{ "count": 15, "next": null, "previous": null, "results": [ { "id": 5107, "url": "https://svs.gsfc.nasa.gov/5107/", "result_type": "Visualization", "release_date": "2023-06-16T10:00:00-04:00", "title": "Air Quality Monitoring Stations in Washington D.C.", "description": "All air quality monitoring stations that measure particulate matter 2.5 (PM2.5) located in Washington D.C. The government operated stations are circled in white. Click the download dropdown for more versions. || dc_air_stations_full_preview.png (1920x1080) [1.1 MB] || dc_air_stations_4320.png (4320x2160) [2.0 MB] || dc_stations_basemap_4320.png (4320x2160) [1.9 MB] || dc_air_stations_full_4320.png (4320x2160) [2.0 MB] || dc_air_stations_full_preview_searchweb.png (320x180) [44.6 KB] || dc_air_stations_full_preview_thm.png (80x40) [3.8 KB] || ", "hits": 52 }, { "id": 5110, "url": "https://svs.gsfc.nasa.gov/5110/", "result_type": "Visualization", "release_date": "2023-06-16T10:00:00-04:00", "title": "Atmospheric Carbon Dioxide Tagged by Source", "description": "Carbon dioxide (CO2) is the most prevalent greenhouse gas driving global climate change. However, its increase in the atmosphere would be even more rapid without land and ocean carbon sinks, which collectively absorb about half of human emissions every year. Advanced computer modeling techniques in NASA's Global Modeling and Assimilation Office allow us to disentangle the influences of sources and sinks and to better understand where carbon is coming from and going to. ||", "hits": 878 }, { "id": 4603, "url": "https://svs.gsfc.nasa.gov/4603/", "result_type": "Visualization", "release_date": "2018-05-22T15:00:00-04:00", "title": "Cholera Risk Maps", "description": "Cholera Risk, Pre-Hurricane || cholera_risk_pre.1000_print.jpg (1024x576) [92.1 KB] || cholera_risk_pre.1000_searchweb.png (320x180) [65.9 KB] || cholera_risk_pre.1000_thm.png (80x40) [5.9 KB] || cholera_risk_pre (1920x1080) [0 Item(s)] || cholera_risk_pre_1080p30.mp4 (1920x1080) [18.1 MB] || cholera_risk_pre_1080p30.webm (1920x1080) [6.9 MB] || cholera_risk_pre_1080p30.mp4.hwshow [190 bytes] || ", "hits": 53 }, { "id": 12958, "url": "https://svs.gsfc.nasa.gov/12958/", "result_type": "Produced Video", "release_date": "2018-05-18T14:00:00-04:00", "title": "Using Precipitation Data to Assess Risk of Cholera Outbreaks", "description": "Music: \"A New Hope,\" Al Lethbridge, Atmosphere Music Ltd PRS; \"Spirals within a Sphere,\" Adam Salkeld, Atmosphere Music Ltd PRSComplete transcript available. || cholera_still_print.jpg (1024x695) [243.6 KB] || cholera_still_searchweb.png (320x180) [119.4 KB] || cholera_still_thm.png (80x40) [7.6 KB] || 12958_Cholera_GPM_prores.mov (1920x1080) [3.1 GB] || 12958_Cholera_GPM_twitter_720.mp4 (1280x720) [54.2 MB] || 12958_Cholera_GPM_youtube_720.mp4 (1280x720) [430.0 MB] || 12958_Cholera_GPM_facebook_720.mp4 (1280x720) [337.4 MB] || 12958_Cholera_GPM_youtube_1080.mp4 (1920x1080) [490.1 MB] || 12958_Cholera_GPM_prores.webm (1920x1080) [23.6 MB] || 12958_Cholera_GPM_large.mp4 (1920x1080) [235.1 MB] || 12958_Cholera.en_US.srt [4.2 KB] || 12958_Cholera.en_US.vtt [4.2 KB] || ", "hits": 51 }, { "id": 40348, "url": "https://svs.gsfc.nasa.gov/gallery/esddatafor-societal-benefits/", "result_type": "Gallery", "release_date": "2018-04-24T00:00:00-04:00", "title": "ESD data for Societal Benefit", "description": "No description available.", "hits": 157 }, { "id": 4581, "url": "https://svs.gsfc.nasa.gov/4581/", "result_type": "Visualization", "release_date": "2017-07-24T00:00:00-04:00", "title": "Using Satellite and Ground-based Data to Develop Malaria Risk Maps", "description": "Malaria is a major problem in the Amazon where malaria mosquitoes tend to prefer wet, hot areas with more standing water. Seasonal occupational movement along rivers and in forested areas increases transmission and concentrates malaria in specific regions. The objective of Malaria Project, an ongoing study led by William Pan and Ben Zaitchik, is to develop a detection and early warning system for malaria risk in the Amazon. Using data from NASA satellites and a Land Data Assimilation System (LDAS), the scientists hope that their research can help health officials pinpoint where to deploy resources and what resources to deploy during a disease outbreak. By incorporating NASA data such as precipitation, soil moisture, air temperature, and humidity into their new system, scientists are better able to predict where malaria-spreading mosquitoes are breeding. These climate factors in conjunction with a population density and human movement model will help scientists better understand where and when people are at high risk for malaria. The malaria warning system will predict outbreaks and simulate response