{ "count": 26, "next": null, "previous": null, "results": [ { "id": 31195, "url": "https://svs.gsfc.nasa.gov/31195/", "result_type": "Hyperwall Visual", "release_date": "2024-04-16T00:00:00-04:00", "title": "50+ years of Landsat: Las Vegas", "description": "The city of Las Vegas—meaning the meadows—was established in 1905. In the 1930s, gambling became legalized and construction of the Hoover Dam began, resulting in the city's first growth spurt. Since then, Las Vegas has not stopped growing. Population has reached nearly two million over the past decade, becoming one of the fastest growing metropolitan areas in the world. These false-color images show the rapid urbanization of Las Vegas between 1972 and 2024.", "hits": 119 }, { "id": 31196, "url": "https://svs.gsfc.nasa.gov/31196/", "result_type": "Hyperwall Visual", "release_date": "2022-10-20T00:00:00-04:00", "title": "50 years of Landsat: Denver", "description": "Since 1972, Landsat satellites have observed our planet’s forests, deserts, cities, farms, and badlands. The Mile High City rose up on the hopes of gold miners, who founded the city in 1858 after the discovery of gold in the waters at the confluence of the South Platte River and Cherry Creek. Denver, Colorado, quickly became a hub for the mining towns to the west and the agricultural interests on the plains to the east. Unhindered by any major body of water or topographic feature to the north, south, or east, the city has expanded in all directions. These red-NIR-green combination false color images show the city of Denver between 1972 or 1972 and 2022, using sensors aboard Landsat satellites that have been collecting data in different ranges of frequencies along the electromagnetic spectrum for nearly 50 years. || ", "hits": 40 }, { "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": 113 }, { "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": 64 }, { "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": 77 }, { "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": 61 }, { "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": 92 }, { "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": 78 }, { "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": 59 }, { "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": 137 }, { "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": 30 }, { "id": 30215, "url": "https://svs.gsfc.nasa.gov/30215/", "result_type": "Hyperwall Visual", "release_date": "2019-03-15T18:00:00-04:00", "title": "Urban Growth in Las Vegas", "description": "The city of Las Vegas—meaning the meadows—was established in 1905. Its grassy meadows and artesian springs attracted settlers traveling across the arid Desert Southwest in the early 1800s. In the 1930s, gambling became legalized and construction of the Hoover Dam began, resulting in the city's first growth spurt. Since then, Las Vegas has not stopped growing. Population has reached nearly two million over the past decade, becoming one of the fastest growing metropolitan areas in the world. These false-color images show the rapid urbanization of Las Vegas between 1972 and 2018. The city streets and other impervious surfaces appear gray, while irrigated vegetation appears red. Over the years, the expansion of irrigated vegetation (e.g., lawns and golf courses) has stretched the city’s desert bounds. || ", "hits": 206 }, { "id": 30874, "url": "https://svs.gsfc.nasa.gov/30874/", "result_type": "Hyperwall Visual", "release_date": "2017-03-24T00:00:00-04:00", "title": "Sprawling Shanghai", "description": "Shanghai sprawl over time, 1984-2022 || shanghai_2022_00865_print.jpg (1024x576) [263.9 KB] || shanghai_2022_00865_searchweb.png (320x180) [123.1 KB] || shanghai_2022_00865_thm.png (80x40) [7.5 KB] || shanghai_2022_1080p30.mp4 (1920x1080) [37.5 MB] || shanghai_2022_1080p30.webm (1920x1080) [4.1 MB] || 3840x2160_16x9_30p (3840x2160) [0 Item(s)] || shanghai_2022_2160p30.mp4 (3840x2160) [135.9 MB] ||", "hits": 67 }, { "id": 