{ "count": 12, "next": null, "previous": null, "results": [ { "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": 55 }, { "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": 49 }, { "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": 33 }, { "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": 52 }, { "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": 54 }, { "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": 39 }, { "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": 27 }, { "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": 87 }, { "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": 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": 77 }, { "id": 30268, "url": "https://svs.gsfc.nasa.gov/30268/", "result_type": "Hyperwall Visual", "release_date": "2013-06-26T12:00:00-04:00", "title": "Crop Circles in the Desert", "description": "Over the past three decades, Saudi Arabia has been drilling for a resource more precious than oil. Engineers and farmers have tapped ancient reserves of water, dating back to the last Ice Age, to grow crops in the desert. This series of false-color satellite images show the evolution of agricultural operations in the Wadi As-Sirhan Basin. New vegetation appears bright green while dry vegetation or fallow fields appear rust colored. Dry, barren surfaces (mostly desert) are pink and yellow. Saudi Arabians have reached this underground water source by drilling wells through sedimentary rock, as much as a kilometer beneath the desert sands. Rainfall averages just 100 to 200 millimeters per year and usually does not recharge the underground aquifers, making the groundwater a non-renewable source. Although no one knows how much water lies beneath the desert—estimates range from 252 to 870 cubic kilometers—hydrologists believe it will only be economical to pump it for about 50 years. || ", "hits": 75 }, { "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 } ] }