to help a country's health care system to more strategically determine where to deploy their resources. Visualizations focus on Peru, one of the central areas of malaria transmission in the Amazon. Four LDAS data sets -- precipitation, soil moisture, air temperature, and humidity are illustrated below. Combined with public health data, the animations show how these factors may affect the outbreak and evolvement of the disease. || ", "hits": 38 }, { "id": 3656, "url": "https://svs.gsfc.nasa.gov/3656/", "result_type": "Visualization", "release_date": "2009-10-17T00:00:00-04:00", "title": "Sea Level Rise \"What Ifs\" in the Southeastern United States", "description": "This visualization shows the Southeastern United States with population data over the land. Darker areas over land indicate higher population densities. Sea level scenarios are shown starting with 0 meters of sea level rise (current sea level) and proceeding through 9 meters of rise. Blue areas moving inland indicate where the coastline would be at various levels.We will likely see some sea level rise in our lifetimes, but the middle-to-higher levels in this visualization are unlikely in the next 100 years.This visualization is based on Shuttle Radar Topography Mission (SRTM) data. This data primarily measured canopy heights. So, this visualization is showing where water might reach the tops of the trees in various areas. || ", "hits": 15 }, { "id": 10496, "url": "https://svs.gsfc.nasa.gov/10496/", "result_type": "Produced Video", "release_date": "2009-10-07T09:00:00-04:00", "title": "Science for a Hungry World: Land Cover Land Use Change", "description": "NASA remote sensing data is used to measure how much land is used for agriculture and where farms are in relation to population density. This episode explore the transition between native vegetation, farms, and cities. Satellites show where land use changes have been most significant.For complete transcript, click here. || 320x190.10127_print.jpg (1024x576) [132.1 KB] || 80x40_thumbnail.jpg (80x40) [5.6 KB] || 160x80_gallery_thumbnail.jpg (160x80) [16.8 KB] || 320x190_web_thumbnail.jpg (320x239) [73.7 KB] || 320x190_web_thumbnail_searchweb.jpg (320x180) [121.2 KB] || LCLUC_1280x720_AppleTV.webmhd.webm (960x540) [59.0 MB] || LCLUC_1280x720_AppleTV.m4v (960x540) [157.9 MB] || LCLUC_1280x720_H264.mov (1280x720) [178.8 MB] || LCLUC_640x480_ipod.m4v (640x360) [50.4 MB] || LCLUC_320x240_ipod.mp4 (320x180) [18.5 MB] || Ag_LCLUC_Ep3_FullRes.mov (1280x720) [4.2 GB] || bigmovie-agriculture_part3_video.hwshow || ", "hits": 39 }, { "id": 3629, "url": "https://svs.gsfc.nasa.gov/3629/", "result_type": "Visualization", "release_date": "2009-10-05T12:00:00-04:00", "title": "Crop Intensity", "description": "The U.S. Department of Agriculture (USDA) and the National Aeronautics and Space Administration (NASA) signed a Memorandum of Understanding (MOU) to strengthen collaboration. In support of this collaboration, NASA and the USDA Foreign Agricultural Service (FAS) jointly funded a new project to assimilate NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data and products into an existing decision support system (DSS) operated by the International Production Assessment Division (IPAD) of FAS. To meet its objectives, FAS/IPAD uses satellite data and data products to monitor agriculture worldwide and to locate and keep track of natural disasters such as short and long term droughts, floods and persistent snow cover which impair agricultural productivity. FAS is the largest user of satellite imagery in the non-military sector of the U.S. government. For the last 20 years FAS has used a combination of Landsat and NOAA-AVHRR satellite data to monitor crop condition and report on episodic events.To successfully monitor worldwide agricultural regions and provide accurate agricultural production assessments, it is important to understand the spatial distribution of croplands. To do this a global croplands mask to identify all sites used for crop production. Croplands are highly variable both temporally and spatially. Croplands vary from year to year due to events such as drought and fallow periods, and they vastly differ across the globe in accordance with characteristics such as cropping intensity and field size. A flexible crop likelihood mask is used to help depict these varying characteristics of global crop cover. Regions featuring intensive agro-industrial farming practices such as the Maize Triangle in South Africa will have higher confidence values in the crop mask as compared to less intensively farmed regions in parts of Sub-Saharan Africa where cropland identification is partly confounded with natural background vegetation phenologies. Thus, a customized threshold can