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To support coordinated conservation, wetland restoration, and climate adaptation planning, we have developed five future scenarios of the Central Valley's seasonally flooded cropland and wetland waterbird habitat based on the State’s most recent climate and land use projections (Wilson et al. 2021).The USGS Western Geographic Science Center and Point Blue Conservation Science modeled a Business-as-Usual scenario plus the four scenarios developed for the Central Valley Landscape Conservation Project, which diverged along two key themes: water availability and management for conservation. Scenarios varied by climate projection (hot and wet vs. warm and dry) and management priorities (wetland restoration rate, crop...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: California,
Central Valley of California,
USGS Science Data Catalog (SDC),
land use/land cover change,
water management and drought, All tags...
waterbirds,
wetland, Fewer tags
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The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
Tags: AZ,
Arizona,
Arizona Plateau,
Black Hills,
Blue Mountains, All tags...
CA,
CO,
California,
Chihuahuan,
Chihuahuan Desert,
Colorado,
Colorado Plateau,
Columbia Plateau,
Desert,
Grand Canyon,
Great Basin,
Gunnison,
ID,
Idaho,
MT,
Mediterranean California,
Middle Rockies,
Mojave,
Montana,
ND,
NE,
NM,
NV,
Nebraska,
Nevada,
New Mexico,
North Dakota,
North Plains,
Northern Great Plains,
Northern Great Salt Lake Desert,
Northern Mountainous,
Northern Rocky Mountains,
OR,
Oregon,
Plains,
Plateau,
Rocky Mountains,
SD,
Sierra Nevada,
Sonoran,
Sonoran Desert,
South Dakota,
Southern Great Salt Lake Desert,
Southern Rocky Mountains,
Southwest Tablelands,
TX,
Texas,
The Rockies,
Three Forks,
UT,
United States,
Utah,
WA,
WY,
Wasatch,
Washington,
Western US,
Wyoming,
Wyoming Basin,
Yellowstone,
annual herbaceous,
back-in-time,
bare ground,
big sagebrush,
biota,
climate change,
environment,
geoscientificInformation,
grass,
grassland change,
herbaceous,
imageryBaseMapsEarthCover,
litter,
mts,
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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The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
Tags: AK,
Alaska,
Burn severity,
Burned area,
CONUS, All tags...
Continental U.S.,
Differenced normalized burn ratio,
Fire location,
Fire occurrence,
HI,
Hawaii,
Landsat,
Location,
MTBS,
Normalized burn ratio,
PR,
Prescribed fire,
Puerto Rico,
Sentinel,
US,
United States,
Wildfire,
Wildland fire,
imageryBaseMapsEarthCover, Fewer tags
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The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
Tags: AK,
Alaska,
Burn severity,
Burned area,
CONUS, All tags...
Continental U.S.,
Differenced normalized burn ratio,
Fire location,
Fire occurrence,
HI,
Hawaii,
Landsat,
Location,
MTBS,
Normalized burn ratio,
PR,
Prescribed fire,
Puerto Rico,
Sentinel,
US,
United States,
Wildfire,
Wildland fire,
imageryBaseMapsEarthCover, Fewer tags
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The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large wildland fires (wildfires and prescribed fires) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image...
Tags: AK,
Alaska,
Burn severity,
Burned area,
CONUS, All tags...
Continental U.S.,
Differenced normalized burn ratio,
Fire location,
Fire occurrence,
HI,
Hawaii,
Landsat,
Location,
MTBS,
Normalized burn ratio,
PR,
Prescribed fire,
Puerto Rico,
Sentinel,
US,
USGS Metadata Identifier,
USGS:62b4778cd34e8f4977cbcee4,
United States,
Wildfire,
Wildland fire,
imageryBaseMapsEarthCover, Fewer tags
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