{ "count": 65, "next": null, "previous": null, "results": [ { "id": 14982, "url": "https://svs.gsfc.nasa.gov/14982/", "result_type": "Produced Video", "release_date": "2026-02-27T11:00:00-05:00", "title": "Deserts of Africa and the Middle East", "description": "Deserts of North Africa and the Middle East || Africa-Asia_HYPERWALL_PRINT.jpg (1280x720) [1.9 MB] || Africa-Asia_HYPERWALL_Thumb.jpg (1280x720) [1.9 MB] || Africa-Asia_HYPERWALL_Thumb.png (1280x720) [1.9 MB] || Africa-Asia_HYPERWALL_SearchWeb.jpg (1280x720) [1.9 MB] || Africa-Asia_HYPERWALL_1080.webm (1920x1080) [21.4 MB] || Africa-Asia_HYPERWALL_1080.mp4 (1920x1080) [222.6 MB] || Africa-Asia_HYPERWALL_6K.webm (5760x3240) [7.2 MB] || Africa-MiddleEast_HYPERWALL_4K.mp4 (3840x2160) [1.1 GB] || Africa-Asia_HYPERWALL_6K.mp4 (5760x3240) [5.0 GB] || ", "hits": 251 }, { "id": 31242, "url": "https://svs.gsfc.nasa.gov/31242/", "result_type": "Hyperwall Visual", "release_date": "2024-09-23T00:00:00-04:00", "title": "Landsat 8 and 9 Composite of Rwanda", "description": "Landsat 8 and Landsat 9 scenes from July 17, 18 and 25, 2023 are combined to make a relatively cloud free mosaic of Rwanda || ", "hits": 17 }, { "id": 14410, "url": "https://svs.gsfc.nasa.gov/14410/", "result_type": "Produced Video", "release_date": "2023-09-13T10:00:00-04:00", "title": "NASA Joins Jane Goodall to Conserve Chimp Habitats", "description": "Complete transcript available. || Jane_Goodall_fullvideo_FINAL.00001_print.jpg (1024x576) [225.0 KB] || Jane_Goodall_fullvideo_FINAL.00001_searchweb.png (320x180) [123.8 KB] || Jane_Goodall_fullvideo_FINAL.00001_web.png (320x180) [123.8 KB] || Jane_Goodall_fullvideo_FINAL.00001_thm.png (80x40) [8.1 KB] || Jane_Goodall_fullvideo_FINAL.en_US.srt [10.7 KB] || Jane_Goodall_fullvideo_FINAL.en_US.vtt [10.2 KB] || Jane_Goodall_fullvideo_FINAL.mp4 (3840x2160) [4.3 GB] || ", "hits": 71 }, { "id": 5014, "url": "https://svs.gsfc.nasa.gov/5014/", "result_type": "Visualization", "release_date": "2022-08-17T00:00:00-04:00", "title": "Drought in the Horn of Africa", "description": "According to a July 29 2022 report from the International Food Security and Nutrition Working Group, the worst drought conditions in 70 years across the Horn of Africa have more than 16 million people coping with a shortage of drinking water. Yields of key crops are down for the third year in a row, milk production is in decline, and more than 9 million livestock animals have been lost due to a lack of water and suitable forage land. At the same time, regional conflicts, COVID-19, locusts, and the Ukraine War have caused price spikes and shortages of basic commodities. An estimated 18 to 21 million people now \"face high levels of acute food insecurity\" in Ethiopia, Kenya, and Somalia.These animations depict root zone and surface soil moisture observations and forecasts from the NASA Hydrological Forecast and Analysis System (NHyFAS). Reds depict areas with soil moisture percentages below the average, while blues reflect areas that are above average (often due to passing storms). The first 27 seconds of the animation show soil moisture from August 2020 through June 2022. The final 10 seconds show forecasts for July through December 2022, including the next rainy season. Root zone moisture is critical for long term crop growth. New seedlings are mostly dependent on surface water, but then as plants grow and sink deeper roots, they are sustained by moisture in the top layer of the soil. || ", "hits": 210 }, { "id": 4836, "url": "https://svs.gsfc.nasa.gov/4836/", "result_type": "Visualization", "release_date": "2021-03-11T10:00:00-05:00", "title": "Liberia Land Use and Ecosystem Extent", "description": "Land Use, Libera || top.00660_print.jpg (1024x576) [220.1 KB] || top.00660_searchweb.png (320x180) [105.8 KB] || top.00660_thm.png (80x40) [7.2 KB] || top.mp4 (1920x1080) [42.8 MB] || top.webm (1920x1080) [2.3 MB] || top.mp4.hwshow [169 bytes] || ", "hits": 59 }, { "id": 13736, "url": "https://svs.gsfc.nasa.gov/13736/", "result_type": "Produced Video", "release_date": "2020-10-16T11:00:00-04:00", "title": "NASA Supercomputing Study Breaks Ground for Tree Mapping, Carbon Research", "description": "Complete transcript available.This video is also available on our YouTube channel. || TreeMapping_Thumbnail.png (1920x1080) [3.4 MB] || TreeMapping_Thumbnail_print.jpg (1024x576) [208.9 KB] || TreeMapping_Thumbnail_searchweb.png (320x180) [120.6 KB] || TreeMapping_Thumbnail_thm.png (80x40) [7.6 KB] || TreeMapping_FINAL.mp4 (1920x1080) [79.8 MB] || TreeMapping_FINAL.webm (1920x1080) [9.7 MB] || TreeMapping_FINAL.en_US.srt [1.6 KB] || TreeMapping_FINAL.en_US.vtt [1.6 KB] || TreeMapping_FINAL.mov (1920x1080) [1.1 GB] || ", "hits": 16 }, { "id": 4162, "url": "https://svs.gsfc.nasa.gov/4162/", "result_type": "Visualization", "release_date": "2014-04-23T10:00:00-04:00", "title": "Drought may take a toll on Congo Rainforest, NASA Satellites Show", "description": "A new analysis of NASA satellite data shows that Africa's Congo rainforest, the second-largest tropical rainforest in the world, has undergone a large-scale decline in greenness over the past decade.The study, lead by Liming Zhou of University at Albany, State University of New York, shows that between 2000 and 2012, the decline affected an increasing amount of forest area and intensified. The research, published April 23 in Nature, is one of the most comprehensive observational studies to explore the effects of long-term drought on Congolese rainforests using several independent satellite sensors.Scientists use the satellite-derived \"greenness\" of forest regions as one indicator of a forest's health. While this study looks specifically at the impact of a persistent drought in the Congo region since 2000, researchers say that a continued drying trend might alter the composition and structure of the Congo rainforest, affecting its biodiversity and carbon storage.