11506, "url": "https://svs.gsfc.nasa.gov/11506/", "result_type": "Produced Video", "release_date": "2014-03-20T00:00:00-04:00", "title": "Tracking Urban Change With Landsat", "description": "For helping communities across the United States stay up-to-date on their flood risk, the NASA/USGS Landsat satellites can take a bow. The Federal Emergency Management Agency uses Landsat images, which can illustrate urban changes, as a key indicator of sites where the agency should further investigate the flooding potential. With its archive of images capturing sprawling cities and new developments, Landsat can help FEMA track how building and construction is impacting an area’s landscapeEarth-observing Landsat satellites have been capturing images of the planet’s surface since 1972. Landsat 8 is the newest satellite in the program, a joint effort between NASA and the U.S. Geological Survey. It launched Feb. 11, 2013, and collects more than 400 images per day. New and archived Landsat data are available free to the public over the internet – and researchers have put the data to a multitude of uses. One is called the National Urban Change Indicator, or NUCI, created by MacDonald, Dettwiler, and Associates, LTD. It’s the results from a process that mines Landsat images over a 27-year period to identify areas of “permanent change,” where soil has been paved over for parking lots or other concrete structures.NUCI results act as a red flag for FEMA, helping the agency focus its mapping efforts and budget. But if maps identify a high risk of floods for a certain community, residents can take action, including elevating houses, building flood barricades, and more. || ", "hits": 58 }, { "id": 4032, "url": "https://svs.gsfc.nasa.gov/4032/", "result_type": "Visualization", "release_date": "2013-01-14T00:00:00-05:00", "title": "Urban Sprawl in Beijing, China (Hyperwall version)", "description": "Beijing is one of the oldest, and now, one of the most crowded cities in the world. Established as a city in 1045 BC, King Wu was the first to declare it as a capital in 1057 BC. Having served as the capital of the Liao, Jin, Yuan, Ming and Qing Dynasties, Beijing is now the capital of the People's Republic of China. In these Landsat images, the explosive growth of this ancient city is clearly visible. In 1972, only about 7.89 million people lived there — but by 2010 the population swelled to more than 12 million. This increase in the city's size corresponds to the opening of China to the Western world in the 1970s. Up until 1979, the government restricted housing in the city, limiting it to the confines of the \"Outer City.\" Previously a walled fortress, its outline is still visible today due to the build up of canals and roads along the path of the original wall. Inside this rectangular boundary is the ancient heart of the capital, the moat-lined Forbidden City. Called forbidden because anyone entering needed royal permission, this is where the Imperial Palace still stands, once home to 500 years of Chinese emperors. It was Kublai Khan who established the Forbidden City in 1260 A.D. He called it Khanbaliq but Italian explorer Marco Polo called it Cambuluc. It still stands as Beijing's city center. In 1421 the Chinese took the city back and gave it its current name of Beijing. Today, Beijing is only limited by the rugged Taihang Mountains that run to the west and northwest of the city, pushing the population to spread to the south and east across the relatively flat coastal plain. || ", "hits": 60 }, { "id": 3791, "url": "https://svs.gsfc.nasa.gov/3791/", "result_type": "Visualization", "release_date": "2012-07-23T00:00:00-04:00", "title": "Urban Sprawl in Beijing, China", "description": "Beijing is one of the oldest, and now, one of the most crowded cities in the world. Established as a city in 1045 BC, King Wu was the first to declare it as a capital in 1057 BC. Having served as the capital of the Liao, Jin, Yuan, Ming and Qing Dynasties, Beijing is now the capital of the People's Republic of China. In these Landsat images, the explosive growth of this ancient city is clearly visible. In 1972, only about 7.89 million people lived there — but by 2010 the population swelled to more than 12 million. This increase in the city's size corresponds to the opening of China to the Western world in the 1970s. Up until 1979, the government restricted housing in the city, limiting it to the confines of the \"Outer City.