{
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    "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": 64
        },
        {
            "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": 43
        },
        {
            "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": 48
        },
        {
            "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": 49
        },
        {
            "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": 45
        },
        {
            "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": 32
        },
        {
            "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": 34
        },
        {
            "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": 13694,
            "url": "https://svs.gsfc.nasa.gov/13694/",
            "result_type": "Produced Video",
            "release_date": "2021-04-19T09:00:00-04:00",
            "title": "Tracking Amazon Deforestation",
            "description": "The Amazon is the largest tropical rainforest in the world, nearly as big as the continental United States. But every year, less of that forest is still standing. Today's deforestation across the Amazon frontier is tractors and bulldozers clearing large swaths to make room for industrial-scale cattle ranching and crops. Landsat satellite data is used to map land cover in Brazil with a historical perspective, going back to 1984.Music: Organic Circuit by Richard Birkin [PRS]; Into the Atmosphere by Sam Joseph Delves [PRS]; Ethereal Journey by Noé Bailleux [SACEM]; Wildfires by Magnum Opus [ASCAP]; Letter For Tomorrow by Anthony d’Amario [SACEM].Complete transcript available.Watch this video on the NASA Goddard YouTube channel. || Amazon_clearing_poster.jpg (3840x2160) [2.4 MB] || Amazon_clearing_DSC_1491.jpg (6000x4000) [5.3 MB] || Amazon_clearing_poster_searchweb.png (320x180) [88.6 KB] || Amazon_clearing_poster_thm.png (80x40) [5.8 KB] || 13694_Amazon_deforestation_yt.mp4 (1920x1080) [417.9 MB] || 13694_Amazon_deforestation_tw.mp4 (1280x720) [89.4 MB] || 13694_Amazon_deforestation_yt.webm (1920x1080) [45.5 MB] || 13694_Amazon_deforestation-captions.en_US.srt [7.1 KB] || 13694_Amazon_deforestation-captions.en_US.vtt [6.9 KB] || ",
            "hits": 347
        },
        {
            "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": 34
        },
        {
            "id": 4530,
            "url": "https://svs.gsfc.nasa.gov/4530/",
            "result_type": "Visualization",
            "release_date": "2018-06-12T11:00:00-04:00",
            "title": "50 Kilometers of Brazilian Forest Canopy",
            "description": "This visualization shows an airplane collecting a 50 kilometer swath of lidar data over the Brazilian rainforest. For ground level features, colors range from deep brown to tan. Vegetation heights are depicted in shades of green, where dark greens are closest to the ground and light greens are the highest. || transect2014.17900_print.jpg (1024x576) [106.2 KB] || transect2014.17900_searchweb.png (320x180) [44.6 KB] || transect2014.17900_thm.png (80x40) [4.1 KB] || transect2014_720p30.webm (1280x720) [71.4 MB] || transect2014_720p30.mp4 (1280x720) [132.4 MB] || transect2014_1080p30.mp4 (1920x1080) [311.2 MB] || transect2014_360p30.mp4 (640x360) [30.3 MB] || transect2014 (3840x2160) [0 Item(s)] || transect2014_2160p30_3.mp4 (3840x2160) [1.2 GB] || transect2014_1080p30.mp4.hwshow [212 bytes] || ",
            "hits": 37
        },
        {
            "id": 4532,
            "url": "https://svs.gsfc.nasa.gov/4532/",
            "result_type": "Visualization",
            "release_date": "2018-06-12T11:00:00-04:00",
            "title": "Flying Through LIDAR Canopy Data",