\"It's important to understand these changes because most climate models predict that tropical forests may be under stress due to increasing severe water shortages in a warmer and drier 21st century climate,\" Zhou said.Previous research used satellite-based measurements of vegetation greenness to investigate changes in the Amazon rainforest, notably the effects of severe short-term droughts in 2005 and 2010. Until now, little attention has been paid to African rainforests, where ground measurements are even sparser than in the Amazon and where droughts are less severe but last longer.To clarify the impact of long-term drought on the Congo rainforest, Zhou and colleagues set out to see if they could detect a trend in a satellite measure of vegetation greenness called the Enhanced Vegetation Index. This measure is developed from data produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Terra satellite. The scientists focused their analysis on intact, forested regions in the Congo basin during the months of April, May and June each year - the first of the area's two peak rainy and growing seasons each year.The study found a gradually decreasing trend in Congo rainforest greenness, sometimes referred to as \"browning,\" suggesting a slow adjustment to the long-term drying trend. This is in contrast to the more immediate response seen in the Amazon, such as large-scale tree mortality, brought about by more episodic drought events.The browning of the forest canopy is consistent with observed decreases in the amount of water available to plants, whether that's in the form of rainfall, water stored in the ground, water in near-surface soils, or water within the vegetation. || ", "hits": 75 }, { "id": 4076, "url": "https://svs.gsfc.nasa.gov/4076/", "result_type": "Visualization", "release_date": "2013-05-15T00:00:00-04:00", "title": "Landsat-8 Long Swath", "description": "Landsat-8 launched February 11th, 2013. This visualization shows one of the first full swaths of data taken on April 19th, 2013, only one week after Landsat-8 ascended to its final altitude of 438 miles (705 km). || ", "hits": 99 }, { "id": 11223, "url": "https://svs.gsfc.nasa.gov/11223/", "result_type": "Produced Video", "release_date": "2013-05-07T10:00:00-04:00", "title": "Narrated Distributed Water Balance of the Nile Basin", "description": "This visualization shows how satellite data and NASA models are being applied to study the hydrology of the Nile basin. It is a narrated version of the original video, which can be found, along with further documentation, in entry #4044. || ", "hits": 31 }, { "id": 4044, "url": "https://svs.gsfc.nasa.gov/4044/", "result_type": "Visualization", "release_date": "2013-02-27T00:00:00-05:00", "title": "The Distributed Water Balance of the Nile Basin", "description": "This visualization shows how satellite data and NASA models are being applied to study the hydrology of the Nile basin. The Tropical Rainfall Measurement Mission (TRMM) Multisensor Precipitation Analysis (TMPA) provides three-hourly estimates of rainfall rate across much of the globe. Here we see the seasonal cycle of monthly precipitation derived from TMPA for Africa, including the Nile Basin. The annual migration of the Intertropical Convergence Zone (ITCZ) from the Nile Equatorial Lakes region around Lake Victoria, source of the White Nile, northward into Sudan and the highlands of Ethiopia, headwaters of the Blue Nile, and back is evident in the seasonal cycle in precipitation. This precipitation cycle drives flow through the Nile River system. The Nile basin, however, is intensely evaporative, and the majority of the water that falls as rain leaves the basin as evaporation rather than river flow—either from the humid headwaters regions or from large reservoirs and irrigation developments in Egypt and Sudan. The Atmosphere Land Exchange Inverse (ALEXI) evapotranspiration product, developed by USDA scientists, uses satellite data to map daily evapotranspiration across the entire Nile basin, providing unprecedented information on water consumption. The balance of rainfall and evapotranspiration can be seen in seasonal patterns of soil moisture, as simulated by the NASA Nile Land Data Assimilation System (LDAS), which merges satellite information with a physically-based land surface model to simulate variability in soil moisture—a critical variable for rainfed agriculture and natural ecosystems. Finally, the twin satellites of the Gravity Recovery and Climate Experiment (GRACE) can be used to monitor variability in total water storage, including surface water, soil moisture, and groundwater. The annual cycle in GRACE estimates of water storage anomalies clearly shows the seasonal movement of water storage due to precipitation patterns and the movement of surface waters from headwaters regions into the wetlands of South Sudan and the reservoirs of the lower Nile basin.The Nile is the longest river in the world and its basin is shared by 11 countries. Reliable, spatially distributed estimates of hydrologic storage and fluxes can provide critical information for water managers contending with multiple resource demands, a variable and changing climate, and the risk of damaging floods and droughts. NASA observations and modeling systems offer unique capabilities to meet these information needs. || ", "hits": 94 }, { "id": 11004, "url": "https://svs.gsfc.nasa.gov/11004/", "result_type": "Produced Video", "release_date": "2012-06-18T09:00:00-04:00", "title": "Mapping The Future With Landsat", "description": "Many non-profits are using Landsat as a tool to identify and protect areas that are important for conservation. This video shows how The African Wildlife Foundation (AWF) has used Landsat in the Democratic Republic of the Congo to protect a wildlife corridor in the Maringa Lopori Wanga (MLW) region. This area is located in the northern part of the Democratic Republic of the Congo (DRC) immediately south of the Congo River. Within its borders are two major reserves: The Lomako-Yokokala Faunal Reserve and the Luo Scientific Reserve. Wildlife travels between these two reserves via a natural wildlife corridor. With Landsat, the AWF identified this corridor as a critical area for conservation and then began working with the DRC government and local communities to map the region. This process has had and will have significant impact on land use planning and zoning in the Democratic Republic of the Congo. || ", "hits": 27 }, { "id": 3960, "url": "https://svs.gsfc.nasa.gov/3960/", "result_type": "Visualization", "release_date": "2012-06-15T00:00:00-04:00", "title": "Saving