{ "count": 165, "next": "https://svs.gsfc.nasa.gov/api/search/?keywords=Environmental+science&limit=100&offset=100", "previous": null, "results": [ { "id": 14432, "url": "https://svs.gsfc.nasa.gov/14432/", "result_type": "Produced Video", "release_date": "2025-01-31T15:00:00-05:00", "title": "How NASA Sees the Air We Breathe", "description": "NASA and NOAA, among other agencies, worked together this summer through the STAQS and AEROMMA missions to calibrate and validate NASA’s new TEMPO satellite. The satellite and missions combined aim to not only better measure air quality, and the major pollutants that impact it, but also to improve air quality, from street to stratosphere. This effort was documented during the August 2023 campaign leg, which took place over the Chicago region. Complete transcript available.Universal Music Production: Night Swimmer Instrumental [PRS], Living In The Light Instrumental [PRS], Nanofiber Instrumental [PRS], Results Take Time Instrumental [PRS], Spin Foam Instrumental [PRS], and Mindful Instrumental [PRS]. \u2028Additional images courtesy of Rafael Méndez Peña Additional images courtesy of Community Research On Climate and Urban Science Department of Energy Integrated Urban Field LaboratoryThis video can be freely shared and downloaded. While the video in its entirety can be shared without permission, some individual imagery provided by ASF is obtained through permission and may not be excised or remixed in other products. For more information on NASA’s media guidelines, visit https://www.nasa.gov/multimedia/guidelines/index.html || STAQS_thumbnail_FINAL.jpg (1280x720) [648.9 KB] || STAQS_thumbnail_FINAL_print.jpg (1024x576) [461.5 KB] || STAQS_thumbnail_FINAL_web.png (320x180) [91.7 KB] || STAQS_Locked_Final.webm (1920x1080) [71.4 MB] || STAQS_transcript_en_US.en_US.srt [11.2 KB] || STAQS_transcript_en_US.en_US.vtt [11.2 KB] || STAQS_Locked_Final.mp4 (1920x1080) [1.3 GB] || ", "hits": 29 }, { "id": 14625, "url": "https://svs.gsfc.nasa.gov/14625/", "result_type": "Produced Video", "release_date": "2024-07-09T15:00:00-04:00", "title": "How NASA and Partners Look at Air Quality Around the Globe", "description": "Together with South Korea, Taiwan, Malaysia, Thailand, and the Philippines, NASA scientists took to the field for the Asia Air Quality campaign to better understand local air quality issues underneath the GEMS satellite— a sister satellite to North America’s TEMPO. || ", "hits": 14 }, { "id": 5325, "url": "https://svs.gsfc.nasa.gov/5325/", "result_type": "Visualization", "release_date": "2024-06-19T00:00:00-04:00", "title": "Tropspheric NO2 Column over Eastern United States, 2015-2023", "description": "Tropspheric NO2 column over Eastern United States, 2015-2023 || NO2_NE_2015-2023_1080p30.00001_print.jpg (1024x576) [158.6 KB] || NO2_NE_2015-2023_1080p30.00001_searchweb.png (320x180) [79.5 KB] || NO2_NE_2015-2023_1080p30.00001_thm.png (80x40) [5.9 KB] || NO2_NE_2015-2023_1080p30.mp4 (1920x1080) [13.1 MB] || This animation is an update to svs.gsfc.nasa.gov/4810, extending the visualization of OMI nitrogen dioxide data through 2023. || ", "hits": 66 }, { "id": 14507, "url": "https://svs.gsfc.nasa.gov/14507/", "result_type": "Produced Video", "release_date": "2024-04-18T08:40:00-04:00", "title": "NASA Joins the Jane Goodall Institute to Conserve Chimpanzee Habitat, Earth Information Center Videos", "description": "After years of forest loss, chimpanzee habitats are recovering. This is, in part, due to a collaboration between NASA and the Jane Goodall Institute (JGI). Using NASA Earth science satellite and other data, the Goodall Institute puts data into the hands of local communities to drive conservation across Africa’s equatorial forest belt.", "hits": 52 }, { "id": 5234, "url": "https://svs.gsfc.nasa.gov/5234/", "result_type": "Visualization", "release_date": "2024-03-12T00:00:00-04:00", "title": "AIRS Global Carbon Dioxide (CO₂) measurements (2002-October 2023)", "description": "Data visualization showing the global distribution and variation of the concentration of mid-tropospheric carbon dioxide observed by the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua spacecraft over a 20 year timespan.", "hits": 176 }, { "id": 14439, "url": "https://svs.gsfc.nasa.gov/14439/", "result_type": "Produced Video", "release_date": "2023-10-24T11:00:00-04:00", "title": "Air Pollution Model Runs", "description": "Soot. Exhaust. Ghosting smog. Air pollutants can travel in wind and wildfire smoke, brew by day, and change by the hour.Predictions of air pollution are created using complex models that combine information about weather and the emissions, transformation, and transport of chemical species and particles. The Goddard Earth Observing System Composition Forecasting (GEOS-CF) system is a research model maintained by NASA’s Global Modeling and Assimilation Office to help scientists understand the causes and impact of air pollution. It is one of the highest resolution and most detailed models of its kind in the world, made possible through ongoing collaborations between NASA and university scientists. GEOS-CF tracks the concentrations of hundreds of gas phase chemical species and dozens of types of particles characterized by their composition and size. It is used by a wide variety of stakeholders around the world to develop new methods for improving local predictions, understanding the impact of pollution on human health, and improving the quality of NASA satellite datasets. || ", "hits": 181 }, { "id": 14442, "url": "https://svs.gsfc.nasa.gov/14442/", "result_type": "Animation", "release_date": "2023-10-24T11:00:00-04:00", "title": "STAQS Air Quality Conceptual Illustrations", "description": "While poor air quality affects everyone, there are pollution hotspots that can adversely affect those nearest. For example, neighborhoods located near highways and warehouses can be hotspots of nitrogen dioxide (NO2) and hazardous particles called PM2.5, which are more than 35 times smaller in diameter than a grain of sand.For other residents, such as those located downwind from major cities like Chicago and New York, ozone can be an issue. While ozone high in the atmosphere protects Earth from dangerous solar radiation, at the ground level it can cause respiratory diseases and drive smog. Ozone ‘brewed’ in cities can travel to rural communities.Ground-level ozone along with another hazardous pollutant – tiny particles called PM2.5 – lead to over 100,000 premature deaths each year in the U.S. || ", "hits": 49 }, { "id": 14386, "url": "https://svs.gsfc.nasa.gov/14386/", "result_type": "Produced Video", "release_date": "2023-07-19T00:00:00-04:00", "title": "Take Flight with NASA's STAQS Campaign", "description": "Music credit: “Game Night Instrumental Wong” from Universal Production MusicStock footage: Pond5.comComplete transcript available. || STAQS_social_Thumbnail.jpg (1280x720) [482.2 KB] || STAQS_social_Thumbnail_print.jpg (1024x576) [372.7 KB] || STAQS_social_Thumbnail_web.png (320x180) [75.5 KB] || STAQS_social_Thumbnail_web-1.png (320x180) [75.5 KB] || STAQS_horizontal_final_revised.webm (1920x1080) [6.8 MB] || STAQS_horizontal_final_revised.mp4 (1920x1080) [116.9 MB] || ", "hits": 33 }, { "id": 5081, "url": "https://svs.gsfc.nasa.gov/5081/", "result_type": "Visualization", "release_date": "2023-03-07T00:00:00-05:00", "title": "National Carbon Dioxide (CO₂) budgets inferred from atmospheric observations", "description": "National yearly carbon dioxide (CO₂) budgets for over 100 countries around the world for the period 2015-2020. || NationalCO2Budgets_Light_1080x1920_30fps_358.png (1080x1920) [1.4 MB] || NationalCO2Budgets_Light_1080x1920.mp4 (1080x1920) [12.3 MB] || NationalCarbonDioxideBudget_Light (1080x1920) [0 Item(s)] || NationalCO2Budgets_Light_1080x1920.webm (1080x1920) [1.4 MB] || ", "hits": 183 }, { "id": 5022, "url": "https://svs.gsfc.nasa.gov/5022/", "result_type": "Visualization", "release_date": "2023-02-24T16:00:00-05:00", "title": "OCO-2 Gridded Global Carbon Dioxide (CO₂)", "description": "Data visualization of global carbon dioxide (CO₂) for the period January 2015-February 2022, showcasing data from NASA's Obriting Carbon Observatory 2 (OCO-2) Gridded/Level 3 product. || oco2_3840x2160p60.1618_print.jpg (1024x576) [112.6 KB] || oco2_3840x2160p60.1618.png (3840x2160) [6.1 MB] || oco2_3840x2160p60.1618_print_searchweb.png (320x180) [53.9 KB] || oco2_3840x2160p60.1618_print_thm.png (80x40) [4.4 KB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || oco2_3840x2160p30.mp4 (3840x2160) [46.0 MB] || oco2_3840x2160_p60.mp4 (3840x2160) [45.1 MB] || oco2_3840x2160_p60.webm (3840x2160) [13.5 MB] || ", "hits": 177 }, { "id": 5024, "url": "https://svs.gsfc.nasa.gov/5024/", "result_type": "Visualization", "release_date": "2023-01-31T22:00:00-05:00", "title": "20 years of AIRS Global Carbon Dioxide (CO₂) measurements (2002-October 2022)", "description": "Data visualization of global carbon dioxide (CO₂) for the period