            "description": "This animation shows an airplane collecting treetop data over a Brazilian rainforest. As the airplane continues to collect data, the viewer flies down to the rainforest canopy and flies through the virtual leaves, eventually emerging to see the airplane off in the distance still collecting new data. It should be noted that for the purposes of this animation, we chose to use leaf-like objects to represent each lidar data point in 3D space. However, lidar data does not specifically show individual leaves, but simply point heights reflected by the leaf canopy. However, the resolution of the lidar data is so good that it potentially can pick up leaves and other structures such as tree branches, and sometimes even flying birds, but has no easy way to differentiate between them. Therefore, since the location of this particular data was known to be a rainforest, and the majority of the data points would represent leaves, we chose leaf-like structures for this particular case. || flythrough.0520_print.jpg (1024x576) [192.8 KB] || flythrough.0520_searchweb.png (320x180) [84.5 KB] || flythrough.0520_thm.png (80x40) [5.8 KB] || flythrough_1080p30.mp4 (1920x1080) [82.6 MB] || flythrough_720p30.mp4 (1280x720) [39.9 MB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || flythrough_1080p30.webm (1920x1080) [5.9 MB] || flythrough_360p30.mp4 (640x360) [12.3 MB] || flythrough_4532.key [40.3 MB] || flythrough_4532.pptx [40.0 MB] || flythrough_1080p30.mp4.hwshow [184 bytes] || ",
            "hits": 115
        },
        {
            "id": 4650,
            "url": "https://svs.gsfc.nasa.gov/4650/",
            "result_type": "Visualization",
            "release_date": "2018-06-12T11:00:00-04:00",
            "title": "Brazilian Rainforest Logged Area Canopy Change 2013-2016",
            "description": "This data visualization starts with an airplane collecting lidar over a flat plane. As the data is collected a strip of the 2013 Brazilian rainforest canopy can be seen. Once the plane flies past, we spin the camera around to get a better view of the treetop canopy data. We then highlight areas of the canopy that will undergo significant change from 2013 to 2016. Finally, we allow those highlighted areas (ie, trees and tree branches) to fall the the ground, revealing the new 2016 forest canopy. || logged_v84_comp.0500_print.jpg (1024x576) [280.1 KB] || logged_v84_comp.0500_searchweb.png (320x180) [100.0 KB] || logged_v84_comp.0500_thm.png (80x40) [6.7 KB] || logged_v84_comp_1080p30.mp4 (1920x1080) [32.8 MB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || logged_v84_comp_1080p30.webm (1920x1080) [2.6 MB] || logged_v84_comp_1080p30.mp4.hwshow [189 bytes] || ",
            "hits": 26
        },
        {
            "id": 4651,
            "url": "https://svs.gsfc.nasa.gov/4651/",
            "result_type": "Visualization",
            "release_date": "2018-06-12T11:00:00-04:00",
            "title": "Brazilian Rainforest Area Canopy Change 2013-2014-2016",
            "description": "This data visualization starts in 2013 with an airplane collecting lidar data. As the plane flies overhead, the viewer finds themselves amongst the recently collected treetop canopy. The viewer then moves forward through the canopy eventually lifting up to get a birds eye view of the recently collected strip of data points (represented as leaf-like shapes). Areas of change from 2013 to 2014 are then highlighted and the data transitions to what the canopy looked like in 2014. Areas of change between 2014 to 2016 are then highlighted before the data transitions again to what the canopy looked like in 2016. Each successive change allows scientists to carefully monitor the turn over rate of foliage over this three year period. || nologging_v87.0410_print.jpg (1024x576) [85.0 KB] || nologging_v87.0410_searchweb.png (320x180) [51.7 KB] || nologging_v87.0410_thm.png (80x40) [5.1 KB] || nologging_v87_comp_1080p30.mp4 (1920x1080) [46.2 MB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || nologging_v87_comp_1080p30.webm (1920x1080) [4.3 MB] || nologging_v87_comp_1080p30.mp4.hwshow [192 bytes] || ",
            "hits": 24
        },
        {
            "id": 4652,
            "url": "https://svs.gsfc.nasa.gov/4652/",
            "result_type": "Visualization",
            "release_date": "2018-06-12T11:00:00-04:00",
            "title": "Brazilian Rainforest Canopy Change at Mission Start 2013-2014-2016",