the Maringa Lopori Wanga Wildlife Corridor", "description": "Maringa Lopori Wanga (MLW) is a region in the northern part of the Democratic Republic of the Congo (DRC) immediately south of the Congo River. Within its borders are two major reserves: The Lomako-Yokokala Faunal Reserve and the Luo Scientific Reserve. Wildlife travels between these two reserves via a natural wildlife corridor. However, a main road bisects this wildlife corridor between the two reserves, along which numerous villages have been established over time. If the corridor is to remain open, villagers living along the route need to control sprawl. This is where scientists have joined in to help, by providing detailed satellite imagery of the area, allowing the people of the MLW region to more accurately zone their land for agricultural expansion. By providing accurate satellite zoning maps, the villages can still thrive and the wildlife corridor can remain open, which benefits both the people and the wildlife of this region of the DRC.Part of NASA's Landsat program mission is to provide tools to assist with global growth and urbanization planning. NASA's Land-Cover and Land-Use Change Program (LCLUC) uses Landsat data to develop socially relevant interdisciplinary science that can be applied to natural resource management questions, starting with agricultural land use change. More information on the varied use of Landsat data can be found at http://landsat.gsfc.nasa.gov/about/appl_matrix.html A fully narrated reporter package of this story, incorporating this element, can be seen here. || ", "hits": 23 }, { "id": 3961, "url": "https://svs.gsfc.nasa.gov/3961/", "result_type": "Visualization", "release_date": "2012-06-15T00:00:00-04:00", "title": "Zoom into the Democratic Republic of the Congo (DRC)", "description": "This scene setting visualization zooms down to the jungles of the Democratic Republic of the Congo (DRC). It was developed in support of the Mapping the Future With Landsat story. || ", "hits": 76 }, { "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": 35 }, { "id": 3855, "url": "https://svs.gsfc.nasa.gov/3855/", "result_type": "Visualization", "release_date": "2011-10-01T00:00:00-04:00", "title": "Clouds over Africa", "description": "This animation is a beauty shot of cloud model output over North America. The clouds are derived from the Goddard Earth Observing System Model, Version 5 (GEOS-5). GEOS-5 is a system of models integrated using the Earth System Modeling Framework and used to help refine atmospheric weather models.The lighting of this scene is completely artistic and not scientifically accurate. If accurate lighting were used the diurnal effect would pulse across the globe approximately every 90 frames (3 seconds when played at 30 fps). The slow strobing would have been undesireable for the intended purpose of this animation, which is to highlight the cloud model output. || ", "hits": 32 }, { "id": 3859, "url": "https://svs.gsfc.nasa.gov/3859/", "result_type": "Visualization", "release_date": "2011-09-12T00:00:00-04:00", "title": "Clouds over Florida and Cuba", "description": "This animation is a beauty shot of cloud model output over North America. The clouds are derived from the Goddard Earth Observing System Model, Version 5 (GEOS-5). GEOS-5 is a system of models integrated using the Earth System Modeling Framework and used to help refine atmospheric weather models.The lighting of this scene is completely artistic and not scientifically accurate. If accurate lighting were used the diurnal effect would pulse across the globe approximately every 90 frames (3 seconds when played at 30 fps). The slow strobing would have been undesireable for the intended purpose of this animation, which is to highlight the cloud model output. || ", "hits": 16 }, { "id": 3860, "url": "https://svs.gsfc.nasa.gov/3860/", "result_type": "Visualization", "release_date": "2011-09-12T00:00:00-04:00", "title": "Clouds over North America", "description": "This animation is a beauty shot of cloud model output over North America. The clouds are derived from the Goddard Earth Observing System Model, Version 5 (GEOS-5). GEOS-5 is a system of models integrated using the Earth System Modeling Framework and used to help refine atmospheric weather models.The lighting of this scene is completely artistic and not scientifically accurate. If accurate lighting were used the diurnal effect would pulse across the globe approximately every 90 frames (3 seconds when played at 30 fps). The slow strobing would have been undesireable for the intended purpose of this animation, which is to highlight the cloud model output. || ", "hits": 13 }, { "id": 3861, "url": "https://svs.gsfc.nasa.gov/3861/", "result_type": "Visualization", "release_date": "2011-09-12T00:00:00-04:00", "title": "Clouds over South America", "description": "This animation is a beauty shot of cloud model output over North America. The clouds are derived from the Goddard Earth Observing System Model, Version 5 (GEOS-5). GEOS-5 is a system of models integrated using the Earth System Modeling Framework and used to help refine atmospheric weather models.The lighting of this scene is completely artistic and not scientifically accurate. If accurate lighting were used the diurnal effect would pulse across the globe approximately every 90 frames (3 seconds when played at 30 fps). The slow strobing would have been undesireable for the intended purpose of this animation, which is to highlight the cloud model output. || ", "hits": 23 }, { "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": 22 }, { "id": 3039, "url": "https://svs.gsfc.nasa.gov/3039/", "result_type": "Visualization", "release_date": "2004-10-29T12:00:00-04:00", "title": "ICESat Cloud Walls (scripted camera path)", "description": "This is an animation showing data from ICESat's Geoscience Laser Altimeter System (GLAS). Cloud data can be seen over about 15 orbits on October 6, 2003. The data are initially laid out in the order that is was collected followed by continued movement around the scene. This version of the animation starts with the full globe, moves south to Antarctica, over the pole, then north to Africa, around the