September 2002-October 2022, showcasing data products from NASA's Aqua mission. Data visualization assets are designed for HD resolution. || co2airs_60South_1920x108030p.0794_print.jpg (1024x576) [170.8 KB] || 60South_exr (1920x1080) [0 Item(s)] || co2airs_60South_1920x1080p30.mp4 (1920x1080) [25.0 MB] || co2airs_60South_1920x108030p.0794.exr (1920x1080) [5.5 MB] || co2airs_60South_1920x1080p30.webm (1920x1080) [3.0 MB] || co2airs_60South_1920x1080p30.mp4.hwshow [194 bytes] || ", "hits": 208 }, { "id": 5043, "url": "https://svs.gsfc.nasa.gov/5043/", "result_type": "Visualization", "release_date": "2022-11-02T08:00:00-04:00", "title": "Methane Emissions over Canada and Alaska in the 2018", "description": "This 3D volumetric visualization shows the emission and transport of atmospheric methane over Canada and Alaska in September 2018 with the date and colorbar. || methane_withDate.0068_print.jpg (1024x576) [282.8 KB] || methane_withDate.0068_searchweb.png (320x180) [94.8 KB] || methane_withDate.0068_thm.png (80x40) [14.7 KB] || methane_withDate (1920x1080) [0 Item(s)] || methane_withDate_1080p30.webm (1920x1080) [1.3 MB] || methane_withDate_1080p30.mp4 (1920x1080) [131.3 MB] || methane_withDate_1080p30.mp4.hwshow || ", "hits": 42 }, { "id": 5025, "url": "https://svs.gsfc.nasa.gov/5025/", "result_type": "Visualization", "release_date": "2022-09-14T17:30:00-04:00", "title": "20 years of AIRS Global Carbon Dioxide (CO₂) measurements (2002-May 2022)", "description": "Data visualization of global carbon dioxide (CO₂) for the period September 2002-May 2022, showcasing data products from NASA's Aqua mission. Data visualization assets are designed for HD resolution. || co2airs_60South_1920x108030p.0779.png (1920x1080) [1.8 MB] || co2airs_60South_1920x108030p.0779_print.jpg (1024x576) [171.8 KB] || co2airs_60South_1920x108030p.mp4 (1920x1080) [31.8 MB] || 60South_exr (1920x1080) [0 Item(s)] || co2airs_60South_1920x108030p.webm (1920x1080) [3.0 MB] || co2airs_60South_1920x108030p.mp4.hwshow [194 bytes] || ", "hits": 74 }, { "id": 5012, "url": "https://svs.gsfc.nasa.gov/5012/", "result_type": "Visualization", "release_date": "2022-09-13T12:00:00-04:00", "title": "Carbon Emissions from Fires: Jan 2003 - Jan 2022", "description": "This visualization protrays the weekly carbon emissions from fires between January 2003 and January 2022. A colorbar indicates the quantity of carbon emitted in each square meter during a week. || Carbon_emissions_with_overlay.6067_print.jpg (1024x576) [76.1 KB] || Carbon_emissions_with_overlay.6067_searchweb.png (180x320) [43.2 KB] || Carbon_emissions_with_overlay.6067_thm.png (80x40) [4.4 KB] || Carbon_emissions_with_overlay_p30_1080p30.mp4 (1920x1080) [42.7 MB] || Carbon_emissions_with_overlay_1080p60.mp4 (1920x1080) [42.6 MB] || Carbon_emissions_with_overlay_p30_1080p30.webm (1920x1080) [10.0 MB] || carbon_with_overlay (3840x2160) [256.0 KB] || carbon_with_overlay (3840x2160) [512.0 KB] || Carbon_emissions_with_overlay_p30_2160p30.mp4 (3840x2160) [110.4 MB] || Carbon_emissions_with_overlay_2160p60.mp4 (3840x2160) [109.7 MB] || Carbon_emissions_with_overlay_p30_1080p30.mp4.hwshow [224 bytes] || ", "hits": 67 }, { "id": 5007, "url": "https://svs.gsfc.nasa.gov/5007/", "result_type": "Visualization", "release_date": "2022-08-11T00:00:00-04:00", "title": "Trends in Global Atmospheric Methane (CH₄)", "description": "Timeplot of global atmospheric methane (CH4) showing the full NOAA record (September 1983-March 2022). This version is created with a dark background. || MethaneTrends_Dark_3840x216030p.1512_print.jpg (1024x576) [44.0 KB] || MethaneTrends_Dark_3840x216030p.1512.png (3840x2160) [508.9 KB] || MethaneTrends_Dark_3840x216030p.1512_searchweb.png (180x320) [13.1 KB] || MethaneTrends_Dark_3840x216030p.1512_thm.png (80x40) [2.2 KB] || MethaneTrends_Dark_3840x216030p.1512_web.png (320x180) [13.1 KB] || MethaneTrends_Dark_1080p30.mp4 (1920x1080) [3.7 MB] || MethaneTrends_Dark_1080p30.webm (1920x1080) [4.6 MB] || MethaneTrends_Dark (3840x2160) [0 Item(s)] || MethaneTrends_Dark_3840x216030p.mp4 (3840x2160) [16.4 MB] || MethaneTrends_Dark_3840x216030p.1512.exr (3840x2160) [886.5 KB] || ", "hits": 114 }, { "id": 4990, "url": "https://svs.gsfc.nasa.gov/4990/", "result_type": "Visualization", "release_date": "2022-05-28T00:00:00-04:00", "title": "20 years of AIRS Global Carbon Dioxide (CO₂) measurements (2002- March 2022)", "description": "Data visualization of global carbon dioxide (CO2) for the period September 2002-March 2022, showcasing data products from NASA's Aqua mission. Data visualization assets are designed for HD resolution. || co2airs_60South_1920x108030p.0771.png (1920x1080) [1.8 MB] || co2airs_60South_1920x1080p30.mp4 (1920x1080) [24.2 MB] || composite_60South (1920x1080) [0 Item(s)] || co2airs_60South_1920x1080p30.webm (1920x1080) [2.9 MB] || co2airs_60South_1920x1080p30.mp4.hwshow [228 bytes] || ", "hits": 108 }, { "id": 14056, "url": "https://svs.gsfc.nasa.gov/14056/", "result_type": "Produced Video", "release_date": "2022-03-24T11:00:00-04:00", "title": "NASA Tracks COVID-19’s Atmospheric Fingerprint", "description": "Universal Production Music: The Mysterious Staircase by Brice Davoli [SACEM], Suspended in Time by Brice Davoli [SACEM]Stock Footage: Pond5Complete transcript available. || 14056_Still.jpg (1920x1080) [939.6 KB] || 14056_Still_searchweb.png (320x180) [61.8 KB] || 14056_Still_thm.png (80x40) [5.4 KB] || 14056_Atmo.mov (1920x1080) [3.2 GB] || 14056_Atmo.mp4 (1920x1080) [233.2 MB] || 14056_Twitter_Atmo.mp4 (1280x720) [60.2 MB] || 14056_Twitter_Atmo.webm (1280x720) [24.8 MB] || 14056_atmo.en_US.srt [4.7 KB] || 14056_atmo.en_US.vtt [4.4 KB] || ", "hits": 71 }, { "id": 4959, "url": "https://svs.gsfc.nasa.gov/4959/", "result_type": "Visualization", "release_date": "2021-12-13T00:00:00-05:00", "title": "Reduction in Tropospheric NOx and Ozone Corresponding to Worldwide COVID-19 Lockdowns", "description": "When the world went into lockdown to slow the spread of COVID-19, air pollution emissions started to rapidly decrease leaving a global atmospheric fingerprint detected by a team of scientists at NASA’s Jet Propulsion Laboratory using satellite measurements. These traces provided an unexpected window into what low-emissions world could look like, thus providing a means for identifying effective environmental policies. While many countries in the last few decades have implemented environmental policies to reduce human health risk from air pollution by controlling emissions, the impacts of those policies have not always been clear. The global lockdowns in response to COVID-19 represent a well-observed “scenario-of-opportunity” that allows us to assess how atmospheric emission and composition responds to reduced human activity. COVID-19 lockdowns effectively showed how reducing NOx emissions affects the global atmosphere. Its identifying signature shows up as in the atmosphere’s altered ability to produce harmful ozone pollution and ozone’s reduced influence on Earth’s heat balance that affects climate. These effects are not uniform across the world and depend on the location and season of the emission reductions.The results of this research indicate that in order to design effective environmental policies which benefit both air quality and climate, decision-makers need to carefully consider the complex relationships between emissions and atmospheric composition. || ", "hits": 62 }, { "id": 4912, "url": "https://svs.gsfc.nasa.gov/4912/", "result_type": "Visualization", "release_date": "2021-06-09T12:30:00-04:00", "title": "Global Tropospheric Ozone Response to Worldwide COVID-19 Lockdowns", "description": "Free tropospheric ozone anomaly at 500 hPa || covid_ozone_z9_500hPa.00900_print.jpg (1024x576) [141.7 KB] || covid_ozone_z9_500hPa.00900_searchweb.png (320x180) [74.2 KB] || covid_ozone_z9_500hPa.00900_thm.png (80x40) [6.6 KB] || covid_ozone_z9_500hPa.mp4 (1920x1080) [87.1 MB] || covid_ozone_z9_500hPa.webm (1920x1080) [5.4 MB] || covid_ozone_z9_500hPa.mp4.hwshow [214 bytes] || ", "hits": 40 }, { "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": 67 }, { "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": 59 }, { "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": 35 }, { "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": 31 }, { "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": 37 }, { "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": 41 }, { "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": 32 }, { "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": 94 }, { "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": 58 }, { "id": 4890, "url": "https://svs.gsfc.nasa.gov/4890/", "result_type": "Visualization", "release_date": "2021-04-02T12:00:00-04:00", "title": "GeoCarb Observes Greenhouse Gasses from Geosynchronous Orbit", "description": "GeoCarb and OCO-2 measuring carbon dioxide from space || geocarb_HD_FINAL.4662_print.jpg (1024x576) [49.8 KB] || geocarb_HD_FINAL.4662_searchweb.png (320x180) [32.3 KB] || geocarb_HD_FINAL.4662_thm.png (80x40) [2.9 KB] || geocarb_HD_FINAL_1080p59.94.mp4 (1920x1080) [43.1 MB] || geocarb_HD_FINAL_1080p29.97.mp4 (1920x1080) [41.3 MB] || geocarb_HD_FINAL_1080p59.94.webm (1920x1080) [19.9 MB] || 1920x1080_16x9_60p (1920x1080) [1.0 MB] || 3840x2160_16x9_60p (3840x2160) [1.0 MB] || 5780x3240_16x9_30p (5760x3240) [1.0 MB] || geocarb_4k_FINAL_2160p59.94.mp4 (3840x2160) [135.4 MB] || ", "hits": 109 }, { "id": 13800, "url": "https://svs.gsfc.nasa.gov/13800/", "result_type": "Produced Video", "release_date": "2021-03-22T09:30:00-04:00", "title": "Landsat Helps Warn of Algae in Lakes and Rivers", "description": "From space, satellites including the NASA and U.S. Geological Survey’s (USGS) Landsat 8 can help scientists identify lakes where an algal bloom has formed. It’s a complicated data analysis process, but one that researchers are automating so resource managers around the country can use the satellite data to identify potential problems.Music: Light From Dark by Adam Salkedi, Neil Pollard [PRS], published by Atmosphere Music Ltd.; Experimental Design by Laurent Dury [SACEM], published by Koka Media; Against The Wall by Benjamin Peter McAvoy [PRS], published by Sound Pocket Music; Brainstorming by Laurent Dury[SACEM], published by Koka Media; Together As One by Le Fat Club [SACEM], Olivier Grim [SACEM]; published by Koka Media.Complete transcript available.Watch this video on the NASA Goddard YouTube channel. || 13800_aquatic_reflection_poster.png (1564x936) [2.7 MB] || 13800_aquatic_reflection_poster_print.jpg (1024x612) [237.1 KB] || 13800_aquatic_reflection_poster_searchweb.png (320x180) [130.5 KB] || 13800_aquatic_reflection_poster_thm.png (80x40) [10.8 KB] || 13800_aquatic_reflectance_prores.mov (1920x1080) [5.3 GB] || 13800_aquatic_reflectance_yt.mp4 (1920x1080) [632.1 MB] || 13800_aquatic_reflectance_fb.mp4 (1920x1080) [473.0 MB] || 13800_aquatic_reflectance_tw-720.mp4 (1280x720) [161.2 MB] || 13800_aquatic_reflectance_yt.webm (1920x1080) [21.7 MB] || 13800_aquatic_reflectance-captions.en_US.srt [9.4 KB] || 13800_aquatic_reflectance-captions.en_US.vtt [9.0 KB] || ", "hits": 61 }, { "id": 13807, "url": "https://svs.gsfc.nasa.gov/13807/", "result_type": "Produced Video", "release_date": "2021-02-17T11:00:00-05:00", "title": "NASA Helps Identify Uptick in Emissions of Ozone-Depleting Compounds", "description": "Music: \"Hidden Movement\" Universal Production Music Complete transcript available. || Screen_Shot_2021-02-10_at_9.41.20_AM_print.jpg (1024x569) [115.7 KB] || Screen_Shot_2021-02-10_at_9.41.20_AM.png (2267x1261) [3.1 MB] || Screen_Shot_2021-02-10_at_9.41.20_AM_searchweb.png (320x180) [87.6 KB] || Screen_Shot_2021-02-10_at_9.41.20_AM_thm.png (80x40) [6.9 KB] || CFC_11_RC_5.webm (1920x1080) [6.5 MB] || 13807_CFC11.mp4 (1920x1080) [389.2 MB] || CFC11RC5.en_US.srt [3.4 KB] || ", "hits": 135 }, { "id": 13702, "url": "https://svs.gsfc.nasa.gov/13702/", "result_type": "Produced Video", "release_date": "2020-08-27T11:00:00-04:00", "title": "Satellites See Fires Burning Across California", "description": "In August 2020, California is facing several major fires, including the LNU Lightning Complex Fire which grew into the second-largest wildfire in California history. The state's heat waves, droughts, and lightning all played a role in the devastating fire season. || ", "hits": 31 }, { "id": 4799, "url": "https://svs.gsfc.nasa.gov/4799/", "result_type": "Visualization", "release_date": "2020-07-09T14:00:00-04:00", "title": "Sources of Methane", "description": "This 3D volumetric visualization shows the emission and transport of atmospheric methane around the globe between December 9, 2017 and December 1, 2018.Music: \"Motion Blur\" by Sam Dobson [PRS]Complete transcript available.This video is also available on our YouTube channel. || Global_methane_narrated.1416_print.jpg (1024x576) [171.2 KB] || composite (1920x1080) [0 Item(s)] || MethaneNarrationSM.webm (1920x1080) [15.5 MB] || MethaneNarrationSM.mp4 (1920x1080) [171.1 MB] || MethaneCaptionsenUS.en_US.srt [2.0 KB] || MethaneCaptionsenUS.en_US.vtt [2.0 KB] || MethaneNarration.mov (1920x1080) [1.6 GB] || ", "hits": 888 }, { "id": 13647, "url": "https://svs.gsfc.nasa.gov/13647/", "result_type": "Produced Video", "release_date": "2020-06-25T07:45:00-04:00", "title": "NASA, ESA, JAXA Release Global View of COVID-19 Impacts", "description": "NASA, ESA (European Space Agency) and JAXA (Japan Aerospace Exploration Agency) have created a dashboard of satellite data showing impacts on the environment and socioeconomic activity caused by the global response to the coronavirus (COVID-19) pandemic.The dashboard will be released on Thursday, June 25 during a tri-agency media briefing. The briefing speakers are:•Josef Aschbacher, director of ESA Earth Observation Programmes•Thomas Zurbuchen, associate administrator of NASA’s Science Mission Directorate•Koji Terada, vice president and director general for the Space Technology Directorate at JAXA•Shin-ichi Sobue, project manager for JAXA’s ALOS-2 mission•Ken Jucks, program scientist for NASA’s OCO-2 and Aura missions•Anca Anghelea, open data scientist, ESA Earth observation programmes || ", "hits": 88 }, { "id": 4835, "url": "https://svs.gsfc.nasa.gov/4835/", "result_type": "Visualization", "release_date": "2020-06-18T00:00:00-04:00", "title": "NO2 Decline Related to Restrictions Due to COVID-19 in South America", "description": "On June 1, the World Health Organization noted that Central and South American countries have become “the intense zones” for COVID-19 transmission. The Ozone Monitoring Instrument (OMI) on board NASA’s Aura satellite provides data that indicate that restrictions on human activity have led to about a 36% decrease in NO2 levels in Rio de Janeiro, Brazil, relative to previous years. Other large cities in South America show similar decreases in NO2: 36% in Santiago, Chile; 35% in São Paolo, Brazil; and 40% in Buenos Aires, Argentina. One notable exception is in Lima, Peru, showing a 69% decrease. The large decrease may partly be associated with natural variations in weather that can, for instance, disperse air pollution more quickly. Additional analysis is required to determine the amount of the decrease of NO2 in Lima that is associated with a decrease in human activity. A notable increase in NO2 occurred in northern South America, which is likely associated with increased agricultural burning in 2020 relative to previous years. || ", "hits": 66 }, { "id": 31142, "url": "https://svs.gsfc.nasa.gov/31142/", "result_type": "Hyperwall Visual", "release_date": "2020-05-18T00:00:00-04:00", "title": "COVID-19: NASA Satellite Data Show Drop in Air Pollution Over U.S.", "description": "Tropospheric NO2 Column, March 15-April 15 2015-2019 average vs. 2020, USA regions || 3-regions_1080p.00001_print.jpg (1024x576) [141.7 KB] || 3-regions_1080p.00001_searchweb.png (320x180) [62.9 KB] || 3-regions_1080p.00001_thm.png (80x40) [5.2 KB] || 3-regions_1080p.mp4 (1920x1080) [1.9 MB] || 3-regions_720p.mp4 (1280x720) [1.0 MB] || 3-regions_1080p.webm (1920x1080) [2.3 MB] || 3-regions_2160p.mp4 (3840x2160) [5.6 MB] || ", "hits": 107 }, { "id": 4810, "url": "https://svs.gsfc.nasa.gov/4810/", "result_type": "Visualization", "release_date": "2020-04-24T00:00:00-04:00", "title": "Reductions in Pollution Associated with Decreased Fossil Fuel Use Resulting from COVID-19 Mitigation", "description": "Over the past several weeks, the United States has seen significant reductions in air pollution over its major metropolitan areas. Similar reductions in air pollution have been observed in other regions of the world. || Tropospheric NO2 Column, Animated GIF || cropped_NO2_2019_2020.gif (848x862) [54.4 MB] || cropped_NO2_2019_2020_print.jpg (1024x1040) [318.2 KB] || cropped_NO2_2019_2020_searchweb.png (320x180) [102.2 KB] || ", "hits": 157 }, { "id": 4798, "url": "https://svs.gsfc.nasa.gov/4798/", "result_type": "Visualization", "release_date": "2020-04-21T00:00:00-04:00", "title": "Earth Day 2020: Global Atmospheric Methane", "description": "This 3D volumetric visualization shows a global view of the methane emission and transport between December 1, 2017 and November 30, 2018. This visualizaion of the rotating global view is designed to be played in a continuous loop.This video is also available on our YouTube channel. || Earth_Day_Methane_loop.2919_print.jpg (1024x576) [102.0 KB] || Earth_Day_Methane_loop.2919_searchweb.png (320x180) [54.3 KB] || Earth_Day_Methane_loop.2919_thm.png (80x40) [5.0 KB] || loop_composite (1920x1080) [0 Item(s)] || Earth_Day_Methane_loop_1080p30.webm (1920x1080) [11.5 MB] || Earth_Day_Methane_loop_1080p30.mp4 (1920x1080) [355.8 MB] || captions_silent.29410.en_US.srt [43 bytes] || Earth_Day_Methane_loop_1080p30.mp4.hwshow [196 bytes] || ", "hits": 77 }, { "id": 13580, "url": "https://svs.gsfc.nasa.gov/13580/", "result_type": "Produced Video", "release_date": "2020-04-14T10:30:00-04:00", "title": "NASA