\" Previously a walled fortress, its outline is still visible today due to the build up of canals and roads along the path of the original wall. Inside this rectangular boundary is the ancient heart of the capital, the moat-lined Forbidden City. Called forbidden because anyone entering needed royal permission, this is where the Imperial Palace still stands, once home to 500 years of Chinese emperors. It was Kublai Khan who established the Forbidden City in 1260 A.D. He called it Khanbaliq but Italian explorer Marco Polo called it Cambuluc. It still stands as Beijing's city center. In 1421 the Chinese took the city back and gave it its current name of Beijing. Today, Beijing is only limited by the rugged Taihang Mountains that run to the west and northwest of the city, pushing the population to spread to the south and east across the relatively flat coastal plain. || ", "hits": 66 }, { "id": 11041, "url": "https://svs.gsfc.nasa.gov/11041/", "result_type": "Produced Video", "release_date": "2012-07-23T00:00:00-04:00", "title": "Phoenix, AZ", "description": "Arizona's capital of Phoenix and its neighboring towns in Maricopa County have undergone a major population boom in the last 40 years, and its effects are seen in everything from the expansion of town and cities and to an increased demand for fresh water. || ", "hits": 41 }, { "id": 11050, "url": "https://svs.gsfc.nasa.gov/11050/", "result_type": "Produced Video", "release_date": "2012-07-18T00:00:00-04:00", "title": "Landsat 40th Liveshot City Images", "description": "The following are U.S. cities imaged by Landsat over its 40 year span. Multiple years of selected cities are grouped together with specific years in parentheses. || Atlanta, Georgia || Atlanta_crop_321_1920x1080.jpg (1920x1080) [3.8 MB] || Atlanta_crop_321_1920x1080_web.png (320x180) [347.9 KB] || landsat_us_city_image.hwshow [65 bytes] || ", "hits": 35 }, { "id": 10721, "url": "https://svs.gsfc.nasa.gov/10721/", "result_type": "Produced Video", "release_date": "2012-03-05T17:00:00-05:00", "title": "Las Vegas, 1972-2021", "description": "Timelapse animation of Lake Mead and the city of Las Vegas, Nevada, from 1972-2021, as captured by Landsat sensors. The images are false-color, showing healthy vegetation in red. || Las_Vegas-wide-2021_print.jpg (1024x576) [226.8 KB] || Las_Vegas-wide-2021_searchweb.png (320x180) [119.1 KB] || Las_Vegas-wide-2021_thm.png (80x40) [7.7 KB] || Las_Vegas_1972-2021-tw.mp4 (1920x1080) [64.7 MB] || Las_Vegas-wide-2021.tif (1920x1080) [7.9 MB] || Las_Vegas_1972-2021-tw.webm (1920x1080) [8.0 MB] || Las_Vegas_1972-2021-yt.mp4 (1920x1080) [129.5 MB] || Las_Vegas_1972-2021.mov (1920x1080) [2.3 GB] || ", "hits": 190 }, { "id": 10381, "url": "https://svs.gsfc.nasa.gov/10381/", "result_type": "Produced Video", "release_date": "2009-02-27T00:00:00-05:00", "title": "25 Years of Landsat 5: 1984 Las Vegas Urban Expansion", "description": "This mosaic of images shows the dramatic growth of the Las Vegas urban area during the 25 years that Landsat 5 has been collecting data. || Las_Vegas_1984_2009_1600_1200.jpg (1600x1200) [912.2 KB] || Las_Vegas_1984_2009_560_420.jpg (560x420) [341.7 KB] || Las_Vegas_1984_2009_1600_1200_web.png (320x240) [354.0 KB] || Las_Vegas_1984_2009_1600_1200_thm.png (80x40) [32.0 KB] || Las_Vegas_1984_2009_1600_1200_searchweb.png (320x180) [144.5 KB] || Las_Vegas_1984_2009_1600_1200.tif (1600x1200) [5.5 MB] || ", "hits": 86 }, { "id": 2176, "url": "https://svs.gsfc.nasa.gov/2176/", "result_type": "Visualization", "release_date": "2001-06-12T12:00:00-04:00", "title": "Impervious