world near the equator and finally to the north pole. || ", "hits": 15 }, { "id": 2987, "url": "https://svs.gsfc.nasa.gov/2987/", "result_type": "Visualization", "release_date": "2004-09-10T12:00:00-04:00", "title": "Hurricane Isabel Genesis", "description": "This animation follows Hurricane Isabel (2003) from its birthplace in the Ethiopian Highlands of East Africa, across the Atlantic Ocean, to the United States. Atlantic hurricanes are often formed as winds over the Gulf of Aden intersect with the Ethiopian Highlands. This animation zooms into the Ethiopian Highlands and shows several storms being formed. Then, the animation dissolves in a reticle to focus in specifically on the formation of Hurricane Isabel. The reticle follows the storm across Africa and into the Atlantic. The path and intensity of Hurricane Isabel is depicted by a colored path. Blue represents the genesis of the storm. Green is a Tropical Depression where winds are less than 39 miles per hour. Yellow is a Tropical Storm where winds are between 39 and 73 miles per hour. Red is a category 1 hurricane where winds are between 74 and 95 miles per hour. Light Red is a category 2 hurricane with winds between 96 and 110 miles per hour. Magenta is a category 3 hurricane with winds between 111 and 130 miles per hour. Light magenta is a category 4 hurricane with winds between 131 and 154 miles per hour. White represents a category 5 hurricane where winds are greater than 155 miles per hour. Note how Isabel gains size and speed over the warm waters of the Atlantic. || ", "hits": 43 }, { "id": 2890, "url": "https://svs.gsfc.nasa.gov/2890/", "result_type": "Visualization", "release_date": "2004-02-10T12:00:00-05:00", "title": "African Fires During 2002 (WMS)", "description": "This animation shows fire activity in Africa from January 1, 2002 to December 31, 2002. The fires are shown as tiny particles with each particle depicting the geographic region in which fire was detected. The color of a particle represents the number of days since a sizable amount of fire was detected in that region, with red representing less than 20 days, orange representing 20 to 40 days, yellow representing 40 to 60 days, and gray to black representing more than 60 days. This data was measured by the MODIS instrument on the Terra satellite. MODIS detects fires by measuring the brightness temperature of a region in several frequency bands and looking for hot spots where this temperature is greater than the surrounding region. || ", "hits": 21 }, { "id": 2706, "url": "https://svs.gsfc.nasa.gov/2706/", "result_type": "Visualization", "release_date": "2003-03-06T12:00:00-05:00", "title": "African Dust Sequence", "description": "A 48-hour dust storm on March 1 and 2, 2003, is responsible for a very large dust transport over the Atlantic Ocean from March 2 through March 6, 2003. || ", "hits": 19 }, { "id": 2542, "url": "https://svs.gsfc.nasa.gov/2542/", "result_type": "Visualization", "release_date": "2002-09-05T12:00:00-04:00", "title": "Fires over Africa during 2001 and 2002", "description": "This animation shows fire activity over Africa from 8/21/2001 to 8/20/2002. The fires are shown as tiny particles with each particle depicting the site at which a fire was detected. Daily fires are displayed at a rate of 10 days per second. The fire particles fade over 1.7 seconds and change color as they age from red to orange, yellow and gray. || ", "hits": 2740 }, { "id": 2543, "url": "https://svs.gsfc.nasa.gov/2543/", "result_type": "Visualization", "release_date": "2002-09-05T12:00:00-04:00", "title": "Fires over Africa during 2001 and 2002 with Clock", "description": "This animation shows fire activity over Africa from 8/21/2001 to 8/20/2002. The fires are shown as tiny particles with each particle depicting the site at which a fire was detected. Daily fires are displayed at a rate of 10 days per second. The fire particles fade over 1.7 seconds and change color as they age from red to orange, yellow and gray. A clock inset indicates the date. || ", "hits": 6 }, { "id": 2353, "url": "https://svs.gsfc.nasa.gov/2353/", "result_type": "Visualization", "release_date": "2002-01-18T12:00:00-05:00", "title": "Lake Kivu Zoom-in", "description": "Zoom down to Lake Kivu, Rwanda, Africa. The northern tip of this lake is considered to be the most likely spot for the next deadly gas eruption (similar to the 1984 and 1986 eruptions at Lake Monoun and Lake Nyos respectively) due to its proximity to volcanically active areas to the north. For more information on similar gas eruptions please see animations #2346 and #2348. || ", "hits": 23 }, { "id": 2354, "url": "https://svs.gsfc.nasa.gov/2354/", "result_type": "Visualization", "release_date": "2002-01-18T12:00:00-05:00", "title": "Lake Kivu Zoom-out", "description": "Zoom out from Lake Kivu, Rwanda, Africa to a global view of the African continent. (This animation is a reverse treatment of animation #2353.) || Animation starting at Lake Kivu which then zooms out to take in a global view of Africa. || a002354.00005_print.png (720x480) [603.7 KB] || kivuout_pre.jpg (320x238) [10.0 KB] || a002354.webmhd.webm (960x540) [2.5 MB] || a002354.dv (720x480) [44.6 MB] || kivuout.mpg (352x240) [2.2 MB] || ", "hits": 11 }, { "id": 2335, "url": "https://svs.gsfc.nasa.gov/2335/", "result_type": "Visualization", "release_date": "2002-01-15T12:00:00-05:00", "title": "Lac de Mbakaou Zoom-in", "description": "Zoom in to Lake Mbakaou, Cameroon, Africa. || Animation starting with a global view of Africa zooming down to 30 m. Landsat-7 data mapped over a 1 km. GTOPO30 Digital Elevation Map (DEM) of Lake Mbakaou. || a002335.00005_print.png (720x480) [478.5 KB] || mbakin_pre.jpg (320x238) [7.3 KB] || a002335.webmhd.webm (960x540) [3.0 MB] || a002335.dv (720x480) [42.3 MB] || mbakin.mpg (352x240) [2.3 MB] || ", "hits": 24 }, { "id": 2336, "url": "https://svs.gsfc.nasa.gov/2336/", "result_type": "Visualization", "release_date": "2002-01-15T12:00:00-05:00", "title": "Lac de Mbakaou Zoom-out", "description": "Zoom out from Lake Mbakaou, Cameroon, Africa to a global view of the African continent. This animation is a reverse treatment of animation #2335. || Animation starting at Lake Mbakaou which then zooms out to take in a