            "description": "This data visualization starts in 2013 with an airplane collecting lidar data. As the plane flies overhead, the stationary viewer finds themselves amongst the recently collected treetop canopy. The viewer then drifts upward getting a better view of the beginning of the data swath. Areas that change between 2013 and 2014 are then highlighted and the data transitions fully to what the canopy looked like in 2014. Next, areas of change between 2014 to 2016 are highlighted and then fully transition to the canopy in 2016. Being able to see this level of change allows scientists to carefully monitor the foliage turnover rate in this remote part of the world. || stillcam5_comp.0690_print.jpg (1024x576) [217.2 KB] || stillcam5_comp.0690_searchweb.png (320x180) [66.4 KB] || stillcam5_comp.0690_thm.png (80x40) [4.3 KB] || stillcam5_comp_1080p30.mp4 (1920x1080) [41.9 MB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || stillcam5_comp_1080p30.webm (1920x1080) [3.1 MB] || stillcam5_comp_1080p30.mp4.hwshow [188 bytes] || ",
            "hits": 34
        },
        {
            "id": 12035,
            "url": "https://svs.gsfc.nasa.gov/12035/",
            "result_type": "Produced Video",
            "release_date": "2015-10-28T11:00:00-04:00",
            "title": "Brazil’s Extreme Drought Seen From Space",
            "description": "Empty water reservoirs, severe water rationing, and electrical blackouts are the new status quo in major cities across southeastern Brazil where the worst drought in 35 years has desiccated the region. A new NASA study estimates that the region has lost an average of 15 trillion gallons of water per year from 2012 to 2015. Eastern Brazil as a whole has lost on average 28 trillion gallons of water per year over the same time period.Augusto Getirana, a hydrologist at NASA's Goddard Space Flight Center, in Greenbelt, Maryland, analyzed the amount of water stored in aquifers and rivers across Brazil from 2002 to 2015, interested in understanding the depth of the current drought.A new data visualization of 13 years of GRACE data shows the distribution of water across Brazil. Blues indicate increases in water, mostly occurring in the western regions of Brazil in the rainforest. Meanwhile red and orange shows where water stores have declined, occurring mainly in the north and southeast. At the beginning of the data collection, in 2002, Brazil was just coming out of a drought that began in 2000. A wet period followed until 2012 when dry conditions set in again due to a lack of precipitation and higher than usual temperatures, according to supplemental data.Southeastern Brazil was hardest hit by drought conditions, said Getirana. To make matters worse, Brazil relies on rivers that feed into reservoirs and dams that generate about 75 percent of the electrical power for the country. By September 2014, for example, the Cantareira reservoir system that provides water for 8.8 million people in São Paulo's metro region reported that it was filled to 10.7 percent of its total capacity, a situation that has led to major water rationing.Research: Extreme water deficit in Brazil detected from space.Journal: Hydrometeorology, October 27, 2015.Link to paper: http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-15-0096.1Here is the YouTube video.Additional footage from: Itaipu Binacional Files. || ",
            "hits": 54
        },
        {
            "id": 12036,
            "url": "https://svs.gsfc.nasa.gov/12036/",
            "result_type": "Produced Video",
            "release_date": "2015-10-28T11:00:00-04:00",
            "title": "Instagram: Brazil's Extreme Drought Seen From Space",
            "description": "Empty water reservoirs, severe water rationing, and electrical blackouts are the new status quo in major cities across southeastern Brazil where the worst drought in 35 years has desiccated the region. A new NASA study estimates that the region has lost an average of 15 trillion gallons of water per year from 2012 to 2015. Eastern Brazil as a whole has lost on average 28 trillion gallons of water per year over the same time period.Augusto Getirana, a hydrologist at NASA's Goddard Space Flight Center, in Greenbelt, Maryland, analyzed the amount of water stored in aquifers and rivers across Brazil from 2002 to 2015, interested in understanding the depth of the current