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Surface Urban Heat Island (SUHI) hotspot data are defined as areas of statistically high land surface temperature (LST). A pixel is determined as statistically high if it exceeds one standard deviation above the mean of all pixels with similar land cover type. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual maximum land surface temperature (MaxLST) – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. The data is further separated into persistent urban and new urban outputs. Persistent Urban is defined as areas that are reported as urban in 1985 and...
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The importance of monitoring shrublands to detect and understand changes through time is increasingly recognized as critical to management. This dataset focuses on ecological change observation over ten years of field observation at 134 plots within two sites that are located in Southwestern of Wyoming, USA from 2008-2018. At sites 1 and 3, 134 long-term field observation plots were measured annually from 2008 to 2018. General plot locations were selected in 2006 using segments and spectral clusters on QuickBird imagery to identify the best locations for representing the variability of the entire site (one QuickBird image). Ground measurements were conducted using ocular measurements with cover was estimated from...
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The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in 50 cities of CONUS and its surrounding area by using surface temperature from Landsat surface temperature product in a time series manner. Landsat land surface temperature from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature changes from 1985 to 2020. The current study assessed UHI intensity and its variations associated with urban development in an annual basis. Two datasets, over the study period, show that the maximum surface temperature in the high intensity urban area significantly increased while no significant trend was found in surrounding non-urban areas. These released datasets were spatially...
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Surface Urban Heat Island (SUHI) intensity data is intended to quantify the difference between urban surface temperatures and the surrounding non-urban environment. The calculation takes the difference between a specific urban pixel’s land surface temperature (LST) and the mean of the cities non-urban LST. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual LST – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. NOTE: While a previous version is available from the author, all datasets for pilot cities can be found in version 5..0.
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The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Surface Urban Heat Island (SUHI) hotspot data are defined as areas of statistically high land surface temperature (LST). A pixel is determined as statistically high if it exceeds one standard deviation above the mean of all pixels with similar land cover type. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual maximum land surface temperature (MeanLST) – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. The data is further separated into persistent urban and new urban outputs. Persistent Urban is defined as areas that are reported as urban in 1985 and...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/eap.1389/full): Woody plant encroachment and overall declines in perennial vegetation in dryland regions can alter ecosystem properties and indicate land degradation, but the causes of these shifts remain controversial. Determining how changes in the abundance and distribution of grass and woody plants are influenced by conditions that regulate water availability at a regional scale provides a baseline to compare how management actions alter the composition of these vegetation types at a more local scale and can be used to predict future shifts under climate change. Using a remote-sensing-based approach, we assessed the balance between grasses and woody plants...
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In LCMAP, monitoring refers to the incorporation of every clear observation of remote sensing imagery to determine if current land conditions diverge from those observed in the past. A suite of operational automated algorithms is used to identify different forms of change and to characterize the large variety of land cover types, uses, and conditions that exist across the United States and beyond. The monitoring product suite is to provide land change science information in understanding changes in the type, intensity, condition, location, and time of land use and cover. By using the full historical depth of the Landsat archive from the Thematic Mapper (TM), Enhanced Thematic Mapper (ETM), and Operational Land Imager...
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The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Surface Urban Heat Island (SUHI) intensity data is intended to quantify the difference between urban surface temperatures and the surrounding non-urban environment. The calculation takes the difference between a specific urban pixel’s maximum land surface temperature (MeanLST) and the mean of the cities non-urban MeanLST. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual MeanLST – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. NOTE: While a previous version is available from the author, all datasets for pilot cities can be found in version 5.0.
We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in 50 cities of CONUS and its surrounding area by using surface temperature from Landsat surface temperature product in a time series manner. Landsat land surface temperature from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature changes from 1985 to 2020. The current study assessed UHI intensity and its variations associated with urban development in an annual basis. Two datasets, over the study period, show that the maximum surface temperature in the high intensity urban area significantly increased while no significant trend was found in surrounding non-urban areas. These released datasets were spatially...
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The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
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Surface Urban Heat Island (SUHI) intensity data is intended to quantify the difference between urban surface temperatures and the surrounding non-urban environment. The calculation takes the difference between a specific urban pixel’s maximum land surface temperature (MaxLST) and the mean of the cities non-urban MaxLST. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual MaxLST – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. NOTE: While a previous version is available from the author, all datasets for pilot cities can be found in version 5.0.
