{
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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": 57
        },
        {
            "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": 44
        },
        {
            "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": 42
        },
        {
            "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": 47
        },
        {
            "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": 38
        },
        {
            "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": 30
        },
        {
            "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": 91
        },
        {
            "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": 38
        },
        {
            "id": 4071,
            "url": "https://svs.gsfc.nasa.gov/4071/",
            "result_type": "Visualization",
            "release_date": "2013-05-08T12:00:00-04:00",
            "title": "Normalized Differential Vegetation Index critical to Agricultural Monitoring in Ukraine, Russia, and Kazakhstan",
            "description": "On April 29-30, 2012 the G8 International Conference on Open Data for Agriculture brought together open data and agriculture experts along with the U.S. Agriculture Secretary U.S. Chief Technology Officer, and the World Bank Vice President for Sustainable Development to explore more opportunities for open data and knowledge sharing. Governments want to help their farmers protect crops from pests and extreme weather, monitor water supplies and anticipate planting seasons that are shifting due to climate change.  New satellite technologies offer enhanced capabilities for early forecasting of food production at national, regional, and global scales. The Group on Earth Observations (GEO) Global Agricultural Monitoring (GEOGLAM) program aims to strengthen national capacity in all countries from freely available data.These visuals show MODIS' satellite-derived crop NDVI Anomaly relative to average (2000-2011). Orange and brown indicate crop with below average conditions. Green indicates crop with above averate conditions. || ",
            "hits": 23
        },
        {
            "id": 4072,
            "url": "https://svs.gsfc.nasa.gov/4072/",
            "result_type": "Visualization",
            "release_date": "2013-05-08T12:00:00-04:00",
            "title": "Normalized Differential Vegetation Index critical to Agricultural Monitoring in the United States",
            "description": "On April 29-30, 2012 the G8 International Conference on Open Data for Agriculture brought together open data and agriculture experts along with the U.S. Agriculture Secretary U.S. Chief Technology Officer, and the World Bank Vice President for Sustainable Development to explore more opportunities for open data and knowledge sharing. Governments want to help their farmers protect crops from pests and extreme weather, monitor water supplies and anticipate planting seasons that are shifting due to climate change.  New satellite technologies offer enhanced capabilities for early forecasting of food production at national, regional, and global scales. The Group on Earth Observations (GEO) Global Agricultural Monitoring (GEOGLAM) program aims to strengthen national capacity in all countries from freely available data.These visuals show MODIS' satellite-derived crop NDVI Anomaly relative to average (2000-2011). Orange and brown indicate crop with below average conditions. Green indicates crop with above averate conditions. The visual compares the crop conditions or NDVI anomaly from year 2011-2012 to year 2012-2013. In the 2012-2013 year 7,342 more metric tons (MT) of wheat were produced then in the previous year, but 40,086 fewer metric tons of corn were produced. || ",
            "hits": 163
        },
        {
            "id": 10484,
            "url": "https://svs.gsfc.nasa.gov/10484/",
            "result_type": "Produced Video",
            "release_date": "2009-09-14T00:00:00-04:00",
            "title": "Landsat: A Space Age Water Gauge",
            "description": "Agriculture consumes a great deal of water. As demand for water increases, the pressure's on to make sure every drop counts. || ",
            "hits": 27
        }
    ]
}