global view of the African continent. || a002336.00005_print.png (720x480) [745.9 KB] || mbakout_pre.jpg (320x238) [13.7 KB] || a002336.webmhd.webm (960x540) [2.7 MB] || a002336.dv (720x480) [42.9 MB] || mbakout.mpg (352x240) [2.3 MB] || ", "hits": 18 }, { "id": 2337, "url": "https://svs.gsfc.nasa.gov/2337/", "result_type": "Visualization", "release_date": "2002-01-15T12:00:00-05:00", "title": "Bamenjing Reservoir Zoom-in", "description": "Zoom in to Bamenjing Reservoir, Cameroon, Africa. || Animation starting with a global view of Africa zooming down to 30 m. Landsat-7 data mapped over a 1 km. GTOPO30 Digital Elevation Map (DEM) of Bamenjing, Reservoir. || a002337.00005_print.png (720x480) [487.5 KB] || bamenjingin_pre.jpg (320x238) [7.4 KB] || a002337.webmhd.webm (960x540) [3.3 MB] || a002337.dv (720x480) [43.5 MB] || bamenjingin.mpg (352x240) [2.3 MB] || ", "hits": 10 }, { "id": 2338, "url": "https://svs.gsfc.nasa.gov/2338/", "result_type": "Visualization", "release_date": "2002-01-15T12:00:00-05:00", "title": "Bamenjing Reservoir Zoom-out", "description": "Zoom out from Bamenjing, Cameroon, Africa to a global view of the African continent.This animation is a reverse treatment of animation #2337. || ", "hits": 3 }, { "id": 2339, "url": "https://svs.gsfc.nasa.gov/2339/", "result_type": "Visualization", "release_date": "2002-01-15T12:00:00-05:00", "title": "Moving from Lac de Mbakaou to Bemanjing Reservoir", "description": "Fly over of 3D terrain from Lake Mbakaou, Cameroon, Africa to Bamenjing Reservoir. || 3D terrain animation fly over from Lake Mbakaou to Bamenjing Reservoir || a002339.00005_print.png (720x480) [746.2 KB] || mbak2res_thm.png (80x40) [6.4 KB] || mbak2res_pre.jpg (320x238) [13.6 KB] || mbak2res_pre_searchweb.jpg (320x180) [90.1 KB] || a002339.webmhd.webm (960x540) [1.5 MB] || a002339.dv (720x480) [20.6 MB] || mbak2res.mpg (352x240) [1.3 MB] || ", "hits": 4 }, { "id": 2340, "url": "https://svs.gsfc.nasa.gov/2340/", "result_type": "Visualization", "release_date": "2002-01-15T12:00:00-05:00", "title": "Moving from Bamenjing Reservoir to Lac de Mbakaou", "description": "3D terrain fly over starting at Bamenjing Reservoir, Cameroon, Africa going to Lake Mbakaou. (This animation is a reverse treatment of animation #2339.) || ", "hits": 11 }, { "id": 2346, "url": "https://svs.gsfc.nasa.gov/2346/", "result_type": "Visualization", "release_date": "2002-01-10T12:00:00-05:00", "title": "Lake Monoun Zoom-in", "description": "On August 8, 1984 37 people from the villages surrounding Lake Monoun, Cameroon, Africa were found mysteriously dead. First reports pointed to man made terrorist activity but it soon became clear that this was a natural event; somehow or other the lake had exploded, releasing huge volumes of a poisonous, invisible gas. || ", "hits": 68 }, { "id": 2347, "url": "https://svs.gsfc.nasa.gov/2347/", "result_type": "Visualization", "release_date": "2002-01-10T12:00:00-05:00", "title": "Lake Monoun Zoom-out", "description": "Zoom out from Lake Monoun, Cameroon, Africa to a global view of the African continent. (This animation is a reverse treatment of animation #2346.) || Animation starting at Lake Monoun which then zooms out to take in a global view of Africa. || a002347.00005_print.png (720x480) [721.6 KB] || monounout_pre.jpg (320x238) [12.5 KB] || a002347.webmhd.webm (960x540) [2.8 MB] || a002347.dv (720x480) [44.6 MB] || monounout.mpg (352x240) [2.4 MB] || ", "hits": 17 }, { "id": 2348, "url": "https://svs.gsfc.nasa.gov/2348/", "result_type": "Visualization", "release_date": "2002-01-10T12:00:00-05:00", "title": "Lake Nyos Zoom-in", "description": "On August 21, 1986 (two years after the gas explosion of Lake Monoun. See animation #2346 for more details), Lake Nyos in Cameroon, Africa, also exploded. The resulting gas emissions killed over 1,700 people and livestock in neighboring villages. The deadly effects were seen as far as 25 kilometers away. || ", "hits": 38 }, { "id": 2349, "url": "https://svs.gsfc.nasa.gov/2349/", "result_type": "Visualization", "release_date": "2002-01-10T12:00:00-05:00", "title": "Lake Nyos Zoom-out", "description": "Zoom out from Lake Nyos, Cameroon, Africa to a global view of the African continent. (This animation is a reverse treatment of animation #2348.) || ", "hits": 26 }, { "id": 2350, "url": "https://svs.gsfc.nasa.gov/2350/", "result_type": "Visualization", "release_date": "2002-01-10T12:00:00-05:00", "title": "Moving from Lake Monoun to Lake Nyos", "description": "Lake Monoun and Lake Nyos are known as the killer lakes of Cameroon, Africa. In 1984 Lake Monoun exploded, emitting a deadly gas. Almost exactly two years later a similar explosion happened at Lake Nyos; although this time the death toll was much higher (over 1,700 people and livestock). Combined, the gas emissions from these lakes killed over 1,800 people and livestock in neighboring villages. || ", "hits": 42 }, { "id": 2315, "url": "https://svs.gsfc.nasa.gov/2315/", "result_type": "Visualization", "release_date": "2001-12-20T12:00:00-05:00", "title": "Leaf Area Index for Africa September, 2000, through May, 2001", "description": "MODIS' observations also allow scientists to track two 'vital signs' of Earth's vegetation. At Boston University, a team of researchers is using MODIS data to create global estimates of the green leaf area of Earth's vegetation and how much sunlight the leaves are absorbing. Called LAI, for 'Leaf Area Index,' and FPAR, for 'Fraction of absorbed Photosynthetically Active Radiation,' both pieces of information are necessary for understanding how sunlight interacts with the Earth's vegetated surfaces-from the top layer, called the canopy, through the understory vegetation, and down to the ground. || ", "hits": 25 }, { "id": 2316, "url": "https://svs.gsfc.nasa.gov/2316/", "result_type": "Visualization", "release_date": "2001-12-20T12:00:00-05:00", "title": "Fraction of Photosynthetically Active Radiation for Africa September, 2000, through May, 2001", "description": "MODIS' observations also allow scientists to track two 'vital signs' of Earth's vegetation. At Boston University, a team of researchers is using MODIS data to create global estimates of the green leaf area of Earth's vegetation and how much sunlight