Filters: Tags: landcover (X) > Types: Map Service (X)
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The Gulf Coast Prairie Landscape Conservation Cooperative needed seamless landcover data for the south-central United States. This information is essential for developing computer modeling tools related to the conservation of many terrestrial species and determining the quality of vegetation to assess current and desired conditions.
Categories: Data,
Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2012,
Conservation NGOs,
DATA ANALYSIS AND VISUALIZATION,
DATA ANALYSIS AND VISUALIZATION,
Data Acquisition and Development,
This dataset is the third (circa 2013) in a series of three 1-kilometer land use land cover (LULC) time-periods datasets (1975, 2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Gambia,
Land Cover,
Land Use,
biota,
land cover,
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Acadia National Park,
ArcGIS Pro,
Arcpy,
Autoclassification,
Automation,
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Acadia National Park,
ArcGIS Pro,
Arcpy,
Autoclassification,
Automation,
The Missouri Resource Assessment Partnership (MoRAP) of the University of Missouri, in conjunction with the Oklahoma Biological Survey of the University of Oklahoma, produced a vegetation and landcover GIS data layer for the eastern portions of Oklahoma. This effort was accomplished with direction and funding from the Oklahoma Department of Wildlife Conservation and state and federal partners (particularly the Gulf Coast Prairie and Great Plains Landscape Conservation Cooperatives of the U. S. Fish and Wildlife Service). The legend for the layer is based on NatureServe’s Ecological System Classification, with finer thematic units derived from land cover and abiotic modifiers of the System unit. Data for development...
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Ecological Systems,
Landcover,
Oklahoma,
Subsystems,
Vegetation
Coastal resources are increasingly impacted by erosion, extreme weather events, sea-level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying impacts on coastal landscapes due to the numerous geologic, oceanographic, ecological, and socioeconomic factors that exist at a given location. Here, an assessment framework is introduced that synthesizes existing datasets describing the variability of the landscape and hazards that may act on it to evaluate the likelihood of coastal change along the U.S coastline within the coming decade. The pilot study, conducted in the Northeastern U.S. (Maine to Virginia), is comprised of datasets derived from a variety of federal,...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Acadia National Park,
ArcGIS Pro,
Arcpy,
Autoclassification,
Automation,
The landscape of the Southern Rockies Landscape Conservation Cooperative (SRLCC) is diverse with mountain peaks over 14,000 feet in the Rocky Mountains to the basement of one of the largest gorges in the world, the Grand Canyon. Variation at this scale lends to a terrestrial composition as varied as its topography. According to the latest dataset used, shrub\scrub and evergreen forest land cover types dominate. Anthropogenic development classified as either urban or agriculture cover only a small portion of the SRLCC. Alterations of the landscape are monopolized by shrub\scrub and forest land covers, but are less significant when compared with their total area across the landscape. The National Land Cover Database...
The Interagency Vegetation Mapping Project (IVMP) provides maps of existing vegetation, canopy cover, size, and cover type for the entire range of the Northern Spotted Owl using satellite imagery from the Landsat Thematic Mapper (TM). This area is commonly called the FEMAT area, in reference to the area's analysis by the Forest Ecosystem Management Assessment Team. A regression modeling approach was used to predict vegetation characteristics from this Landsat data. This process involved the use of numerous sources of ancillary data, the most crucial being USFS, BLM, and Forest Inventory and Analysis (FIA) plot field data and plot photo interpreted information. This data served as training data in the regression...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: BLM,
Bureau of Land Management,
FEMAT,
FIA,
Forest inventory and analysis,
The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 NAIP dataset (1m) as the basemap, E-Cognition image objects were derived from the multiresolution segmentation algorithm at 75 and 250 segments. Attempts to refine the data training methods using E-cognition, to extrapolate automating categories of this information to the entire map resulted with exceedingly low accuracy. Therefore, a raster was produced by piecing together several data resources, which provide reliable data for specific LULC categories. This process involved stitching together more reliable sources for specific categories to apply to higher resolution (75) segmentation product....
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service;
Tags: LA,
Landcover,
Landuse,
Louisiana,
coastal Louisiana,
This dataset represents vegetation and landcover for Ruby Lake NWR. It was produced by the U.S. Fish and Wildlife Service, with field data collection provided by the University of Nevada, Reno. The process was iterative and took place over two calendar years and two field seasons. Additional data points were acquired in order to validate the map product and to develop a product that met a minimal accuracy level of 80%. The final classification is based on 2013 National Agricultural Imagery Program (NAIP) orthophotography, produced by the U.S. Department of Agriculture but additional datasets were also utilized, including a digital elevation model. The classification methodology uses a hybrid approach of pixel-based...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Nevada,
Ruby Lake NWR,
USFWS,
landcover
This layer represents land cover classes mapped within the Modoc Wildlife Refuge. Mapping was completed using a combination of field data, object-based image analysis using Feature Analyst, and photo interpretation. Source data included 2005 CIR NAIP digital aerial photography, and Modoc National Wildlife Refuge data layers. Field data was collected by USFWS staff in May and June of 2007.
