{ "count": 17, "next": null, "previous": null, "results": [ { "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": 50 }, { "id": 4783, "url": "https://svs.gsfc.nasa.gov/4783/", "result_type": "Visualization", "release_date": "2020-02-27T00:00:00-05:00", "title": "Precipitation Anomaly and Rift Valley fever (RVF) outbreaks in South Africa: 2008-2011", "description": "This visualization with corresponding data dashboard shows the relationship between precipitation anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal precipitation over land (blue) and RVF outbreak locations (orange pins). || PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg (1024x576) [97.8 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_searchweb.png (320x180) [57.6 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_thm.png (80x40) [5.2 KB] || PrecipRVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [31.5 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || PrecipRVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [68.2 MB] || PrecipRVF_SAfrica_Composite_3840x2160_3422.tif (3840x2160) [4.0 MB] || PrecipRVF_SAfrica_Composite_3840x2160_p30.webm (3840x2160) [14.1 MB] || ", "hits": 53 }, { "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": 43 }, { "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": 37 }, { "id": 4784, "url": "https://svs.gsfc.nasa.gov/4784/", "result_type": "Visualization", "release_date": "2020-02-21T00:00:00-05:00", "title": "ENSO Teleconnections and Rift Valley fever (RVF) Outbreaks", "description": "During the 2008-2011 period, ENSO events brought changes to weather conditions across the globe that triggered infectious disease outbreaks, such as mosquito-borne Rift Valley fever (RVF) in South Africa. This visualization with corresponding data dashboard shows how Sea Surface Temperature (SST) anomalies in the equatorial Pacific Ocean (left) gave rise to Precipitation (center) and Vegetation (right) Index Anomalies in South Africa. During La Niña events, Southern Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus. However, in rare cases there is a departure from this canonical response, as we can observe in 2009-2010, when a mild El Niño event resulted in above normal vegetaton and a large RVF outbreak in South Africa. || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960_print.jpg (1024x576) [107.8 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png (320x180) [63.0 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_thm.png (80x40) [6.5 KB] || ENSO_Teleconnections (1920x1080) [0 Item(s)] || SST_Precip_NDVI_Dashboard_2008_2011_1920x1080_p30.mp4 (1920x1080) [22.7 MB] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.mp4 (3840x2160) [56.0 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.webm (3840x2160) [10.2 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960.tif (3840x2160) [3.4 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525.tif (3840x2160) [3.4 MB] || ", "hits": 53 }, { "id": 4785, "url": "https://svs.gsfc.nasa.gov/4785/", "result_type": "Visualization", "release_date": "2020-01-09T00:00:00-05:00", "title": "Sea Surface Temperature Anomalies and Patterns of Global Disease Outbreaks: 2009-2018 (4K version)", "description": "This webpage provides the 4K version of: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated), released on January 6, 2020.Content has been created for 4K display systems that can handle finer resolution and details. It is recommended to use content from this version for HD (1920x1080) and lower resolutions. || ", "hits": 108 }, { "id": 4781, "url": "https://svs.gsfc.nasa.gov/4781/", "result_type": "Visualization", "release_date": "2020-01-06T00:00:00-05:00", "title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated)", "description": "This visualization shows the variability in global sea surface temperature anomalies, the associated ENSO index timeline and locations of infectious disease outbreaks over the global land surface. || CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg (1024x576) [135.9 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_searchweb.png (320x180) [82.6 