Models the Complex Chemistry of Earth's Atmosphere", "description": "Music: \"Interconnecting Threads\" by Axel Tenner [GEMA]; \"Night Drift\" by Andrew Michael Britton [PRS], David Stephen Goldsmith [PRS], from Universal Production MusicWatch this video on the NASA Goddard YouTube channel. Complete transcript available. || ChemicalSpecies_Still_print.jpg (1024x576) [313.1 KB] || ChemicalSpecies_Still.jpg (3840x2160) [2.0 MB] || ChemicalSpecies_Still_searchweb.png (320x180) [104.5 KB] || ChemicalSpecies_Still_web.png (320x180) [104.5 KB] || ChemicalSpecies_Still_thm.png (80x40) [7.8 KB] || 13580_ChemSpecies_Final.mov (1920x1080) [1.8 GB] || 13580_ChemSpecies_Final_lowres.mp4 (1280x720) [82.5 MB] || 13580_ChemSpecies_Final.mp4 (1920x1080) [467.4 MB] || 13580_ChemSpecies_Final.webm (1920x1080) [2.7 MB] || ChemicalSpecies.en_US.srt [4.2 KB] || ChemicalSpecies.en_US.vtt [4.2 KB] || ", "hits": 57 }, { "id": 4789, "url": "https://svs.gsfc.nasa.gov/4789/", "result_type": "Visualization", "release_date": "2020-03-23T10:00:00-04:00", "title": "Global Atmospheric Methane", "description": "This first 3D volumetric visualization focuses on several continents showing the emission and transport of atmospheric methane around the globe between January 1, 2017 and November 30, 2018. This video is also available on our YouTube channel. || Global_methane_comp.1320_print.jpg (1024x576) [163.2 KB] || Global_methane_comp_1080p30.webm (1920x1080) [22.1 MB] || composite (1920x1080) [0 Item(s)] || captions_silent.29083.en_US.srt [43 bytes] || Global_methane_comp_1080p30.mp4 (1920x1080) [1.4 GB] || Global_methane_comp_1080p30.mp4.hwshow || ", "hits": 105 }, { "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": 59 }, { "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": 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": 58 }, { "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": 44 }, { "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": 52 }, { "id": 13543, "url": "https://svs.gsfc.nasa.gov/13543/", "result_type": "Produced Video", "release_date": "2020-02-12T10:00:00-05:00", "title": "Landsat: Farming Data From Space", "description": "Landsat satellites have been gathering data for 48 years, equipping scientists and farmers to answer big questions about how to improve agriculture around the world. From tracking crop production, assessing crop health, and monitoring water use, Landsat data provides tangible benefits to the USA and the world. Landsat satellites are built and lauched by NASA, and operated by USGS. Complete transcript available.Music: \"Lines of Enquiry\" by Theo Golding [PRS], published by Atmosphere Music [PRS]Watch this video on the NASA Goddard YouTube channel. || LandsatAg-Thumbnail.png (1920x1080) [4.0 MB] || LandsatAg-Thumbnail_print.jpg (1024x576) [166.3 KB] || LandsatAg-Thumbnail_searchweb.png (320x180) [109.3 KB] || LandsatAg-Thumbnail_thm.png (80x40) [6.6 KB] || LandsatAg-FINAL.mov (1920x1080) [3.2 GB] || LandsatAg-FINAL_youtube_1080.mp4 (1920x1080) [148.1 MB] || LandsatAg-FINAL_facebook_720.mp4 (1280x720) [110.9 MB] || LandsatAg-FINAL_twitter_720.mp4 (1280x720) [20.1 MB] || LandsatAg-FINAL.webm (960x540) [39.3 MB] || LandsatAg-FINAL-captions.en_US.srt [1.8 KB] || LandsatAg-FINAL-captions.en_US.vtt [1.8 KB] || ", "hits": 131 }, { "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": 94 }, { "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": 89 }, { "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": 121 }, { "id": 13284, "url": "https://svs.gsfc.nasa.gov/13284/", "result_type": "Produced Video", "release_date": "2019-08-16T11:00:00-04:00", "title": "Students Work with NASA to Forecast Dust Storms", "description": "Four Maryland high school students were inspired by a documentary to find a way to let people know when a potentially hazardous dust storm is incoming. Using National Weather Service forecasts improved by NASA data, their Dust Watch app alerts people about incoming dust storms. || ", "hits": 23 }, { "id": 13281, "url": "https://svs.gsfc.nasa.gov/13281/", "result_type": "Produced Video", "release_date": "2019-08-13T11:00:00-04:00", "title": "NASA Studies How Arctic Fires Change the World", "description": "Music: Stepping Stone Bridge by Timothy Michael Hammond [PRS], Wayne Roberts [PRS]Watching Ladybirds by Benjamin James Parsons [PRS] This video can be freely shared and downloaded. While the video in its entirety can be shared without permission, some individual imagery provided by pond5.com and Artbeats is obtained through permission and may not be excised or remixed in other products. Specific details on stock footage may be found here. For more information on NASA’s media guidelines, visit https://www.nasa.gov/multimedia/guidelines/index.html. Complete transcript available. || Thumbnail_Arctic_Fires_Print.jpg (1920x1080) [917.1 KB] || Thumbnail_Arctic_Fires_Print_searchweb.png (320x180) [121.3 KB] || Thumbnail_Arctic_Fires_Print_thm.png (80x40) [8.0 KB] || 13281_Arctic_Fires_720.mp4 (1280x720) [265.3 MB] || 13281_Arctic_Fires.mov (1920x1080) [3.5 GB] || 13281_Arctic_Fires.webm (1920x1080) [21.2 MB] || 13281_Arctic_Fires.en_US.srt [4.1 KB] || 13281_Arctic_Fires.en_US.vtt [4.0 KB] || ", "hits": 108 }, { "id": 13262, "url": "https://svs.gsfc.nasa.gov/13262/", "result_type": "Produced Video", "release_date": "2019-07-22T11:00:00-04:00", "title": "NASA and NOAA Take to the Air to Chase Smoke", "description": "Music: Broad Horizons by Chris White [PRS]Complete transcript available. || Still.png (1773x995) [3.3 MB] || Still_print.jpg (1024x574) [163.4 KB] || Still_searchweb.png (320x180) [119.4 KB] || Still_thm.png (80x40) [7.0 KB] || TWITTER_720_13692_FIREExKickoff_twitter_720.mp4 (1280x720) [27.0 MB] || 13692_FIREExKickoff.webm (960x540) [44.5 MB] || 13262_FIREExKickoff.mov (1920x1080) [1.4 GB] || YOUTUBE_1080_13692_FIREExKickoff_youtube_1080.mp4 (1920x1080) [207.3 MB] || 13262_FIREEx.en_US.srt [2.9 KB] || 13262_FIREEx.en_US.vtt [2.9 KB] || ", "hits": 162 }, { "id": 4729, "url": "https://svs.gsfc.nasa.gov/4729/", "result_type": "Visualization", "release_date": "2019-07-18T00:00:00-04:00", "title": "FIREX-AQ Prelaunch Data Visualization", "description": "This data visualization starts with an overview of the United States west coast. As we zoom into several California wildfires, MODIS data dissolves in to show some of the low-lying smoke resulting from these fires. The camera then pans across the United States, slowly revealing CALIPSO swath passes as they dissect the atmosphere. Throughout most of the journey CALIPSO picks up many aerosol signatures as shown in the more opaque portions of the curtain. || firex_comp2.0400_print.jpg (1024x576) [167.7 KB] || firex_comp2.0400_searchweb.png (320x180) [119.9 KB] || firex_comp2.0400_thm.png (80x40) [7.4 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || firex_comp2_1080p30.webm (1920x1080) [12.0 MB] || firex_comp2_1080p30.mp4 (1920x1080) [100.7 MB] || firex_comp2_1080p30.mp4.hwshow [185 bytes] || ", "hits": 61 }, { "id": 4728, "url": "https://svs.gsfc.nasa.gov/4728/", "result_type": "Visualization", "release_date": "2019-07-11T11:00:00-04:00", "title": "Carbon Emissions from Fires: 2003 - 2018", "description": "This visualization shows carbon emissions from fires from January 1, 2003 through December 31, 2018. The colorbar reflects the quantity of carbon emitted. || carbonEmissions_wDate.1687_print.jpg (1024x576) [98.0 KB] || carbonEmissions_wDate.1687_searchweb.png (320x180) [57.2 KB] || carbonEmissions_wDate.1687_thm.png (80x40) [5.4 KB] || carbonEmissions_wDate_1080p30.mp4 (1920x1080) [37.4 MB] || carbonEmission_comp (1920x1080) [0 Item(s)] || carbonEmissions_wDate_1080p30.webm (1920x1080) [6.8 MB] || carbonEmissions_wDate_1080p30.mp4.hwshow [230 bytes] || ", "hits": 32 }, { "id": 13192, "url": "https://svs.gsfc.nasa.gov/13192/", "result_type": "Produced Video", "release_date": "2019-06-21T11:00:00-04:00", "title": "NASA Helps Warn of Harmful Algal Blooms", "description": "With limited resources to dedicate to monitoring for harmful algal blooms, water managers are looking to new technologies from NASA and its partners to detect and monitor potential hazards in lakes and reservoirs. || ", "hits": 23 }, { "id": 13152, "url": "https://svs.gsfc.nasa.gov/13152/", "result_type": "Produced Video", "release_date": "2019-02-28T12:30:00-05:00", "title": "2015-2016 El Niño Triggered Disease Outbreaks Across the Globe", "description": "Music: Under Offer by Peter Keith Yelland-BrownComplete transcript available. || ENSO_Dengue_Thumbnail.png (1920x1080) [3.2 MB] || ENSO_Dengue_Thumbnail_print.jpg (1024x576) [143.5 KB] || ENSO_Dengue_Thumbnail_searchweb.png (320x180) [88.1 KB] || ENSO_Dengue_Thumbnail_thm.png (80x40) [6.2 KB] || ENSO_Dengue_FINAL_lowres.mp4 (1280x720) [39.4 MB] || ENSO_Dengue_FINAL_lowres.webm (1280x720) [16.2 MB] || ENSO_Dengue_Captions.en_US.srt [2.6 KB] || ENSO_Dengue_Captions.en_US.vtt [2.6 KB] || ENSO_Dengue_FINAL.mov (1920x1080) [3.9 GB] || ", "hits": 