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: California,
Modoc NWR,
USFWS,
Wetland,
habitat,
One of the determinants of runoff is the occurrence of excess rainfall events where rainfall rates exceed the infiltration capacity of soils. To help understand runoff risks, we calculated the probability of excess rainfall events across the Hawaiian landscape by comparing the probability distributions of projected rainfall frequency and land cover-specific infiltration capacity. We characterized soil infiltration capacity based on different land cover types (bare soil, grasses, and woody vegetation) and compared them to the frequency of large rainfall events under current and future (pseudo-global warming) climate scenarios. Here we provide two rasters of excess rainfall for current (2002-2012) and future (2090-2099)...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Shift,
Ecohydrology,
Hawai’i,
Infiltration,
Landcover,
This dataset is the second (2013) of two 500-meter land use land cover (LULC) time-periods datasets (2000, and 2013) aids in monitoring change in West Africa’s land resources. To monitor and map these changes, a 26 general LULC class system was used. The classification system that was developed was primarily inspired by the “Yangambi Classification” (Trochain, 1957). This fairly broad class system for LULC was used because the classes can be readily identified on Landsat satellite imagery. A visual photo-interpretation approach was used to identify and map the LULC classes represented on Landsat images. The Rapid Land Cover Mapper (RLCM) was used to facilitate the photo-interpretation using Esri’s ArcGIS Desktop...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Cape Verde,
Capo Verde,
biota,
land cover,
land use,
This dataset shows Marinas within the Gulf of Mexico
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service;
Tags: Alabama,
Aransas County,
Baldwin County,
Boat,
Boat Ramps,
Potential pollinator habitat was derived by ranking land use classifications and grassland quality based on ground truthing and remotely sensed features indicative of remnant prairie. High resolution (10m) land use data served as the basemap (Hartley et al 2017) from which most categories were identified. All known prairie remnants, prairie plantings, and clusters of mima mounds were delineated. Mima mounds were detected by deriving a slope at 1m scale with greater than 5% from high resolution LiDar data (3m). Mima mounds are indicative of areas in which the topsoil has not been significantly disturbed, and therefore have a higher potential to contain native prairie vegetation. Based on an in-depth literature review...
Categories: Data;
Types: Citation,
Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Landcover,
Landuse,
USGS Science Data Catalog (SDC),
coastal Louisiana,
environment,
Sea level rise caused by climate change is an ongoing phenomenon and a concern both locally and worldwide. Low-lying coastal areas are particularly at risk to flooding and inundation, affecting a large proportion of the human population concentrated in these areas as well as natural communities-particularly animal species that depend on these habitats as a key component of their life cycle. While more local, state, and federal governments have become concerned with the potential effects that predicted sea levels will have on their communities and coastal landscapes, more information is needed on the potential effects that changes in sea level will have on coastal habitats and species.ehensive Habitat Type Dataset...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
Academics & scientific researchers,
BIOLOGICAL CLASSIFICATION,
BIRDS,
CRANES AND ALLIES,
Sea level rise caused by climate change is an ongoing phenomenon and a concern both locally and worldwide. Low-lying coastal areas are particularly at risk to flooding and inundation, affecting a large proportion of the human population concentrated in these areas as well as natural communities-particularly animal species that depend on these habitats as a key component of their life cycle. While more local, state, and federal governments have become concerned with the potential effects that predicted sea levels will have on their communities and coastal landscapes, more information is needed on the potential effects that changes in sea level will have on coastal habitats and species.ehensive Habitat Type Dataset...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
Academics & scientific researchers,
BIOLOGICAL CLASSIFICATION,
The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 NAIP dataset (1m) as the basemap, E-Cognition image objects were derived from the multiresolution segmentation algorithm at 75 and 250 segments. Attempts to refine the data training methods using E-cognition, to extrapolate automating categories of this information to the entire map resulted with exceedingly low accuracy. Therefore, a raster was produced by piecing together several data resources, which provide reliable data for specific LULC categories. This process involved stitching together more reliable sources for specific categories to apply to higher resolution (75) segmentation product....
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2015,
Complete,
Data,
EARTH SCIENCE,
EARTH SCIENCE > LAND SURFACE,
NWFP-20 - Northwest Forest Plan Effectiveness Monitoring (20-Year Report)Estimated completion June 2015This project is a continuation of research completed for the 15-year Report for NWFP Effectiveness Monitoring. We are continuing to develop and refine modeling techniques and data, to provide improved multi-date GNN maps of forest vegetation and older forest. Key improvements to GNN modeling to be implemented in this project are: (1) addition of more inventory plots, with yearly matching of plots to LandTrendr imagery for model development; (2) incorporation of measures of disturbance history, derived from LandTrendr algorithms, as spatial predictors; (3) improved GNN outlier analysis using TimeSync; and (4) additional...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: BLM,
Bureau of Land Management,
CA,
CLAMS,
CMONster,
One of the determinants of runoff is the occurrence of excess rainfall events where rainfall rates exceed the infiltration capacity of soils. To help understand runoff risks, we calculated the probability of excess rainfall events across the Hawaiian landscape by comparing the probability distributions of projected rainfall frequency and land cover-specific infiltration capacity. We characterized soil infiltration capacity based on different land cover types (bare soil, grasses, and woody vegetation) and compared them to the frequency of large rainfall events under current and future (pseudo-global warming) climate scenarios. Here we provide a raster stack that contain the probability of excess rainfall exceeding...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Climate Shift,
Ecohydrology,
Hawai’i,
Infiltration,
Landcover,
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