be employed to examine areas of varying cropping intensification. || ", "hits": 42 }, { "id": 3601, "url": "https://svs.gsfc.nasa.gov/3601/", "result_type": "Visualization", "release_date": "2009-06-27T12:00:00-04:00", "title": "Global Agricultural Monitoring", "description": "The U.S. Department of Agriculture (USDA) and the National Aeronautics and Space Administration (NASA) signed a Memorandum of Understanding (MOU) to strengthen collaboration. In support of this collaboration, NASA and the USDA Foreign Agricultural Service (FAS) jointly funded a new project to assimilate NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data and products into an existing decision support system (DSS) operated by the International Production Assessment Division (IPAD) of FAS. To meet its objectives, FAS/IPAD uses satellite data and data products to monitor agriculture worldwide and to locate and keep track of natural disasters such as short and long term droughts, floods and persistent snow cover which impair agricultural productivity. FAS is the largest user of satellite imagery in the non-military sector of the U.S. government. For the last 20 years FAS has used a combination of Landsat and NOAA-AVHRR satellite data to monitor crop condition and report on episodic events. || ", "hits": 34 }, { "id": 3491, "url": "https://svs.gsfc.nasa.gov/3491/", "result_type": "Visualization", "release_date": "2008-03-13T12:00:00-04:00", "title": "Pacific Anthropogenic Aerosol Optical Depth (AOD) in 2003", "description": "According to measurements taken with a satellite instrument, vast quantities of industrial aerosols and smoke from biomass burning in East Asia and Russia are traveling from one side of the globe to another. Explosive economic growth in Asia has profound implications for the atmosphere worldwide. Data collected by a NASA satellite shows a dense blanket of polluted air over the Northwestern Pacific. This brown cloud is a toxic mix of ash, acids, and airborne particles from car and factory emissions, as well as from low-tech polluters like coal-burning stoves and from forest fires. This image generated by data from NASA's instrument called MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the Terra satellite demonstrates how large and pervasive this transport phenomenon is across vast areas. China's exports fill shelves around the world, but according to a new NASA research paper, China also heavily exports pollution. This week, space agency scientists reveal how Chinese industrialization and Russian forest fires in combination with pollution transported eastward from Europe send roughly 18 teragrams - almost 40 billion pounds-of pollution aerosols into the atmosphere over the Northwestern Pacific every year. The MODIS instrument on NASA's Terra satellite has been tracking the particulate pollution for more than seven years, gathering data as most of it drifted east across the Pacific Ocean. About 4.5 teragrams of particulate pollution each year could reach the western boundary of North America, which is about 15% of local emissions of particulate pollutants from the U.S. and Canada. In the last two decades, China has more than doubled its pollution production. This boom may be contributing to substantial changes in climate and weather in places far from the origin of the particulates. Never in human history-anywhere-has there been industrial growth like that in modern China. But with fast growth comes unintended consequences, and from space evidence of those consequences is starting to emerge. The research relies on measurements of something called \"aerosol optical thickness\". It's a quantitative measurement about how well a slice of atmosphere transmits light. The greater the value of optical thickness for a given location, the less light of a particular wavelength can pass through it. Measurements of aerosol optical thickness describe quantities of tiny particles in a given volume. By measuring how much light can penetrate a region of atmosphere across a variety of wavelengths, scientists can make certain inferences about the quantity and type of particles blocking that light. This visualization shows the seasonal variations of transport of pollution aerosols across the North Pacific. The East Asian airstream carries its largest pollution loading in spring and smallest in summer and fall. With heavy concentrations of aerosols represented by shades of brown, scientists can track the origins and distribution of the particles as they travel in the atmosphere. The sequence also shows a trail of substantial aerosol concentrations from a variety of sources. These sources include heavy industrial activity in East Asia associated with high population density represented in