73 }, { "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": 51 }, { "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": 378 }, { "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": 28 }, { "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": 100 }, { "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": 12372, "url": "https://svs.gsfc.nasa.gov/12372/", "result_type": "B-Roll", "release_date": "2016-09-13T16:00:00-04:00", "title": "ORACLES B-roll", "description": "Southern Africa produces almost a third of the world’s vegetative burning, which sends smoke particles up into the atmosphere, where they eventually mix with stratocumulus clouds over the southeastern Atlantic Ocean. The Observations of Clouds above Aerosols and their Interactions (ORACLES) study is investigating how these particles impact the stratocumulus clouds, which play a key role in both regional and global surface temperatures and precipitation, in order to help improve current climate models. A team of scientists worked out of Walvis Bay, Nambia, with NASA’s P-3 and ER-2 research aircraft to get first-hand measurements of clouds and aerosols in August-Sept, 2016. || ", "hits": 11 }, { "id": 4381, "url": "https://svs.gsfc.nasa.gov/4381/", "result_type": "Visualization", "release_date": "2015-10-14T12:00:00-04:00", "title": "Nebraska Water Usage", "description": "Animation begins with a wide view of the entire United States and then zooms down to an area in Nebraska where water usage studies have been done using Landsat-8 satellite data. The camera slowly pans across the area first showing true color Landsat-8 data, then transitioning to temperature data (in shades of orange and violet), then to ETRF (shades of green), ending with an extrusion of water use data (shades of blue) where the camera pulls back to show the entire area of interest. || neb_v2.2150_print.jpg (1024x576) [191.2 KB] || neb_v2.mp4 (1920x1080) [52.8 MB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || neb_v2.webm (1920x1080) [8.6 MB] || neb_v2.mp4.hwshow [335 bytes] || ", "hits": 29 }, { "id": 11900, "url": "https://svs.gsfc.nasa.gov/11900/", "result_type": "Produced Video", "release_date": "2015-07-21T13:00:00-04:00", "title": "Instagram: Scientists Link Earlier Melting Of Snow To Dark Aerosols", "description": "Tiny particles suspended in the air, known as aerosols, can darken snow and ice causing it to absorb more of the sun’s energy. But until recently, scientists rarely considered the effect of all three major types of light-absorbing aerosols together in climate models.In a new study, NASA scientists used a climate model to examine the impact of this snow-darkening phenomenon on Northern Hemisphere snowpacks, including how it affects snow amount and heating on the ground in spring.The study looked at three types of light-absorbing aerosols – dust, black carbon and organic carbon. Black carbon and organic carbon are produced from the burning of fossil fuels, like coal and oil, as well as biofuels and biomass, such as forests.With their snow darkening effect added to NASA’s GEOS-5 climate model, scientists analyzed results from 2002 to 2011, and compared them to model runs done without the aerosols on snow. They found that the aerosols indeed played a role in absorbing more of the sun’s energy. Over broad places in the Northern Hemisphere, the darkened snow caused some surface temperatures to be up to 10 degrees Fahrenheit warmer than it would be if the snow were pristine. As a result, warmer, snow-darkened areas had less snow in spring than they would have had under pristine snow conditions.According to the study, dust’s snow darkening effect significantly contributed to surface warming in Central Asia and the western Himalayas. Black carbon’s snow darkening effect had a larger impact primarily in Europe, the eastern Himalayas and East Asia. It had a smaller impact in North America. Organic carbon’s snow darkening effect was relatively lower but present in regions such as southeastern Siberia, northeastern East Asia and western Canada.“As we add more of these aerosols to the mix, we are potentially increasing our overall impact on Earth’s climate,” said research scientist Teppei Yasunari at NASA’s Goddard Space Flight Center in Greenbelt, Maryland.Research: Impact of snow darkening via dust, black carbon, and organic carbon on boreal spring climate in the Earth systemJournal: Geophysical Research: Atmospheres, June 15, 2015.Link to paper: http://onlinelibrary.wiley.com/doi/10.1002/2014JD022977/fullHere is the YouTube video. || ", "hits": 31 }, { "id": 11812, "url": "https://svs.gsfc.nasa.gov/11812/", "result_type": "Produced Video", "release_date": "2015-03-29T00:00:00-04:00", "title": "A Tale of Three Cities: Beijing, Los Angeles, Atlanta", "description": "Dr. Bryan N. Duncan is a deputy project scientist for the Aura Mission at NASA Goddard. In this talk he tells the story of air quality in three cities-Beijing, Los Angeles, and Atlanta.For complete transcript, click here. || G2015-017_Air_Quality_TedTalk_nasaportal_print.jpg (1024x576) [74.5 KB] || G2015-017_Air_Quality_TedTalk_nasaportal_searchweb.png (320x180) [63.8 KB] || G2015-017_Air_Quality_TedTalk_nasaportal_print_thm.png (80x40) [6.7 KB] || G2015-017_Air_Quality_TedTalk_appletv.webm (960x540) [100.6 MB] || G2015-017_Air_Quality_TedTalk_appletv.m4v (960x540) [323.4 MB] || G2015-017_Air_Quality_TedTalk_youtube_hq.mov (1280x720) [416.3 MB] || G2015-017_Air_Quality_TedTalk_1280x720.wmv (1280x720) [342.1 MB] || G2015-017_Air_Quality_TedTalk_prores.mov (1280x720) [13.8 GB] || G2015-017_Air_Quality_TedTalk_appletv_subtitles.m4v (960x540) [323.0 MB] || G2015-017_Air_Quality_TedTalk_ipod_lg.m4v (640x360) [135.3 MB] || G2015-017_Air_Quality_TedTalk_nasaportal.mov (640x360) [290.3 MB] || TedTalk_AirQuality.en_US.srt [18.0 KB] || G2015-017_Air_Quality_TedTalk_ipod_sm.mp4 (320x240) [60.7 MB] || ", "hits": 67 }, { "id": 11648, "url": "https://svs.gsfc.nasa.gov/11648/", "result_type": "Produced Video", "release_date": "2014-09-10T09:00:00-04:00", "title": "Ozone minimum concentrations, 1979-2013", "description": "Visualizations of ozone concentrations over the southern hemisphere.Data is from ozonewatch.gsfc.nasa.gov || ", "hits": 56 }, { "id": 30515, "url": "https://svs.gsfc.nasa.gov/30515/", "result_type": "Hyperwall Visual", "release_date": "2014-06-30T13:00:00-04:00", "title": "Simulated Atmospheric Carbon Concentrations", "description": "Carbon exists in many forms—e.g., carbon dioxide (CO2), carbon monoxide (CO)—and continually cycles through Earth’s atmosphere, ocean, and terrestrial ecosystems. This visualization, created using data from the 7-km GEOS-5 Nature Run model, shows average column concentrations of atmospheric CO2 (colored shades) and CO (white shades underneath) from January 1, 2006 to December 31, 2006.CO2 variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and pink shades represent regions where CO2 concentrations are enhanced by carbon sources, mainly from human activities. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of CO2 through photosynthesis, thus removing CO2 from the atmosphere. Atmospheric CO, a pollutant harmful to human health, is produced mainly from fossil fuel combustion and biomass burning. Here, high concentrations of CO (white) are mainly from fire activity in Africa, South America, and Australia. Scientists use model output data such as these to help answer important questions about Earth’s climate and to help design future satellite missions.These model simulations use fossil fuel emissions estimates provided by the Emissions Database for Global Atmospheric Research (EDGAR). NASA’s Quick Fire Emissions Dataset (QFED) estimates fire emissions using MODIS fire radiative power observations. Additional, observationally constrained estimates of CO2 flux between the atmosphere and land and ocean carbon reservoirs were produced as part of NASA’s Carbon Monitoring System Flux Pilot Project (http://carbon.nasa.gov/cgi-bin/cms/inv_pgp.pl?pgid=581). Land biosphere fluxes come from the Carnegie-Ames-Stanford Approach Global Fire Emissions Database (CASA-GFED) model which incorporates MODIS vegetation classification and AVHRR Normalized Difference Vegetation Index (NDVI) data. Ocean fluxes are produced by the NASA Ocean Biogeochemical Model (NOBM) which incorporates MODIS chlorophyll observations. || ", "hits": 118 }, { "id": 30392, "url": "https://svs.gsfc.nasa.gov/30392/", "result_type": "Hyperwall Visual", "release_date": "2013-10-24T12:00:00-04:00", "title": "Monthly Chlorophyll Concentrations", "description": "At the base of the ocean food web are single-celled algae and other plant-like organisms known as phytoplankton. Like plants on land, phytoplankton use chlorophyll and other light-harvesting pigments to carry out photosynthesis, absorbing atmospheric carbon dioxide to produce sugars for fuel. Chlorophyll in the water changes the way it reflects and absorbs sunlight, allowing scientists