 1981-2000 time frame. || North America NDVI Average August || na_season0008.jpg (2560x1920) [494.1 KB] || na_season0008_web.jpg (320x240) [10.7 KB] || na_season0008_thm.png (80x40) [4.6 KB] || na_season0008_web_searchweb.jpg (320x180) [66.3 KB] || na_season0008.tif (2560x1920) [3.4 MB] || ", "hits": 9 }, { "id": 1189, "url": "https://svs.gsfc.nasa.gov/1189/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "North America NDVI 1988 August", "description": "NDVI in North America for August 1988, based off data collected over the 1981-2000 time frame. || North America NDVI 1988 August || na_ndvi0086.jpg (2560x1920) [600.3 KB] || na_ndvi0086_web.jpg (320x240) [11.5 KB] || na_ndvi0086_thm.png (80x40) [4.7 KB] || na_ndvi0086_web_searchweb.jpg (320x180) [70.0 KB] || na_ndvi0086.tif (2560x1920) [4.0 MB] || For More Information || See [http://svs.gsfc.nasa.gov/stories/drought/index.html](http://svs.gsfc.nasa.gov/stories/drought/index.html) || ", "hits": 13 }, { "id": 1190, "url": "https://svs.gsfc.nasa.gov/1190/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "North America NDVI 1988 August Anomaly", "description": "NDVI Anomaly in North America for August 1988, based off data collected over the 1981-2000 time frame. || North America NDVI 1988 August Anomaly || na_anomaly0086.jpg (2560x1920) [745.9 KB] || na_anomaly0086_web.jpg (320x240) [12.4 KB] || na_anomaly0086_thm.png (80x40) [4.7 KB] || na_anomaly0086_web_searchweb.jpg (320x180) [76.4 KB] || na_anomaly0086.tif (2560x1920) [5.0 MB] || ", "hits": 12 }, { "id": 1192, "url": "https://svs.gsfc.nasa.gov/1192/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "North America NDVI 1993 August", "description": "NDVI in North America for August 1993, based off data collected over the 1981-2000 time frame. || North America NDVI 1993 August || na_ndvi0146.jpg (2560x1920) [587.0 KB] || na_ndvi0146_web.jpg (320x240) [11.1 KB] || na_ndvi0146_thm.png (80x40) [4.6 KB] || na_ndvi0146_web_searchweb.jpg (320x180) [72.3 KB] || na_ndvi0146.tif (2560x1920) [3.9 MB] || For More Information || See [http://svs.gsfc.nasa.gov/stories/drought/index.html](http://svs.gsfc.nasa.gov/stories/drought/index.html) || ", "hits": 6 } ] }