the leaves are absorbing. Called LAI, for 'Leaf Area Index,' and FPAR, for 'Fraction of absorbed Photosynthetically Active Radiation,' both pieces of information are necessary for understanding how sunlight interacts with the Earth's vegetated surfaces-from the top layer, called the canopy, through the understory vegetation, and down to the ground. || ", "hits": 11 }, { "id": 2318, "url": "https://svs.gsfc.nasa.gov/2318/", "result_type": "Visualization", "release_date": "2001-12-20T12:00:00-05:00", "title": "United States EVI from Summer 2000 to Spring 2001", "description": "Traditional satellite-based mapping of vegetation vigor and amount is based on the way vegetation interacts with red and infrared light. Occasionally, however, those two signals are not enough. MODIS measures light reflected from Earth at a variety of wavelengths, and the Arizona researchers incorporate the additional information into their Enhanced Vegetation Index (EVI). The EVI has increased sensitivity within very dense vegetation, and it has built-in corrections for several factors that can interfere with the satellite-based vegetation mapping, like smoke and background noise caused by light reflecting off soil. The bi-weekly and monthly vegetation index maps have wide usability by biologists, natural resources managers, and climate modelers. They can track naturally occurring fluctuations in vegetation, such as seasonal changes, as well as those that result from land use change, such as deforestation. The EVI can also monitor changes in vegetation resulting from climate change, such as expansion of deserts or extension of growing seasons. || ", "hits": 24 }, { "id": 2257, "url": "https://svs.gsfc.nasa.gov/2257/", "result_type": "Visualization", "release_date": "2001-06-14T12:00:00-04:00", "title": "Aerosols from Nimbus 7 TOMS: Transatlantic Dust Event in 1983", "description": "Saharan dust storms raise dust that is carried in the upper atmosphere across the Atlantic Ocean. That dust can land as far west as the Caribbean and the Americas. This dust can carry potentially hazardous bacteria and fungi. || ", "hits": 7 }, { "id": 2258, "url": "https://svs.gsfc.nasa.gov/2258/", "result_type": "Visualization", "release_date": "2001-06-14T12:00:00-04:00", "title": "Aerosols from Nimbus 7 TOMS: Transatlantic Dust Event in 1983 (with Dates)", "description": "Saharan dust storms raise dust that is carried in the upper atmosphere across the Atlantic Ocean. That dust can land as far west as the Caribbean and the Americas. This dust can carry potentially hazardous bacteria and fungi. || ", "hits": 15 }, { "id": 2259, "url": "https://svs.gsfc.nasa.gov/2259/", "result_type": "Visualization", "release_date": "2001-06-14T12:00:00-04:00", "title": "Aerosols from Earth Probe TOMS: Transatlantic Dust Event in July 2000", "description": "Saharan dust storms raise dust that is carried in the upper atmosphere across the Atlantic Ocean. That dust can land as far west as the Caribbean and the Americas. This dust can carry potentially hazardous bacteria and fungi. || ", "hits": 7 }, { "id": 2260, "url": "https://svs.gsfc.nasa.gov/2260/", "result_type": "Visualization", "release_date": "2001-06-14T12:00:00-04:00", "title": "Aerosols from Earth Probe TOMS: Transatlantic Dust Event in July 2000 (with Dates)", "description": "Saharan dust storms raise dust that is carried in the upper atmosphere across the Atlantic Ocean. That dust can land as far west as the Caribbean and the Americas. This dust can carry potentially hazardous bacteria and fungi. || ", "hits": 8 }, { "id": 2137, "url": "https://svs.gsfc.nasa.gov/2137/", "result_type": "Visualization", "release_date": "2001-05-10T12:00:00-04:00", "title": "West Africa Dust Storms", "description": "On the Coast of West Africa, dust storms are a common occurrance, if you take a look at this one, its about the size of Spain. SeaWIFS returned this dramatic close-up view of a vast, developing cloud of Saharan desert dust blowing from northwest Africa a thousand miles or more out over the Atlantic Ocean. Aerosol particles larger than about 1 micrometer in size are produced by windblown dust and other sources. After formation, the aerosols are mixed and transported by atmospheric motions and are primarily removed by cloud and precipitation processes. From space-based vantage points, other satellite images have also revealed storms that transport massive quantities of fine sand and dust across Earth's oceans. || ", "hits": 29 }, { "id": 2075, "url": "https://svs.gsfc.nasa.gov/2075/", "result_type": "Visualization", "release_date": "2001-03-12T13:30:00-05:00", "title": "Cyclone Dera", "description": "View of Cyclone Dera in the Mozambique Channel || Cyclone Dera between Madagascar and the East coast of Africa (March 11, 2001) || a002075.00170_print.png (720x480) [457.1 KB] || a002075_pre.jpg (320x266) [11.9 KB] || a002075.webmhd.webm (960x540) [2.9 MB] || a002075.dv (720x480) [41.2 MB] || a002075.mp4 (640x480) [2.2 MB] || a002075.mpg (320x240) [595.7 KB] || ", "hits": 29 }, { "id": 2064, "url": "https://svs.gsfc.nasa.gov/2064/", "result_type": "Visualization", "release_date": "2001-02-26T12:00:00-05:00", "title": "Lake Chad Evaporation 1963 to 1997", "description": "Located on the edge of the Sahara and bordering four countries—Chad, Cameroon, Nigeria, and Niger—the immense area of this land locked lake has nearly disappeared in recent years. Persistent drought has caused the lake to drop from its former sixth place position in the list of world's largest lakes; it is now one tenth its former size.The basin of the lake is not naturally deep, so the surface area of the lake tended to spread out, keeping the total depth to little more 23 feet (7 meters). In recent years, rainfall patterns have begun to change, and tributaries to Lake Chad have not been refilling the basin as rapidly as they used to. The lush, productive flora and fauna fed by the wetlands of the shallow lake have suffered as a result.This has led to significant changes for various communities of people that live in the vicinity of the Lake. While for some the now exposed lake bed has enabled new land to be cultivated, much of the available fresh water that might have been used for irrigation is no longer