drought.A new data visualization of 13 years of GRACE data shows the distribution of water across Brazil. Blues indicate increases in water, mostly occurring in the western regions of Brazil in the rainforest. Meanwhile red and orange shows where water stores have declined, occurring mainly in the north and southeast. At the beginning of the data collection, in 2002, Brazil was just coming out of a drought that began in 2000. A wet period followed until 2012 when dry conditions set in again due to a lack of precipitation and higher than usual temperatures, according to supplemental data.Southeastern Brazil was hardest hit by drought conditions, said Getirana. To make matters worse, Brazil relies on rivers that feed into reservoirs and dams that generate about 75 percent of the electrical power for the country. By September 2014, for example, the Cantareira reservoir system that provides water for 8.8 million people in São Paulo's metro region reported that it was filled to 10.7 percent of its total capacity, a situation that has led to major water rationing.Research: Extreme water deficit in Brazil detected from space.Journal: Hydrometeorology, October 27, 2015.Link to paper: http://journals.ametsoc.org/doi/abs/10.1175/JHM-D-15-0096.1Here is the YouTube video.Additional footage from: Itaipu Binacional Files. || ",
            "hits": 26
        },
        {
            "id": 3967,
            "url": "https://svs.gsfc.nasa.gov/3967/",
            "result_type": "Visualization",
            "release_date": "2012-07-23T00:00:00-04:00",
            "title": "Deforestation in Rondonia, Brazil",
            "description": "In this animation of images from 1975 until 2012, acquired by the Landsat 5 and 7 satellites, enormous tracts of Amazonian forest disappear in Rondonia, a state in Western Brazil.Deforestation in Rondonia in the 1970s until the 1990s had a distinctive \"fishbone\" pattern. Access to this remote region began with a major road cutting through the dense tropical forest, opening up new territory for small farms and ranches. Then, other roads developed at right angles to the initial road. In this visualization, these roads shoot off a stretch of the main \"backbone\" road for about 31 miles (~50 kilometers) long, each secondary road branching off about every 2.5 (~4 kilometers). This creates the \"fishbone\" pattern. Even with the deforestation, Brazil is still home to more than a quarter of Earth's tropical forests. In addition to their astounding biodiversity, these forests act as a major carbon \"sink.\" These are places where carbon dioxide in the atmosphere is absorbed by living things, like trees and plants, and thus the carbon is said to be trapped or sequestered. With increasing carbon dioxide levels around the world, the ability of these forests to hold onto carbon has beneficial implications for stabilizing the world's climate.NASA and the U.S. Department of the Interior through the U.S. Geological Survey (USGS) jointly manage Landsat, and the USGS preserves a 40-year archive of Landsat images that is freely available over the Internet. The next Landsat satellite, now known as the Landsat Data Continuity Mission (LDCM) and later to be called Landsat 8, is scheduled for launch in 2013. || ",
            "hits": 78
        },
        {
            "id": 10872,
            "url": "https://svs.gsfc.nasa.gov/10872/",
            "result_type": "Produced Video",
            "release_date": "2011-11-14T13:00:00-05:00",
            "title": "Amazon Deforestation in Rondonia, Brazil, 2000-2010",
            "description": "The state of Rondonia in western Brazil is observed by satellite. This timelapse of MODIS images shows the reduction of the forest from 2000-2010.Deforestation follows a fairly predictable pattern in these images. The first clearings that appear in the forest are in a fishbone pattern, arrayed along the edges of roads. Over time, the fishbones collapse into a mixture of forest remnants, cleared areas, and settlements. This pattern follows one of the most common deforestation trajectories in the Amazon. Legal and illegal roads penetrate a remote part of the forest, and small farmers migrate to the area. They claim land along the road and clear some of it for crops. Within a few years, heavy rains and erosion deplete the soil, and crop yields fall. Farmers then convert the degraded land to cattle pasture, and clear more forest for crops. Eventually the small land holders, having cleared much of their land, sell it or abandon it to large cattle holders, who consolidate the plots into large areas of pasture. || ",
