{ "count": 13, "next": null, "previous": null, "results": [ { "id": 13689, "url": "https://svs.gsfc.nasa.gov/13689/", "result_type": "Produced Video", "release_date": "2020-08-20T08:00:00-04:00", "title": "GLOBE Observer Getting Started: Mosquito Habitat Mapper - Sample Collection", "description": "Music: “The Slickness” by Brett Engel [BMI]; Killer Tracks; Killer Edge; Universal Production Music“Shaking It Up” by Andrew Lappin [ASCAP]; Soundcast Music; Killer Edge; Universal Production Music || 13689_GO_GettingStarted_MHM_SampleCollection.jpg (1920x1080) [600.8 KB] || 13689_GO_GettingStarted_MHM_SampleCollection_print.jpg (1024x576) [249.5 KB] || 13689_GO_GettingStarted_MHM_SampleCollection_searchweb.png (320x180) [80.5 KB] || 13689_GO_GettingStarted_MHM_SampleCollection_thm.png (80x40) [6.8 KB] || 13689_GO_GettingStarted_MHM_SampleCollection_VX-313852_1080.mp4 (1920x1080) [363.7 MB] || 13689_GO_GettingStarted_MHM_SampleCollection_VX-313852_lowres.mp4 (1280x720) [69.4 MB] || 13689_GO_GettingStarted_MHM_SampleCollection_VX-313852.webm (960x540) [98.2 MB] || 13689_GO_GettingStarted_MHM_SampleCollection_VX-313852_720.mp4 (1280x720) [257.6 MB] || 13689_GO_GettingStarted_MHM_SampleCollection_VX-313852_youtube_720.mp4 (1280x720) [345.2 MB] || 13689_GO_MHM_SampleCollection.en_US.vtt [2.4 KB] || 13689_GO_MHM_SampleCollection.en_US.srt [2.4 KB] || ", "hits": 50 }, { "id": 13308, "url": "https://svs.gsfc.nasa.gov/13308/", "result_type": "Produced Video", "release_date": "2020-01-28T00:00:00-05:00", "title": "GLOBE Observer Mosquito Habitat Mapper: Getting Started Basic", "description": "Underwater Lights by Wally Gagel [ASCAP] & Xandy Barry [ASCAP]; Soundcast Music [SESAC]; Universal Production Music || GLOBE_Observer_MHM_Basic.jpg (1920x1080) [833.5 KB] || GLOBE_Observer_MHM_Basic_searchweb.png (320x180) [93.9 KB] || GLOBE_Observer_MHM_Basic_thm.png (80x40) [7.7 KB] || 13308_MHM_Basic.mov (1920x1080) [3.3 GB] || 13308_MHM_Basic_lowres.mp4 (1280x720) [42.7 MB] || YOUTUBE_1080_13308_MHM_Basic_youtube_1080.mp4 (1920x1080) [199.2 MB] || YOUTUBE_720_13308_MHM_Basic_youtube_720.mp4 (1280x720) [196.9 MB] || FACEBOOK_720_13308_MHM_Basic_facebook_720.mp4 (1280x720) [147.3 MB] || 13308_MHM_Basic.webm (960x540) [58.8 MB] || GO_MHM_Basic_Final.en_US.srt [1.8 KB] || GO_MHM_Basic_Final.en_US.vtt [1.8 KB] || ", "hits": 48 }, { "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": 113 }, { "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": 94 }, { "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": 125 }, { "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": 99 }, { "id": 40348, "url": "https://svs.gsfc.nasa.gov/gallery/esddatafor-societal-benefits/", "result_type": "Gallery", "release_date": "2018-04-24T00:00:00-04:00", "title": "ESD data for Societal Benefit", "description": "No description available.", "hits": 199 }, { "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": 58 }, { "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": 36 }, { "id": 30593, "url": "https://svs.gsfc.nasa.gov/30593/", "result_type": "Hyperwall Visual", "release_date": "2015-04-13T00:00:00-04:00", "title": "Malaria Modeling and Transmission", "description": "Remote sensing data products which are input into malaria model. || malaria_modeling_w_sat_data_print.jpg (1024x574) [158.6 KB] || malaria_modeling_w_sat_data.png (4104x2304) [2.7 MB] || malaria_modeling_w_sat_data_web.jpg (319x179) [21.9 KB] || malaria_modeling_w_sat_data_searchweb.png (180x320) [72.7 KB] || malaria_modeling_w_sat_data_thm.png (80x40) [6.6 KB] || malaria_modeling_w_sat_data_30593.pptx [3.1 MB] || malaria_modeling_w_sat_data_30593.key [5.8 MB] || malaria_modeling_w_sat_data.hwshow [222 bytes] || ", "hits": 35 }, { "id": 2565, "url": "https://svs.gsfc.nasa.gov/2565/", "result_type": "Visualization", "release_date": "2002-10-09T12:00:00-04:00", "title": "Mosquito Distribution Maps", "description": "These maps show mosquito habitat distribution for four mosquito species. The red/black areas are results of satellite data analysis showing where particular species of mosquitos can be found. The yellow lines are the 'published' boundaries for where these species can be found. There is a strong correlation between the two. These images were created in support of a story describing how NASA is assisting the CDC and EPA in tracking the spread of West Nile Virus. || ", "hits": 154 }, { "id": 2567, "url": "https://svs.gsfc.nasa.gov/2567/", "result_type": "Visualization", "release_date": "2002-10-09T12:00:00-04:00", "title": "Land Surface Temperature", "description": "The average temperature of the land is one component of a model used to predict the areas where mosquitos will flourish and where they will not. Satellite remote sensing can help construct maps of the average land surface temperature. These images were created in support of a story describing how NASA is assisting the CDC and EPA in tracking the spread of West Nile Virus. || ", "hits": 25 }, { "id": 2568, "url": "https://svs.gsfc.nasa.gov/2568/", "result_type": "Visualization", "release_date": "2002-10-09T12:00:00-04:00", "title": "NDVI Animation over Continental United States", "description": "The Normalized Differential Vegetation Index, NDVI, is one component of a model that is used to predict mosquito where mosquitos will flourish and where they will not. These images were created in support of a story describing how NASA is assisting the CDC and EPA in tracking the spread of West Nile Virus. || ", "hits": 24 } ] }