dependable. As rainfall rates appear to be declining year after year, people living nearby develop even greater dependence on the lake, draining it even faster. || ", "hits": 73 }, { "id": 2065, "url": "https://svs.gsfc.nasa.gov/2065/", "result_type": "Visualization", "release_date": "2001-02-26T12:00:00-05:00", "title": "Lake Chad Evaporation 1973 to 1987", "description": "Located on the edge of the Sahara and bordering four countries—Chad, Cameroon, Nigeria, and Niger—the immense area of this land locked lake has nearly disappeared in recent years. Persistent drought has caused the lake to drop from its former sixth place position in the list of world's largest lakes; it is now one tenth its former size.The basin of the lake is not naturally deep, so the surface area of the lake tended to spread out, keeping the total depth to little more 23 feet (7 meters). In recent years, rainfall patterns have begun to change, and tributaries to Lake Chad have not been refilling the basin as rapidly as they used to. The lush, productive flora and fauna fed by the wetlands of the shallow lake have suffered as a result.This has led to significant changes for various communities of people that live in the vicinity of the Lake. While for some the now exposed lake bed has enabled new land to be cultivated, much of the available fresh water that might have been used for irrigation is no longer dependable. As rainfall rates appear to be declining year after year, people living nearby develop even greater dependence on the lake, draining it even faster. || ", "hits": 101 }, { "id": 2066, "url": "https://svs.gsfc.nasa.gov/2066/", "result_type": "Visualization", "release_date": "2001-02-26T12:00:00-05:00", "title": "Lake Chad 2001", "description": "Sweep of Lake Chad, February 2001.Located on the edge of the Sahara and bordering four countries—Chad, Cameroon, Nigeria, and Niger—the immense area of this land locked lake has nearly disappeared in recent years. Persistent drought has caused the lake to drop from its former sixth place position in the list of world's largest lakes; it is now one tenth its former size.The basin of the lake is not naturally deep, so the surface area of the lake tended to spread out, keeping the total depth to little more 23 feet (7 meters). In recent years, rainfall patterns have begun to change, and tributaries to Lake Chad have not been refilling the basin as rapidly as they used to. The lush, productive flora and fauna fed by the wetlands of the shallow lake have suffered as a result.This has led to significant changes for various communities of people that live in the vicinity of the Lake. While for some the now exposed lake bed has enabled new land to be cultivated, much of the available fresh water that might have been used for irrigation is no longer dependable. As rainfall rates appear to be declining year after year, people living nearby develop even greater dependence on the lake, draining it even faster. || ", "hits": 32 }, { "id": 2016, "url": "https://svs.gsfc.nasa.gov/2016/", "result_type": "Visualization", "release_date": "2000-11-15T12:00:00-05:00", "title": "Aerial View of the Madikwe Fire", "description": "This flyover occurred on August 20, 2000. The aircraft's altitude was an at 64,250 feet while acquiring the image. The flight direction on the image is from top to bottom. The aircraft heading was approximately 6.5 degrees. || ", "hits": 15 }, { "id": 1184, "url": "https://svs.gsfc.nasa.gov/1184/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Seasonal NDVI for Africa: 1981-2000 Averaged, With Month Notation", "description": "Seasonal NDVI for Africa. 1981-2000 averaged with month notation. 15 frames/month || Seasonal NDVI for Africa. || a001184.00005_print.png (720x480) [400.4 KB] || a001184_pre.jpg (320x242) [6.6 KB] || a001184_thm.png (80x40) [4.2 KB] || a001184_pre_searchweb.jpg (320x180) [40.5 KB] || a001184.webmhd.webm (960x540) [676.3 KB] || a001184.dv (720x480) [41.0 MB] || a001184.mp4 (640x480) [2.1 MB] || a001184.mpg (352x240) [1.4 MB] || ", "hits": 13 }, { "id": 1185, "url": "https://svs.gsfc.nasa.gov/1185/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Seasonal NDVI for Africa: 1981-2000 Averaged Without Month Notation", "description": "Seasonal NDVI for Africa. 1981-2000 averaged without month notation. 15 frames/month || Seasonally averaged NDVI for Africa || a001185.00005_print.png (720x480) [401.6 KB] || a001185_pre.jpg (320x242) [6.5 KB] || a001185_thm.png (80x40) [4.3 KB] || a001185_pre_searchweb.jpg (320x180) [40.5 KB] || a001185.webmhd.webm (960x540) [653.1 KB] || a001185.dv (720x480) [41.0 MB] || a001185.mp4 (640x480) [2.1 MB] || a001185.mpg (352x240) [1.4 MB] || ", "hits": 9 }, { "id": 1186, "url": "https://svs.gsfc.nasa.gov/1186/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Monthly NDVI for Africa: July 1981-July 2000", "description": "Monthly NDVI for Africa. July 1981-July 2000. 5 frames/month || Monthly NDVI for Africa over 20 years. || a001186.00005_print.png (720x480) [411.0 KB] || a001186_pre.jpg (320x242) [6.7 KB] || a001186_thm.png (80x40) [4.4 KB] || a001186_pre_searchweb.jpg (320x180) [43.0 KB] || a001186.webmhd.webm (960x540) [6.2 MB] || a001186.dv (720x480) [153.0 MB] || a001186.mp4 (640x480) [7.9 MB] || a001186.mpg (352x240) [5.9 MB] || ", "hits": 7 }, { "id": 1187, "url": "https://svs.gsfc.nasa.gov/1187/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Monthly NDVI Anomaly for Africa: July 1981-July 2000", "description": "Monthly NDVI Anomaly for Africa. July 1981-July 2000. 