to map the amount and location of phytoplankton. These measurements give scientists valuable insights into the health of the ocean environment, and help scientists study the ocean carbon cycle. These monthly chlorophyll maps show milligrams of chlorophyll per cubic meter of seawater from July 2002 to the present, derived using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard NASA’s Aqua satellite. Places where chlorophyll amounts were very low, indicating very low numbers of phytoplankton are blue. Places where chlorophyll concentrations were high, meaning many phytoplankton were growing, are yellow. Land is dark gray, and places where MODIS could not collect data because of sea ice, polar darkness, or clouds are light gray. The highest chlorophyll concentrations, where tiny surface-dwelling ocean plants are thriving, are in cold polar waters or in places where ocean currents bring cold water to the surface. || ", "hits": 108 }, { "id": 30190, "url": "https://svs.gsfc.nasa.gov/30190/", "result_type": "Hyperwall Visual", "release_date": "2013-10-17T12:00:00-04:00", "title": "Saharan Dust over the Atlantic", "description": "Easterly winds carry Saharan dust from Africa high above the North Atlantic Ocean. At left, a natural color image captured by NASA’s Aqua satellite shows the dust as it travels offshore on September 21, 2009. The dust plume is shaped by the wind, forming waves near the surface immediately offshore. An even higher, thinner tan cloud veils the surface-level dust. Dust has infiltrated into different heights of the atmosphere. Differences in wind direction at various heights in the atmosphere create the “X” near the center of the dust plume.In certain atmospheric conditions, dust from the Sahara Desert is transported clear around the globe. In fact, many scientists use space-based multi-angle imaging to track the journey of dust. Having the capability to track dust from space, provides even greater opportunities for understanding atmospheric circulation patterns at a global scale. || ", "hits": 27 }, { "id": 4062, "url": "https://svs.gsfc.nasa.gov/4062/", "result_type": "Visualization", "release_date": "2013-06-30T00:00:00-04:00", "title": "Georgia Urban Sprawl", "description": "One of the many ways to keep FEMA maps up to date is by tracking urban change using satellite imagery. Take this suburb of Atlanta, Georgia as an example. By mining Landsat images spanning a 27 year period, it's possible to identify areas where the land surface has permanently changed and affect the areas ability to absorb water.The river to the Northwest is the Chattahoochee River. The \"Y\"-shaped roads are Interstate 85 (upper branch) and Route 316 (lower branch). As the years go by, one can see the Mall of Georgia being built in the upper middle part of the screen, immediately north of Interstate 85. Surrounding neighborhoods sprout up throughout this whole area as we move through time. This animation was created for use in a NASA video on water run-off changes related to urban sprawl titled \"FEMA Risk Map\". || ", "hits": 93 }, { "id": 11221, "url": "https://svs.gsfc.nasa.gov/11221/", "result_type": "Produced Video", "release_date": "2013-04-12T00:00:00-04:00", "title": "GPM: Our Wet Wide World", "description": "The Global Precipitation Measurement (GPM) is an international satellite mission to provide next-generation observations of rain and snow worldwide every three hours. NASA and the Japan Aerospace Exploration Agency (JAXA) will launch a \"Core\" satellite carrying advanced instruments that will set a new standard for precipitation measurements from space. The data they provide will be used to unify precipitation measurements made by an international network of partner satellites to quantify when, where, and how much it rains or snows around the world.The GPM mission will help advance our understanding of Earth's water and energy cycles, improve the forecasting of extreme events that cause natural disasters, and extend current capabilities of using satellite precipitation information to directly benefit society. || ", "hits": 23 }, { "id": 11054, "url": "https://svs.gsfc.nasa.gov/11054/", "result_type": "Produced Video", "release_date": "2012-08-02T12:00:00-04:00", "title": "Earth's Water Cycle", "description": "Water is the fundamental ingredient for life on Earth. Looking at our Earth from space, with its vast and deep ocean, it appears as though there is an abundance of water for our use. However, only a small portion of Earth's water is accessible for our needs. How much fresh water exists and where it is stored affects us all. This animation uses Earth science data from a variety of sensors on NASA Earth observing satellites as well as cartoons to describe Earth's water cycle and the continuous movement of water on, above and below the surface of the Earth. Sensors on a suite of NASA satellites observe and measure water on land, in the ocean and in the atmosphere. These measurements are important to understanding the availability and distribution of Earth's water — vital to life and vulnerable to the impacts of climate change on a growing world population.NASA Earth Observing System Data and Information Systems (EOSDIS) EOSDIS is a distributed system of twelve data centers and science investigator processing systems. EOSDIS processes, archives, and distributes data from Earth observing satellites, field campaigns, airborne sensors, and related Earth science programs. These data enable the study of Earth from space to advance scientific understanding.For questions, please contact eosdis-outreach@lists.nasa.gov || ", "hits": 240 }, { "id": 3905, "url": "https://svs.gsfc.nasa.gov/3905/", "result_type": "Visualization", "release_date": "2012-04-13T09:00:00-04:00", "title": "Mapping Diseases", "description": "The print-resolution still images were created for the February 2012 issue of The Scientist (print and online). In an article in the same issue, NASA scientist Assaf Anyamba explains how he can predict diseases with remote-sensing data.The data used are: 1. NDVI is an index that quantifies the photosynthetic capacity of vegetation. It is derived from visible and near-infrared reflectance measurements made by Advanced Very High Resolution Radiometer (AVHRR) sensors onboard NOAA's polar orbiting satellites (in this case NOAA-17). Taken as time series measurements, NDVI indicates the response of vegetation to seasonal and interannual variations in climate.2. SST data are a blend of direct observations from ships, buoys, satellite imagery also from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) instruments, and SSTs simulated by sea-ice cover. The monthly optimum interpolated fields were derived by a linear interpolation of the weekly fields to daily fields, and then averaging daily values over a month.All anomaly fields (as shown here) are derived by subtracting the monthly values from the respective long-term monthly means. || ", "hits": 29 }, { "id": 10935, "url": "https://svs.gsfc.nasa.gov/10935/", "result_type": "Produced Video", "release_date": "2012-03-21T00:00:00-04:00", "title": "Visions of Goddard", "description": "Excerpts of 14 short films about the NASA's Goddadrd Space Flight Center. || ", "hits": 43 }, { "id": 10926, "url": "https://svs.gsfc.nasa.gov/10926/", "result_type": "Produced Video", "release_date": "2012-03-08T12:00:00-05:00", "title": "Evaporation and Transpiration", "description": "Much of the water that soaks into the soil from irrigation or rain ultimately returns the the atmosphere as water vapor through direct evaporation from the surface or by transpiration through plant leaves as the plants use the water for growth and seed production. This loss cools the surface and plant canopy just like the evaporation of sweat cools our skin. A cool field in an arid area indicates water use by irrigation. Using the surface temperatures measured by satellites, and some additional information, water resource managers can determine the rate at which water is used in a farm field. || ", "hits": 371 }, { "id": 3807, "url": "https://svs.gsfc.nasa.gov/3807/", "result_type": "Visualization", "release_date": "2011-08-31T00:00:00-04:00", "title": "Predicting Disease Outbreaks from Space", "description": "These visualizations were created for the May 18, 2012 Library of Congress Talk Predictiding Disease Outbreaks from Space. In this talk NASA scientist Assaf Anyamba, will present how using remote-sensing data we can see links among weather, diseases and famine.An early warning system more than a decade in development successfully predicted the 2006-2007 outbreak of the deadly Rift Valley Fever (RVF) in East Africa and subsequent outbreaks in Sudan (2007) and South Africa (2008-2011). RVF is a deadly hemorrhagic disease transmitted by mosquitoes that infects livestock and human populations episodically. An international team of research scientists, public-health professionals, agricultural specialists and military personnel had