            "hits": 150
        },
        {
            "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": 47
        },
        {
            "id": 2993,
            "url": "https://svs.gsfc.nasa.gov/2993/",
            "result_type": "Visualization",
            "release_date": "2004-09-07T12:00:00-04:00",
            "title": "Up on Deck, Hurricane Ivan",
            "description": "From space, the Aqua satellite has a bird's eye view of Hurricane Ivan. This data was gathered on the September 5, 2004. At that time, Ivan was off the coast of Brazil. || ",
            "hits": 13
        },
        {
            "id": 2388,
            "url": "https://svs.gsfc.nasa.gov/2388/",
            "result_type": "Visualization",
            "release_date": "2002-02-18T12:00:00-05:00",
            "title": "Wonderglobe: Brazil",
            "description": "Zoom in to Brazil following the Amazon River. Data set is the Wonderglobe data composited via Terra/MODIS data. || Animation zooming into Brazil || a002388.00100_print.png (720x480) [239.0 KB] || brazil_thm.png (80x40) [4.2 KB] || brazil_pre.jpg (320x238) [5.8 KB] || brazil_pre_searchweb.jpg (320x180) [43.5 KB] || a002388.webmhd.webm (960x540) [5.6 MB] || a002388.dv (720x480) [157.8 MB] || brazil.mpg (352x240) [6.8 MB] || ",
            "hits": 32
        },
        {
            "id": 2106,
            "url": "https://svs.gsfc.nasa.gov/2106/",
            "result_type": "Visualization",
            "release_date": "2001-04-19T12:00:00-04:00",
            "title": "Deforestation of Rondonia, Brazil, from 1975 to 2001",
            "description": "Throughout much of the 1980s, deforestation in Brazil eliminated more than 15,000 square kilometers (9000 square miles) per year. That pace has only increased through the 90s and into the 21st century.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 primaryproducer of oxygen. In the respiration process that absorbs gaseous carbon dioxide, trees and other plants give off oxygen.It is for these and a host of other reasons why scientists and policy makers need to monitor and forestall wholesale deforestation.This sequence shows how profligate clear cutting can influence that trust. Data gathered over time by several in the Landsat series of spacecraft shows enormous tracts of forest disappearing in Rondonia, Brazil. This territory underwent an enormous rise in population towards the end of the twentieth century, buoyed by cheap land offered by the national government for agricultural use. As you see the visualization progress, it is useful to note how the human phenomenon of deforestation generally works, especially in the dense tropical forests of Brazil. Systematic cutting of a road opens new territory to potential deforestation by penetrating into new areas. Clearing of vegetation along the sides of those roads tends to fan out to create a pattern akin to a fish skeleton. As new paths appear in the woods, new areas become vulnerable. The spaces between the 'skeletal bones' fall to defoliation, and another inch of the Earth's biological rudder is no longer reliably steering the planet into the future. || ",
            "hits": 66
        },
        {
            "id": 2116,
            "url": "https://svs.gsfc.nasa.gov/2116/",
            "result_type": "Visualization",
            "release_date": "2001-04-19T12:00:00-04:00",
            "title": "Deforestation of Rondonia, Brazil (with dates), from 1975 to 2001",