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_thm.png (80x40) [7.1 KB] || Composite_StrongElNino (1920x1080) [0 Item(s)] || Composite_StrongElNino (1920x1080) [0 Item(s)] || CompositeWLabel_2009_2018_1920x1080_p30.mp4 (1920x1080) [22.1 MB] || CompositeWLabel_2009_2018_1920x108060fps_1705.tif (1920x1080) [1.3 MB] || CompositeWLabel_2009_2018_1920x1080_p30.webm (1920x1080) [4.6 MB] || CompositeWLabel_2009_2018_1920x1080_p30.mp4.hwshow [205 bytes] || ", "hits": 144 }, { "id": 4765, "url": "https://svs.gsfc.nasa.gov/4765/", "result_type": "Visualization", "release_date": "2019-12-10T00:00:00-05:00", "title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018", "description": "El Niño is an irregularly recurring climate pattern characterized by warmer than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions. This visualization captures monthly Sea Surface Temperature (SST) anomalies around the world from 2009-2018, along with locations of global disease outbreaks and a corresponding timeline showcasing the Niño 3.4 Index. The Niño 3.4 Index represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the above average El Niño years, in which sea surface temperature anomalies peaked during 2015-2016. || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg (1024x576) [130.6 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_searchweb.png (320x180) [79.7 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_thm.png (80x40) [7.0 KB] || Composite (1920x1080) [0 Item(s)] || Composite (1920x1080) [0 Item(s)] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4 (1920x1080) [23.0 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769.tif (1920x1080) [1.3 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.webm (1920x1080) [4.7 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4.hwshow [211 bytes] || ", "hits": 174 }, { "id": 13275, "url": "https://svs.gsfc.nasa.gov/13275/", "result_type": "Produced Video", "release_date": "2019-08-07T11:30:00-04:00", "title": "How NASA Will Protect Astronauts From Space Radiation", "description": "Today, the Apollo-era flares serve as a reminder of the threat of radiation exposure for technology and astronauts in space. Understanding and predicting solar eruptions is crucial for safe space exploration. Almost 50 years since those 1972 storms, the data, technology and resources available to NASA have improved, enabling advancements towards space weather forecasts and astronaut protection — key to NASA’s Artemis program to return astronauts to the Moon.", "hits": 242 }, { "id": 4693, "url": "https://svs.gsfc.nasa.gov/4693/", "result_type": "Visualization", "release_date": "2019-02-28T09:00:00-05:00", "title": "Precipitation Anomaly and Dengue Outbreaks in South East Asia: 2015-2016", "description": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between precipitation anomaly in Southeast Asia and dengue outbreaks. Drier than normal habitats drew mosquitoes into populated, urban areas containing the open water needed for laying eggs. As the air warmed, mosquitoes also grew hungrier and reached sexual maturity more quickly, resulting in an increase in mosquito bites. || SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg (1024x576) [75.8 KB] || SEAsia_PrecipDengueComposite_1920x1080_1211_searchweb.png (320x180) [52.9 KB] || SEAsia_PrecipDengueComposite_1920x1080_1211_thm.png (80x40) [5.4 KB] || SEAsia_PrecipDengueComposite_1920x1080_p30.webm (1920x1080) [6.4 MB] || SEAsia_PrecipDengue_Composite (1920x1080) [0 Item(s)] || SEAsia_PrecipDengueComposite_1920x1080_p30.mp4 (1920x1080) [14.8 MB] || SEAsia_PrecipDengueComposite_1920x1080_1211.tif (1920x1080) [1.5 MB] || SEAsia_PrecipDengueComposite (3840x2160) [0 Item(s)] || ", "hits": 101 }, { "id": 4695, "url": "https://svs.gsfc.nasa.gov/4695/", "result_type": "Visualization", "release_date": "2019-02-28T09:00:00-05:00", "title": "Niño 3.4 Index and Sea Surface Temperature Anomaly Timeline: 1982-2017", "description": "This visualization captures Sea Surface Temperature (SST) anomalies around the world from 1982 to 2017, along with a corresponding timeplot graph focusing on the Niño 3.4 SST