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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...
Tags: CONUS,
CONUS,
Landsat ARD,
Landsat Analysis Ready Data (ARD),
United States, All tags...
United States,
climatologyMeteorologyAtmosphere,
environment,
heat flow (earth),
image collections,
land surface temperature (LST),
land use change,
maximum land surface temperature (MaxLST),
multispectral imaging,
new growth urban areas (NUA),
persistent urban areas (PUA),
surface urban heat island (SUHI),
surface urban heat island hotspot (SUHIH), Fewer tags
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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...
Categories: Data;
Tags: Land Use Change,
Landsat Path/Row,
Landsat time-series,
Southwest Wyoming,
U.S., All tags...
US,
USGS Science Data Catalog (SDC),
United States,
WY,
Wyoming,
climate change,
field observation,
fractional components,
heat flow (earth),
image collections,
imageryBaseMapsEarthCover,
land use change,
long-term monitoring,
multispectral imaging,
plant community,
shrubland,
shrubland ecosystem,
trends, Fewer tags
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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...
CA,
CO,
California,
Chihuahuan Desert,
Colorado,
Colorado Plateau,
Columbia Plateau,
Grand Canyon,
Great Basin,
Gunnison,
ID,
Idaho,
MT,
Middle Rockies,
Montana,
ND,
NE,
NM,
NV,
Nebraska,
Nevada,
New Mexico,
North Dakota,
Northern Mountainous,
OR,
Oregon,
Rocky Mountains,
SD,
Sonoran Desert,
South Dakota,
Southwest Tablelands,
TX,
Texas,
Three Forks,
UT,
United States,
Utah,
WA,
WY,
Wasatch,
Washington,
Western US,
Wyoming,
Yellowstone,
annual herbaceous,
back-in-time,
bare ground,
big sagebrush,
biota,
climate change,
environment,
geoscientificInformation,
grass,
grassland change,
herbaceous,
imageryBaseMapsEarthCover,
litter,
rangeland,
rangeland management,
sagebrush,
shrub,
shrubland,
shrubland change,
shrubland ecosystems,
shrublands,
terrestrial ecosystems,
time series,
trends,
vegetation,
vegetation change, Fewer 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...
Tags: CONUS,
CONUS,
Landsat ARD,
Landsat Analysis Ready Data (ARD),
United States, All tags...
United States,
climatologyMeteorologyAtmosphere,
environment,
heat flow (earth),
image collections,
land use change,
maximum land surface temperature,
multispectral imaging,
urban heat island, Fewer 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 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.
Tags: CONUS,
CONUS,
Landsat ARD,
Landsat Analysis Ready Data (ARD),
United States, All tags...
United States,
climatologyMeteorologyAtmosphere,
environment,
heat flow (earth),
image collections,
land surface temperature (LST),
land use change,
maximum land surface temperature (MaxLST),
mean land surface temperature (MeanLST),
multispectral imaging,
surface urban heat island (SUHI),
surface urban heat island intensity (SUHII), Fewer tags
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