            "description": "Throughout much of the 1980s, deforestation in Brazil eliminated more than 15,000 square kilometers (9000 square miles) per year. That pace has only increased through the 90s and into the 21st century.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 primaryproducer of oxygen. In the respiration process that absorbs gaseous carbon dioxide, trees and other plants give off oxygen.It is for these and a host of other reasons why scientists and policy makers need to monitor and forestall wholesale deforestation.This sequence shows how profligate clear cutting can influence that trust. Data gathered over time by several in the Landsat series of spacecraft shows enormous tracts of forest disappearing in Rondonia, Brazil. This territory underwent an enormous rise in population towards the end of the twentieth century, buoyed by cheap land offered by the national government for agricultural use. As you see the visualization progress, it is useful to note how the human phenomenon of deforestation generally works, especially in the dense tropical forests of Brazil. Systematic cutting of a road opens new territory to potential deforestation by penetrating into new areas. Clearing of vegetation along the sides of those roads tends to fan out to create a pattern akin to a fish skeleton. As new paths appear in the woods, new areas become vulnerable. The spaces between the 'skeletal bones' fall to defoliation, and another inch of the Earth's biological rudder is no longer reliably steering the planet into the future. || ",
            "hits": 59
        },
        {
            "id": 1338,
            "url": "https://svs.gsfc.nasa.gov/1338/",
            "result_type": "Visualization",
            "release_date": "1999-04-09T12:00:00-04:00",
            "title": "Iturralde Structure",
            "description": "Zooming in to the Iturralde structure, a suspected impact crater in northern Bolivia, from Landsat imagery taken in 1988.  Major features are labeled. || a001338.00005_print.png (720x480) [455.3 KB] || a001338_thm.png (80x40) [5.5 KB] || a001338_pre.jpg (320x238) [9.4 KB] || a001338_pre_searchweb.jpg (320x180) [64.5 KB] || a001338.webmhd.webm (960x540) [4.1 MB] || a001338.dv (720x480) [73.2 MB] || a001338.mp4 (640x480) [3.9 MB] || a001338.mpg (352x240) [2.9 MB] || ",
            "hits": 13
        },
        {
            "id": 1339,
            "url": "https://svs.gsfc.nasa.gov/1339/",
            "result_type": "Visualization",
            "release_date": "1999-04-09T12:00:00-04:00",
            "title": "Iturralde Structure Without Labels",
            "description": "Zooming in to the Iturralde structure, a suspected impact crater in northern Bolivia, from Landsat imagery taken in 1988. || a001339.00005_print.png (720x480) [431.4 KB] || a001339_thm.png (80x40) [4.8 KB] || a001339_pre.jpg (320x238) [7.6 KB] || a001339_pre_searchweb.jpg (320x180) [49.2 KB] || a001339.webmhd.webm (960x540) [2.5 MB] || a001339.dv (720x480) [53.3 MB] || a001339.mp4 (640x480) [2.8 MB] || a001339.mpg (352x240) [2.2 MB] || ",
            "hits": 12
        },
        {
            "id": 1340,
            "url": "https://svs.gsfc.nasa.gov/1340/",
            "result_type": "Visualization",
            "release_date": "1999-04-09T12:00:00-04:00",
            "title": "Photograph of Iturralde Structure from a Cessna",
            "description": "A photograph of the Iturralde structure in northern Bolivia, taken from a Cessna.  Major features are labeled. || a001340_still.jpg (720x528) [116.0 KB] || a001340_pre.jpg (320x238) [12.6 KB] || a001340_thm.png (80x40) [6.7 KB] || a001340_pre_searchweb.jpg (320x180) [86.7 KB] || Video slate image reads, \"LandSat ImagesPhotograph of the Araona Crater from Cessna.Features labeled.courtesy of Compton Tucker\". || a001340_slate.jpg (720x528) [90.4 KB] || a001340_slate_web.png (320x234) [68.2 KB] || ",
            "hits": 3
        },
        {
            "id": 1341,
            "url": "https://svs.gsfc.nasa.gov/1341/",
            "result_type": "Visualization",
            "release_date": "1999-04-09T12:00:00-04:00",
            "title": "Photograph of Iturralde Structure from a Cessna (No Labels)",
            "description": "A photograph of the Iturralde structure in northern Bolivia, taken from a Cessna. || a001341_still.jpg (720x528) [107.4 KB] || a001341_pre.jpg (320x238) [11.5 KB] || a001341_thm.png (80x40) [5.7 KB] || a001341_pre_searchweb.jpg (320x180) [72.1 KB] || ",
            "hits": 4
        }
    ]
}