Index region (5N-5S, 120W-170W), which represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the El Niño years, in which sea surface temperature anomalies peaked: 1982-1983, 1997-1998, and 2015-2016. || NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg (1024x576) [104.9 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_searchweb.png (320x180) [72.1 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_thm.png (80x40) [6.8 KB] || SST_Nino3.4Index_1982_2017_Composite (1920x1080) [0 Item(s)] || NINO3.4SST_FlatMapComposite_1920x1080_p30.mp4 (1920x1080) [57.2 MB] || NINO3.4SST_FlatMapComposite_1920x1080_00932.tif (1920x1080) [1.4 MB] || NINO3.4SST_FlatMapComposite_1920x1080_p30.webm (1920x1080) [9.3 MB] || SSTNino3.4Index_1982_2017_Composite (3840x2160) [0 Item(s)] || ", "hits": 750 }, { "id": 4696, "url": "https://svs.gsfc.nasa.gov/4696/", "result_type": "Visualization", "release_date": "2019-02-28T09:00:00-05:00", "title": "Land Surface Temperature Anomaly and Dengue Outbreaks in South East Asia Region: 2015-2016", "description": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between land surface temperature anomaly in Southeast Asia and dengue outbreaks. Higher than normal land surface temperatures results in an increase of dengue reported locations. || SEAsia_LSTDiseases_1920x1080_1730_print.jpg (1024x576) [85.1 KB] || SEAsia_LSTDiseases_1920x1080_1730_searchweb.png (320x180) [54.4 KB] || SEAsia_LSTDiseases_1920x1080_1730_thm.png (80x40) [5.3 KB] || SEAsia_LSTDengue_Composite (1920x1080) [0 Item(s)] || SEAsia_LSTDiseases_1920x1080_p30.mp4 (1920x1080) [33.8 MB] || SEAsia_LSTDiseases_1920x1080_1730.tif (1920x1080) [1.7 MB] || SEAsia_LSTDiseases_1920x1080_p30.webm (1920x1080) [6.2 MB] || SEAsia_LSTDengue_Composite (3840x2160) [0 Item(s)] || ", "hits": 34 }, { "id": 4697, "url": "https://svs.gsfc.nasa.gov/4697/", "result_type": "Visualization", "release_date": "2019-02-28T09:00:00-05:00", "title": "ENSO teleconnections in South East Asia for the period of 2015-2016", "description": "The 2015-2016 strong El Niño event brought changes to weather conditions across the globe that triggered regional infectious disease outbreaks, including mosquito-borne dengue fever in South East Asia. This visualization with corresponding multi-plot graph shows how Sea Surface Temperature anomalies in the equatorial Pacific Ocean (left), resulted in anomalous drought conditions (center) and increase in land surface temperatures (right) in South East Asia. During the 2015-2016 El Niño event, the South East Asia region received below than normal precipitation resulting in drier and warner than normal conditions, which increased the populations of mosquito vectors in urban areas, where there are open water storage containers providing ideal habitats for mosquito production. In addition, the higher than normal temperature on land shortens the maturation time of larvae to adult mosquitos and induces frequent blood feeding/biting of humans by mosquito vectors resulting in the amplification of dengue disease outbreaks over the South East Asia region. || SST_LST_Precip_2014_2016_Comp_print.jpg (1024x576) [82.9 KB] || SST_LST_Precip_2014_2016_Comp_searchweb.png (320x180) [51.5 KB] || SST_LST_Precip_2014_2016_Comp_thm.png (80x40) [6.0 KB] || SST_Precip_LST_Plot_Composite (1920x1080) [0 Item(s)] || SST_LST_Precip_2014_2016_Comp_1080p30.mp4 (1920x1080) [9.7 MB] || SST_LST_Precip_2014_2016_Comp.tif (1920x1080) [1.1 MB] || SST_LST_Precip_2014_2016_Comp_1080p30.webm (1920x1080) [4.2 MB] || TeleconnectionsSEAsia (3840x2160) [0 Item(s)] || SST_LST_Precip_2014_2016_Comp_1080p30.mp4.hwshow [203 bytes] || ", "hits": 235 }, { "id": 12958, "url": "https://svs.gsfc.nasa.gov/12958/", "result_type": "Produced Video", "release_date": "2018-05-18T14:00:00-04:00", "title": "Using Precipitation Data to Assess Risk of Cholera Outbreaks", "description": "Music: \"A New Hope,\" Al Lethbridge, Atmosphere Music Ltd PRS; \"Spirals within a Sphere,\" Adam Salkeld, Atmosphere Music Ltd PRSComplete transcript available. || cholera_still_print.jpg (1024x695) [243.6 KB] || cholera_still_searchweb.png (320x180) [119.4 