this sequence by gradations of black covering the land surface, and intense Russian forest fires in high latitudes. || ", "hits": 86 }, { "id": 30214, "url": "https://svs.gsfc.nasa.gov/30214/", "result_type": "Hyperwall Visual", "release_date": "2007-09-21T12:00:00-04:00", "title": "Population Density at Night", "description": "This image combines the Earth’s Gridded Population of the World, version 3 (GPWv3) data from 2000 with Defense Meteorological Satellite Program (DMSP) night-lights data to show the distribution of human population across the globe, including estimates to 2015. The map is colored to show the number of persons per square kilometer, from dark blue (1 person) to yellow (10,000 people). The blue-to-yellow color scale was desaturated proportional to the amount of night-lights (i.e., the color was made whiter where there were more lights). The brightest areas are generally the most urbanized but not necessarily the most populated. A comparison between the U.S. and India shows a more dense population in India but more lights in the U.S. Other patterns of distribution are also visible. For example, most major cities are along coastlines, near rivers, or near transportation networks. GPWv3 was produced by the Center for International Earth Science Information Network of the Earth Institute at Columbia University using population data from 2000.Gridded Population of the World, version 3 (GPWv3) is one of the latest developments in the rendering of human populations in a common geo-referenced framework, produced by the Center for International Earth Science Information Network (CIESIN) of the Earth Institute at Columbia University. GPWv3 depicts the distribution of human population across the globe. It is the most detailed version of GPW to date with more than three times the amount of data as version 2, and includes population estimates to 2015. Developed between 2003 and 2005, GPWv3 provides globally consistent and spatially explicit human population information and data for use in research, policy-making, and communications. || ", "hits": 171 }, { "id": 2912, "url": "https://svs.gsfc.nasa.gov/2912/", "result_type": "Visualization", "release_date": "2005-05-16T12:00:00-04:00", "title": "Population Density of the World, 1990-2015 (WMS)", "description": "This animation shows the population density of the world in the years 1990, 1995, 2000, as well as a population density estimated for the year 2015. These figures have been adjusted to match United Nations totals. The most dramatic differences in population are not readily visible in this animation because they are located in cities. The maximum population density in 1990 was about 79,000 people per square kilometer, while the estimated maximum population density in 2015 will be about 236,000 people per square kilometer. Developing areas in Africa, Latin America, and Asia change the most visibly. || ", "hits": 170 }, { "id": 2707, "url": "https://svs.gsfc.nasa.gov/2707/", "result_type": "Visualization", "release_date": "2003-11-03T12:00:00-05:00", "title": "Multisensor Fire Observations", "description": "From space, we can understand fires in ways that are impossible from the ground. New Earth-observing satellites capture the significant impact of fires on our planet. In this animation of fires around the globe in 2002, each red dot marks a new fire. Dots change color to yellow after a few days and to black when fires burn out. From brush fires in Africa to forest fires in North America, satellites are locating every significant fire on Earth to within one kilometer. In the summer and fall burning seasons, particularly destructive fires occurred in Colorado, Arizona, and Oregon. || ", "hits": 25 }, { "id": 2806, "url": "https://svs.gsfc.nasa.gov/2806/", "result_type": "Visualization", "release_date": "2003-11-03T12:00:00-05:00", "title": "Multisensor Fire Observations without Labels", "description": "From space, we can understand fires in ways that are impossible from the ground. New Earth-observing satellites capture the significant impact of fires on our planet. In this animation of fires around the globe in 2002, each red dot marks a new fire. Dots change color to yellow after a few days and to black when fires burn out. From brush fires in Africa to forest fires in North America, satellites are locating every significant fire on Earth to within one kilometer. In the summer and fall burning seasons, particularly destructive fires occurred in Colorado, Arizona, and Oregon. This animation of remote sensing observations of fires and other related data was chosen as part of the SIGGRAPH 2003 Computer Animation Theater. (The only difference was that the SIGGRAPH version had shorter credits.) || ", "hits": 33 } ] }