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Surface Urban Heat Island (SUHI) hotspot data are defined as areas of statistically high land surface temperature (LST). A pixel is determined as statistically high if it exceeds one standard deviation above the mean of all pixels with similar land cover type. Data are provided across 50 regions throughout the Continental U.S. using previously generated annual land surface temperature (LST) – derived from Collection 1 Landsat U.S. Analysis Ready Data (ARD) for Surface Temperature. The data ranges from 1985-2020, and covers data within 5 km of each city. The data is further separated into persistent urban and new urban outputs. Persistent Urban is defined as areas that are reported as urban in 1985 and remained urban...
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The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
Woody plant encroachment and overall declines in perennial vegetation in dryland regions can alter ecosystem properties and indicate land degradation, but the causes of these shifts remain controversial. Determining how changes in the abundance and distribution of grass and woody plants are influenced by conditions that regulate water availability at a regional scale provides a baseline to which compare how management actions alter the composition of these vegetation types at a more local scale and can be used to predict future shifts under climate change. Using a remote sensing-based approach, we assessed the balance between grasses and woody plants and how climate and topo-edaphic conditions affected their abundances...
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The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
Tags: AZ, Arizona, Arizona Plateau, Black Hills, Blue Mountains, All tags...
thumbnail
We developed an approach to quantify Urban Heat Island (UHI) extent and intensity in 50 cities of CONUS and its surrounding area by using surface temperature from Landsat surface temperature product in a time series manner. Landsat land surface temperature from Landsat Analysis Ready Data (ARD) were used to quantify surface temperature changes from 1985 to 2020. The current study assessed UHI intensity and its variations associated with urban development in an annual basis. Two datasets, over the study period, show that the maximum surface temperature in the high intensity urban area significantly increased while no significant trend was found in surrounding non-urban areas. These released datasets were spatially...


map background search result map search result map Data for Decadal shifts in grass and woody plant cover are driven by prolonged drying and modified by topo-edaphic properties Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Annual Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Bare Ground Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Litter Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Sagebrush Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Shrub Products for the Western U.S., 1985 - 2018 Land surface thermal feature (MaxLST) change monitoring in urban and urban wild land interface in 50 cities of CONUS from 1985-2020 Land surface thermal feature (MeanLST) change monitoring in urban and urban wild land interface in 50 cities of CONUS from 1985-2020 Annual land surface urban heat island intensity from 1985 to present (collection 1) Annual SUHI intensity from MaxLST in 50 cities of CONUS from 1985 to 2020 Annual land surface urban heat island hotspot from 1985 to present (Collection 1) Annual SUHI intensity from MeanLST in 50 cities of CONUS from 1985 to 2020 SUHI Hotspot from MaxLST in persistent urban and new growth urban area of 50 cities of CONUS from 1985 to 2020 SUHI Hotspots from MeanLST in persistent urban and new growth urban area of 50 cities of CONUS from 1985 to 2020 Data for Decadal shifts in grass and woody plant cover are driven by prolonged drying and modified by topo-edaphic properties Long-term field observation of shrubland ecosystem in Wyoming, USA from 2008-2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Annual Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Bare Ground Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Herbaceous Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Litter Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Sagebrush Products for the Western U.S., 1985 - 2018 Remote Sensing Shrub/Grass National Land Cover Database (NLCD) Back-in-Time (BIT) Shrub Products for the Western U.S., 1985 - 2018 Land surface thermal feature (MaxLST) change monitoring in urban and urban wild land interface in 50 cities of CONUS from 1985-2020 Land surface thermal feature (MeanLST) change monitoring in urban and urban wild land interface in 50 cities of CONUS from 1985-2020 Annual land surface urban heat island intensity from 1985 to present (collection 1) Annual SUHI intensity from MaxLST in 50 cities of CONUS from 1985 to 2020 Annual land surface urban heat island hotspot from 1985 to present (Collection 1) Annual SUHI intensity from MeanLST in 50 cities of CONUS from 1985 to 2020 SUHI Hotspot from MaxLST in persistent urban and new growth urban area of 50 cities of CONUS from 1985 to 2020 SUHI Hotspots from MeanLST in persistent urban and new growth urban area of 50 cities of CONUS from 1985 to 2020