KB] || cholera_still_thm.png (80x40) [7.6 KB] || 12958_Cholera_GPM_prores.mov (1920x1080) [3.1 GB] || 12958_Cholera_GPM_twitter_720.mp4 (1280x720) [54.2 MB] || 12958_Cholera_GPM_youtube_720.mp4 (1280x720) [430.0 MB] || 12958_Cholera_GPM_facebook_720.mp4 (1280x720) [337.4 MB] || 12958_Cholera_GPM_youtube_1080.mp4 (1920x1080) [490.1 MB] || 12958_Cholera_GPM_prores.webm (1920x1080) [23.6 MB] || 12958_Cholera_GPM_large.mp4 (1920x1080) [235.1 MB] || 12958_Cholera.en_US.srt [4.2 KB] || 12958_Cholera.en_US.vtt [4.2 KB] || ", "hits": 41 }, { "id": 12603, "url": "https://svs.gsfc.nasa.gov/12603/", "result_type": "Produced Video", "release_date": "2017-09-13T11:00:00-04:00", "title": "Predicting Malaria Outbreaks With NASA Satellites", "description": "In the Amazon Rainforest, few animals are as dangerous to humans as mosquitos that transmit malaria. The tropical disease can bring on severe fever, headaches and chills and is particularly severe for children and the elderly and can cause complications for pregnant women. In rainforest-covered Peru the number of malaria cases has spiked such that, in the past five years, it has had on average the second highest rate in the South American continent. In 2014 and 2015 there were 65,000 reported cases in the country.Containing malaria outbreaks is challenging because it is difficult to figure out where people are contracting the disease. As a result, resources such as insecticide-treated bed nets and indoor sprays are often deployed to areas where few people are getting infected, allowing the outbreak to grow.To tackle this problem, university researchers have turned to data from NASA’s fleet of Earth-observing satellites, which are able to track the types of human and environmental events that typically precede an outbreak. With funding from NASA’s Applied Sciences Program, they are working in partnership with the Peruvian government to develop a system that uses satellite and other data to help forecast outbreaks at the household level months in advance and prevent outbreaks.Additional imagery from: Christopher B. Plunkett FortJames GathanyFábio Medeiros da Costa || ", "hits": 35 }, { "id": 30824, "url": "https://svs.gsfc.nasa.gov/30824/", "result_type": "Hyperwall Visual", "release_date": "2016-10-27T00:00:00-04:00", "title": "Mosquito Spread and Health", "description": "Seasonal Occurrence and Abundance of Zika Virus Vector Mosquito || gupta_slide_5_1080p.00001_print.jpg (1024x576) [162.3 KB] || gupta_slide_5_1080p.00001_searchweb.png (180x320) [71.3 KB] || gupta_slide_5_1080p.00001_thm.png (80x40) [6.6 KB] || gupta_slide_5_1080p.mp4 (1920x1080) [6.4 MB] || gupta_slide_5_720p.mp4 (1280x720) [3.4 MB] || gupta_slide_5_720p.webm (1280x720) [3.8 MB] || gupta_slide_5_2304p.mp4 (4096x2304) [19.1 MB] || gupta_slide_5_360p.mp4 (640x360) [1.1 MB] || 4104x2304_16x9_30p (4104x2304) [32.0 KB] || ", "hits": 123 }, { "id": 10617, "url": "https://svs.gsfc.nasa.gov/10617/", "result_type": "Produced Video", "release_date": "2010-07-19T00:00:00-04:00", "title": "Three Months of Oil: Satellites View Gulf Oil Spill", "description": "On April 20, 2010, the Deepwater Horizon oil rig exploded in the Gulf of Mexico, triggering the largest oil spill in U.S. history. The MODIS instrument, on board NASA's Terra and Aqua satellites, continues to capture imagery of the region. This short video time series shows a satellite perspective of the spill through July 12, 2010, and updates the earlier NASA video time series released on May 27, 2010. The oil slick appears a dull grayish-beige in the images and changes due in part to to changing weather, ocean currents, and the use of oil dispersing chemicals. The oil slick only appears clearly in MODIS imagery when the sun is a a particular angle in relation to the satellite's position as it orbits over the Gulf. In areas where sunlight reflects off the ocean's surface toward the satellite, oil-slicked water usually looks brighter than cleaner ocean water in the region.Images in the video time series were selected that show the spill most clearly. The full image archive is available on the MODIS Rapid Response web site. || ", "hits": 248 } ] }