5 frames/month || Montly averaged NDVI anomalies in Africa for 20 years. || a001187.00005_print.png (720x480) [411.9 KB] || a001187_pre.jpg (320x242) [6.8 KB] || a001187_thm.png (80x40) [4.4 KB] || a001187_pre_searchweb.jpg (320x180) [45.3 KB] || a001187.webmhd.webm (960x540) [7.3 MB] || a001187.dv (720x480) [151.4 MB] || a001187.mp4 (640x480) [7.6 MB] || a001187.mpg (352x240) [5.8 MB] || ", "hits": 17 }, { "id": 1197, "url": "https://svs.gsfc.nasa.gov/1197/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Africa NDVI Average August", "description": "Average NDVI in Africa for the month of August, based off data collected over the 1981-2000 time frame. || Africa NDVI Average August || africa_season0008.jpg (2560x1920) [317.2 KB] || africa_season0008_web.jpg (320x240) [5.9 KB] || africa_season0008_thm.png (80x40) [3.0 KB] || africa_season0008_web_searchweb.jpg (320x180) [40.4 KB] || africa_season0008.tif (2560x1920) [2.1 MB] || ", "hits": 7 }, { "id": 1198, "url": "https://svs.gsfc.nasa.gov/1198/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Africa NDVI 1984 August", "description": "NDVI in Africa for August 1984, based off data collected over the 1981-2000 time frame. || Africa NDVI 1984 August || africa_ndvi0038.jpg (2560x1920) [355.2 KB] || africa_ndvi0038_web.jpg (320x240) [6.0 KB] || africa_ndvi0038_thm.png (80x40) [3.1 KB] || africa_ndvi0038_web_searchweb.jpg (320x180) [40.5 KB] || africa_ndvi0038.tif (2560x1920) [2.3 MB] || For More Information || See [http://svs.gsfc.nasa.gov/stories/drought/index.html](http://svs.gsfc.nasa.gov/stories/drought/index.html) || ", "hits": 6 }, { "id": 1199, "url": "https://svs.gsfc.nasa.gov/1199/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Africa NDVI 1984 August Anomaly", "description": "NDVI anomaly in Africa for August 1984, based off data collected over the 1981-2000 time frame. || Africa NDVI 1984 August Anomaly. Green is more vegetation than average, brown is a deficit of vegetation with respect to the average. || africa_anomaly0038.jpg (2560x1920) [436.4 KB] || africa_anomaly0038_web.jpg (320x240) [6.5 KB] || africa_anomaly0038_thm.png (80x40) [3.1 KB] || africa_anomaly0038_web_searchweb.jpg (320x180) [44.0 KB] || africa_anomaly0038.tif (2560x1920) [2.7 MB] || ", "hits": 7 }, { "id": 1200, "url": "https://svs.gsfc.nasa.gov/1200/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Africa NDVI Average March", "description": "Average NDVI in Africa for the month of March, based off data collected over the 1981-2000 time frame. || Africa NDVI Average March || africa_season0003.jpg (2560x1920) [307.9 KB] || africa_season0003_web.jpg (320x240) [5.6 KB] || africa_season0003_thm.png (80x40) [2.9 KB] || africa_season0003_web_searchweb.jpg (320x180) [38.0 KB] || africa_season0003.tif (2560x1920) [2.0 MB] || ", "hits": 2 }, { "id": 1201, "url": "https://svs.gsfc.nasa.gov/1201/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Africa NDVI 2000 March", "description": "NDVI in Africa for March 2000, based off data collected over the 1981-2000 time frame. || NDVI anomaly for Africa in March, 2000. || africa_ndvi0225.jpg (2560x1920) [352.9 KB] || africa_ndvi0225_web.jpg (320x240) [5.7 KB] || africa_ndvi0225_thm.png (80x40) [2.9 KB] || africa_ndvi0225_web_searchweb.jpg (320x180) [38.9 KB] || africa_ndvi0225.tif (2560x1920) [2.3 MB] || ", "hits": 6 }, { "id": 1202, "url": "https://svs.gsfc.nasa.gov/1202/", "result_type": "Visualization", "release_date": "2000-08-23T12:00:00-04:00", "title": "Africa NDVI 2000 March Anomaly", "description": "NDVI anomaly in Africa for March 2000, based off data collected over the 1981-2000 time frame. || Africa NDVI 2000 March Anomaly. Green is more vegetation than average, brown is a deficit of vegetation with respect to the average. || africa_anomaly0225.jpg (2560x1920) [450.6 KB] || africa_anomaly0225_web.jpg (320x240) [6.4 KB] || africa_anomaly0225_thm.png (80x40) [3.1 KB] || africa_anomaly0225_web_searchweb.jpg (320x180) [42.8 KB] || africa_anomaly0225.tif (2560x1920) [2.8 MB] || ", "hits": 3 }, { "id": 589, "url": "https://svs.gsfc.nasa.gov/589/", "result_type": "Visualization", "release_date": "1999-01-01T12:00:00-05:00", "title": "African Vegetation: Comparing July 1984 and July 1994", "description": "For many years, scientists have believed that the southern expansion of the Sahara has been due to human activity. However, results from the AVHRR instrument and its measurements of vegetation suggest a different explanation: rainfall patterns. In drier years (1984 was one of the driest summers in recorded history in Northern Africa), the Sahara expands south, but in wetter years (such as 1994), vegetation moves back and there is no net expansion of the Sahara as had been previously suggested. || ", "hits": 15 }, { "id": 590, "url": "https://svs.gsfc.nasa.gov/590/", "result_type": "Visualization", "release_date": "1999-01-01T12:00:00-05:00", "title": "African Vegetation: Comparing August 1984 and August 1994", "description": "For many years, scientists have believed that the southern expansion of the Sahara has been due to human activity. However, results from the AVHRR instrument and its measurements of vegetation suggest a different explanation: rainfall patterns. In drier years (1984 was one of the driest summers in recorded history in Northern Africa), the Sahara expands south, but in wetter years (such as 1994), vegetation moves back and there is no net expansion of the Sahara as had been previously suggested. || ", "hits": 10 }, { "id": 591, "url": "https://svs.gsfc.nasa.gov/591/", "result_type": "Visualization", "release_date": "1999-01-01T12:00:00-05:00", "title": "African Vegetation: Comparing September 1984 and September 1994", "description": "For many years, scientists have believed that the southern expansion of the Sahara has been due to human activity. However, results from the AVHRR instrument and its measurements of vegetation suggest a different explanation: rainfall patterns. In drier years (1984 was one of the driest summers in recorded history in Northern Africa), the Sahara expands south, but in wetter years (such as 1994), vegetation moves back and there is no net expansion of the Sahara as had been previously suggested. || ", "hits": 11 }, { "id": 440, "url": "https://svs.gsfc.nasa.gov/440/", "result_type": "Visualization", "release_date": "1998-09-09T12:00:00-04:00", "title": "Africa: Showing the Changing Seasons", "description": "SeaWiFS false color data showing seasonal change in the oceans and on land for Africa. The data is seasonally averaged, and shows spring, summer, fall, winter, spring, summer, and fall. || a000440.00470_print.png (720x480) [691.0 KB] || a000440_thm.png (80x40) [6.6 KB] || a000440_pre.jpg (320x238) [12.9 KB] || a000440_pre_searchweb.jpg (320x180) [84.6 KB] || a000440.webmhd.webm (960x540) [5.1 MB] || a000440.dv (720x480) [75.9 MB] || a000440.mp4 (640x480) [4.1 MB] || a000440.mpg (352x240) [2.7 MB] || ", "hits": 47 } ] }