worked for a decade to successfully predict when and where an outbreak of RVF would occur. || ", "hits": 34 }, { "id": 3845, "url": "https://svs.gsfc.nasa.gov/3845/", "result_type": "Visualization", "release_date": "2011-06-29T00:00:00-04:00", "title": "Discover-AQ: Targeted Airborne and Ground-Based Observations of Near-Surface Pollution", "description": "The project is called DISCOVER-AQ, which stands for Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality. Discover - AQ is a four-year campaign to improve the use of satellites to monitor air quality for public health and environmental benefit. The fundamental challenge for satellites measuring air quality is to distinguish between pollution near the surface and pollution higher in the atmosphere. Scientific questions remain about the vertical distribution of pollutants. How far up in the atmosphere are morning and evening spikes in pollution associated with rush hour noticeable? How does ozone, which peaks near the surface in afternoon, behave at other altitudes throughout the day? When is the best time of the day for satellites to measure various pollutants?Measurements from aircraft, in combination with ground-based measurements, offer a key perspective that makes such distinctions easier to make. The problem is particularly pronounced for pollutants that are abundant at the surface and higher in the atmosphere. For example, a \"Code Red\" air-quality day during the summer might produce very high concentrations of ozone in the bottom few kilometers of the atmosphere, yet generate a change of a mere 1 or 2 percent to a total column of ozone. Studies suggest that discrepancies of as much as 30 to 50 percent exist between estimates of ground nitrogen dioxide inferred from the Ozone Monitoring Instrument(OMI), an instrument on NASA's Aura satellite launched in 2004, and measurements from ground-based instruments. DISCOVER-AQ will address such problems by helping researchers develop a three-dimensional view of how air pollutants are distributed and move between different levels of the atmosphere throughout the day.A phalanx of ground-based instruments will offer a critical view of the same patches of air the aircraft are monitoring from above. While NASA sponsors certain ground instruments, other institutions including the Environmental Protection Agency, the Maryland Department of the Environment, Howard University, and Pennsylvania State University manage the instruments at the ground stations.Scientists will use information collected during the DISCOVER-AQ campaign to improve measurements from existing satellites and to help establish parameters for future NASA satellite missions that will monitor air quality. More information is available at http://www.nasa.gov/mission_pages/discover-aq/index.html. || ", "hits": 24 }, { "id": 10800, "url": "https://svs.gsfc.nasa.gov/10800/", "result_type": "Produced Video", "release_date": "2011-06-23T00:00:00-04:00", "title": "Discover-AQ", "description": "NASA's launching a new mission this summer designed to better understand air pollution and gather data that could allow pollutants to be monitored more exactly from space. The field study coined, \"Discover-AQ\", will take place over the Baltimore/DC region on select days in July. || ", "hits": 18 }, { "id": 3783, "url": "https://svs.gsfc.nasa.gov/3783/", "result_type": "Visualization", "release_date": "2010-10-21T00:00:00-04:00", "title": "Iceland's Eyjafjallajökull Volcanic Ash Plume May 6-8, 2010 - Stereoscopic Version", "description": "During April and May, 2010, the Eyjafjallajökull volcano on Iceland's southern coast erupted, creating an expansive ash cloud that disrupted air traffic throughout Europe and across the Atlantic. This animation shows the flow of this ash cloud for three days in early May on an hourly basis as sensed from a geostationary satellite. The ash cloud heights were determined using an approach developed by NOAA/NESDIS/STAR for the next generation of Geostationary Operational Environmental Satellite (GOES-R). Data from EUMETSAT's Spinning Enhanced Visible and Infrared Imager (SEVIRI) was used as a proxy for GOES-R Advanced Baseline Imager (ABI) data. This data is shown intersecting with the CALIPSO Parallel Attenuated Backscatter curtain on May 6th. In this page the visualization content is offered in two different modes to accommodate stereoscopic systems as: Left and Right Eye separate and Left and Right Eye side-by-side combined on the same frame. || ", "hits": 55 }, { "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": 235 }, { "id": 3737, "url": "https://svs.gsfc.nasa.gov/3737/", "result_type": "Visualization", "release_date": "2010-06-22T00:00:00-04:00", "title": "Tropospheric Column Ozone", "description": "These visuals present retrieved global distribution of tropospheric column ozone from NASA's AURA spacecraft. Tropospheric ozone is close the ground and a component of pollution. This should be distinguished from high-altitude (stratospheric) ozone which shields the Earth's surface from ultraviolet radiation. Ozone measurements from the OMI and MLS instruments on board the Aura satellite are used for deriving global distributions of tropospheric column ozone (TCO). TCO is determined using the tropospheric ozone residual method which involves subtracting measurements of MLS stratospheric column ozone (SCO) from OMI total column ozone after adjusting for intercalibration differences of the two instruments using the convective-cloud differential method. The derived TCO field, which covers one complete year of mostly continuous daily measurements from January 2005 through December 2006, is used for studying the regional and global pollution on a timescale of a few days to months. MLS and OMI are two out of a total of four instruments on board the Aura spacecraft which is flown in a sunsynchronous polar orbit at 705 km altitude with a 98.2 degree inclination. The spacecraft has an equatorial crossing time of 1:45 pm (ascending node) with around 98.8 min per orbit (14.6 orbits per day on average). OMI is a nadir-scanning instrument that at visible (350-500 nm) and UV wavelength channels (UV-1: 270-314 nm; UV-2: 306-380 nm) detects backscattered solar radiance to measure column ozone. The MLS instrument is a thermal-emission microwave limb sounder that measures vertical profiles of mesospheric, stratospheric, and upper tropospheric temperature, ozone and other constituents from limb scans ahead of the Aura satellite. The MLS profile measurements are taken about 7 min before OMI views the same location during ascending (daytime) orbital tracks. These are referred as \"collocated\" measurements between OMI and MLS. The data shows signals due to convection, biomass burning, stratospheric influence, pollution, and transport. They are capable of capturing the spatiotemporal evolution of tropospheric column ozone. For more information see the links below: http://www.nasa.gov/vision/earth/environment/ozone_resource_page.htmlhttp://acdb-ext.gsfc.nasa.gov/Data_services/cloud_slice/#nd || ", "hits": 47 }, { "id": 3667, "url": "https://svs.gsfc.nasa.gov/3667/", "result_type": "Visualization", "release_date": "2010-06-03T00:00:00-04:00", "title": "Ship Tracks Reveal Pollution's Effects on Clouds", "description": "NASA's MODIS satellite instrument is revealing that humans may be changing our planet's brightness. Pollution in the atmosphere creates smaller, brighter cloud droplets that reflect more sunlight back to space and may have a slight impact on global warming.This narrated visualization illustrates how we can study the effect against a clean backdrop by looking for zones of pollution in otherwise pristine air - in this case the North Pacific Ocean near the Aleutian islands. On an overcast day, the clouds look uniform. However, MODIS' sesor reveals a different picture - long skinny trails of brighter clouds hidden within. As ships travel across the ocean, pollution in the ships' exhaust create more cloud drops that are smaller in size, resulting in even brighter clouds. On clear days, ships can actually create new clouds. Water vapor condenses around the particles of pollution, forming streamers of clouds as the ships travel on. The ship tracks themselves are too small to impact global temperatures, but they help us understand how larger pollution sources such as industrial sites or agricultural burning might be changing clouds on a larger scale. || ", "hits": 57 }, { "id": 10562, "url": "https://svs.gsfc.nasa.gov/10562/", "result_type": "Produced Video", "release_date": "2010-05-27T00:00:00-04:00", "title": "Gulf of Mexico Oil Spill", "description": "You can learn more about NASA's satellite observations of the oil spill by visiting https://www.nasa.gov/topics/earth/features/oilspill/. || ", "hits": 60 }, { "id": 10612, "url": "https://svs.gsfc.nasa.gov/10612/", "result_type": "Produced Video", "release_date": "2010-05-12T00:00:00-04:00", "title": "The Smog Bloggers", "description": "Has