Surface Cover: Paved Areas in DC and Baltimore", "description": "A special algorithm has been applied to the Landsat 7 image to illuminate the changes in low-density residential land use which exemplify sprawl.There is a link between impervious surfaces within a watershed, (here we see a subset of the Chesapeake Bay watershed area) and the water quality within the watershed. In general, once 10-15 % of an area is covered by impervious surfaces, increased sediments and chemical pollutants in runoff have a measurable effect on water quality. When 15-25% of a watershed is paved or impervious to drainage, increased runoff leads to reduced oxygen levels and impaired stream life. When more then 25% of surfaces are paved, many types of stream life die from the concentrated runoff and sediments. || ", "hits": 21 }, { "id": 2177, "url": "https://svs.gsfc.nasa.gov/2177/", "result_type": "Visualization", "release_date": "2001-06-12T12:00:00-04:00", "title": "Impervious Surface Cover: Non-Paved Areas", "description": "A special algorithm has been applied to the Landsat 7 image to illuminate the changes in low-density residential land use which exemplify sprawl.There is a link between impervious surfaces within a watershed, (here we see a subset of the Chesapeake Bay watershed area) and the water quality within the watershed. In general, once 10-15 % of an area is covered by impervious surfaces, increased sediments and chemical pollutants in runoff have a measurable effect on water quality. When 15-25% of a watershed is paved or impervious to drainage, increased runoff leads to reduced oxygen levels and impaired stream life. When more then 25% of surfaces are paved, many types of stream life die from the concentrated runoff and sediments. || ", "hits": 17 }, { "id": 2178, "url": "https://svs.gsfc.nasa.gov/2178/", "result_type": "Visualization", "release_date": "2001-06-12T12:00:00-04:00", "title": "Impervious Surface Cover: Full Graph of DC and Baltimore", "description": "Here we see an image of the Baltimore/D.C. area taken with the Landsat satellite on March 27, 1998. For over 26 years, Landsat images have been used to help urban planners understand where growth is taking place and help geographers evaluate how different urban planning programs effect population growth and land use. || ", "hits": 13 }, { "id": 2179, "url": "https://svs.gsfc.nasa.gov/2179/", "result_type": "Visualization", "release_date": "2001-06-12T12:00:00-04:00", "title": "Impervious Surface Cover: Close Up of DC", "description": "Here we see an image of the DC area taken with the Landsat satellite on March 27, 1998. For over 26 years, Landsat images have been used to help urban planners understand where growth is taking place and help geographers evaluate how different urban planning programs effect population growth and land use. || ", "hits": 20 }, { "id": 2180, "url": "https://svs.gsfc.nasa.gov/2180/", "result_type": "Visualization", "release_date": "2001-06-12T12:00:00-04:00", "title": "Impervious Surface Cover: Close Up of Baltimore", "description": "Here we see an image of the Baltimore area taken with the Landsat satellite on March 27, 1998. For over 26 years, Landsat images have been used to help urban planners understand where growth is taking place and help geographers evaluate how different urban planning programs effect population growth and land use. || ", "hits": 16 }, { "id": 1056, "url": "https://svs.gsfc.nasa.gov/1056/", "result_type": "Visualization", "release_date": "2000-02-21T12:00:00-05:00", "title": "Shenzhen, China Land Use - True Color", "description": "Zoom into Shenzen, China. True color (3,2,1) Landsat inset. Years 1988, 1989, 1992, 1993, 1994, 1995, 1996. || a001056.00005_print.png (720x480) [713.6 KB] || a001056_pre.jpg (320x240) [28.2 KB] || a001056.webmhd.webm (960x540) [7.2 MB] || a001056.m2v (720x480) [22.0 MB] || a001056.dv (720x480) [102.8 MB] || a001056.mp4 (640x480) [5.6 MB] || a001056.mpg (352x240) [3.8 MB] || ", "hits": 28 } ] }