pollen got you sneezing? Wondering what's causing that mysterious afternoon haze? How do you find out what's in the air you are breathing? For the thousands of people who visit the University of Maryland Baltimore County's \"Smog Blog\" each day, the answer is just a web click away. The Smog Bloggers combine laser measurements of current air quality with NASA satellite data to paint a daily picture of air pollution across the US. To date, the blog has received over two million hits, and is itself a big hit with weather forecasters, astronomers, asthma sufferers, and those with just a healthy curiosity about what kinds of pollution they may be breathing in. For complete transcript, click here. || G2010-057_Smog_Bloggers_YouTubeHQ.01477_print.jpg (1024x576) [98.1 KB] || G2010-057_Smog_Bloggers_YouTubeHQ_web.png (320x180) [262.6 KB] || G2010-057_Smog_Bloggers_YouTubeHQ_thm.png (80x40) [17.4 KB] || G2010-057_Smog_Bloggers_appletv.webmhd.webm (960x540) [53.5 MB] || G2010-057_Smog_Bloggers_appletv.m4v (960x720) [146.6 MB] || G2010-057_Smog_Bloggers_Youtube.mov (1280x720) [58.9 MB] || G2010-057_Smog_Bloggers_YouTubeHQ.mov (1280x720) [113.1 MB] || G2010-057_Smog_Bloggers_iPod_large.m4v (640x360) [45.3 MB] || G2010-057_Smog_Bloggers_iPod_small.m4v (320x180) [17.5 MB] || G2010-057_Smog_Bloggers_NASA_PORTAL.wmv (346x260) [46.4 MB] || G2010-057_Smog_Bloggers_SVS.mpg (512x288) [36.2 MB] || ", "hits": 19 }, { "id": 10514, "url": "https://svs.gsfc.nasa.gov/10514/", "result_type": "Produced Video", "release_date": "2009-12-11T18:00:00-05:00", "title": "Terra@10: Terra 10th Anniversary Video", "description": "The Earth-observing satellite Terra celebrates its tenth anniversary in 2009. This video highlights how Terra has helped us better understand our home planet. The satellite's five instruments - ASTER, CERES, MISR, MODIS and MOPITT - reveal how our our world is changing. For complete transcript, click here. || Terra10_ipodlarge.08402_print.jpg (1024x576) [38.3 KB] || Terra10_ipodlarge_web.png (320x180) [47.8 KB] || Terra10_ipodlarge_thm.png (80x40) [4.3 KB] || Terra10_Apple_TV.webmhd.webm (960x540) [71.4 MB] || Terra10_Youtube.mov (1280x720) [72.8 MB] || Terra10_Apple_TV.m4v (960x720) [179.0 MB] || Terra10_H.264.mov (1280x720) [146.6 MB] || Terra10_ipodlarge.m4v (640x360) [55.7 MB] || Terra10.mpg (512x288) [118.8 MB] || Terra10_ipodsmall.m4v (320x180) [24.0 MB] || Terra10.wmv (346x260) [18.2 MB] || ", "hits": 26 }, { "id": 10513, "url": "https://svs.gsfc.nasa.gov/10513/", "result_type": "Produced Video", "release_date": "2009-12-11T00:00:00-05:00", "title": "A Landsat Flyby", "description": "The Landsat program is the longest continuous global record of the Earth's surface, and continues to deliver both visually stunning and scientifically valuable images of our planet. This short video highlights Landsat's many benefits to society. || ", "hits": 24 }, { "id": 3637, "url": "https://svs.gsfc.nasa.gov/3637/", "result_type": "Visualization", "release_date": "2009-10-05T12:00:00-04:00", "title": "Deforestation of Rondonia, Brazil from 1975 to 2009", "description": "In the 1970s, Brazil's Program of National Integration built roads across the Amazon and settled land along these roads with colonists. These roads were catalysts of land use change in the Amazon.Brazil is also home to more than a quarter of Earth's tropical forests. Considering that the band of lush green that circles the globe through many equatorial nations is fundamental to the overall health of the whole planet's environment, careful monitoring of forest health in the tropics is essential. Tropical forests act as major carbon 'sinks', places where ambient carbon dioxide in the atmosphere can be absorbed by growing things and sequestered for years. Definitive evidence shows that excess carbon dioxide can contribute to the greenhouse effect and speed global warming. Similarly, tropical forests also act as a primary producer of oxygen. In the respiration process that absorbs gaseous carbon dioxide, trees and other plants give off oxygen.Data taken in 1975 and 2009 from the Landsat series of spacecraft shows enormous tracts of forest disappearing in Rondonia, Brazil. || ", "hits": 62 }, { "id": 3632, "url": "https://svs.gsfc.nasa.gov/3632/", "result_type": "Visualization", "release_date": "2009-09-14T00:00:00-04:00", "title": "Evapotranspiration from Landsat", "description": "Instruments on the Landsat satellites capture images in the visible spectrum, but they also take images in wavelengths invisible to the naked eye. Landsat's thermal imager captures land surface temperature data. As farmers irrigate fields, water evaporates from the soil and transpires from plants' leaves. The combined process is called evapotranspiration. Evapotranspiring water absorbs energy, so farm fields consuming more water appear cooler in the thermal band. Landsat-based evapotranspiration measurements provide an objective way for water managers to assess on a field-by-field basis how much water agricultural growers are using. The measurements have even been used to help settle water rights conflicts in court. || ", "hits": 49 }, { "id": 10402, "url": "https://svs.gsfc.nasa.gov/10402/", "result_type": "Produced Video", "release_date": "2009-03-11T00:00:00-04:00", "title": "Rain, Drought, Urbanization Contributing Factors for Storms", "description": "On March 14, 2008, a tornado swept through downtown Atlanta, its 130 mile-per-hour winds ripping holes in the roof of the Georgia Dome, blowing out office windows and trashing parts of Centennial Olympic Park. It was an event so rare in an urban landscape that researchers immediately began to examine NASA satellite data and historical archives to see what weather and climatological ingredients may have combined to brew such a storm. Read more at http://www.nasa.gov/topics/earth/features/atlanta_tornado.html. || ", "hits": 18 }, { "id": 10207, "url": "https://svs.gsfc.nasa.gov/10207/", "result_type": "Produced Video", "release_date": "2008-04-20T12:00:00-04:00", "title": "NASA Satellites Aid in Chesapeake Bay Recovery", "description": "From the distant reaches of the Universe, to black holes, and the Martian surface, NASA explores some of the most far out parts of space. But NASA also does research much closer to home. In fact, NASA Earth Science satellites are taking part in the management and recovery of an ecosystem right in our backyard, the Chesapeake Bay. || ", "hits": 12 }, { "id": 3509, "url": "https://svs.gsfc.nasa.gov/3509/", "result_type": "Visualization", "release_date": "2008-04-16T00:00:00-04:00", "title": "Las Vegas Growth from Landsat", "description": "This sequence of images from the earliest Landsat satellite to the present captures the dramatic growth of Las Vegas, Nevada. From 1973 to 2006, the population of Las Vegas grew from 358,000 to over 2 million. || ", "hits": 49 }, { "id": 10184, "url": "https://svs.gsfc.nasa.gov/10184/", "result_type": "Produced Video", "release_date": "2008-01-30T00:00:00-05:00", "title": "Urban Growth in Las Vegas", "description": "In May 1973, less than a year after the first of NASA's Landsat satellites was launched, Las Vegas, Nevada had a population of only 358,000. By 2006 the population had ballooned to over 2 million. Still one of America's fastest growing urban areas, this series of Landsat scenes from four different years shows just how dramamtic the growth of Las Vegas has been. || ", "hits": 51 }, { "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": 12 }, { "id": 3471, "url": "https://svs.gsfc.nasa.gov/3471/", "result_type": "Visualization", "release_date": "2007-10-05T00:00:00-04:00", "title": "SeaWiFS Biosphere Data over the North Pacific (Slow Version)", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land.This animation is essentially the same as animation #3454 with a few minor changes and runs at a slower speed. || ", "hits": 12 }, { "id": 3494, "url": "https://svs.gsfc.nasa.gov/3494/", "result_type": "Visualization", "release_date": "2007-10-05T00:00:00-04:00", "title": "SeaWiFS Biosphere Data over Australia", "description": "The SeaWiFS instrument aboard the Seastar satellite has been collecting ocean data since 1997. By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This animation represents nearly a decade's worth of data taken by the SeaWiFS instrument, showing the abundance of life in the sea. Dark blue represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. || ", "hits": 6 }, { "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": 10 }, { "id": 3452, "url": "https://svs.gsfc.nasa.gov/3452/", "result_type": "Visualization", "release_date": "2007-04-23T12:00:00-04:00", "title": "Global Rotation of SeaWiFS Biosphere Decadal Average without 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": 22 }, { "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": 14 }, { "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": 13 }, { "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": 21 } ] }