Filters: Tags: landcover (X) > Types: OGC WMS Layer (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,
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
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,
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,
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,
This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was...
The National Landcover Database (NLCD) from the United States (2001) and the Agriculture and Agri-Food Canada (AAFC) (2000), and a classified Landsat TM scene to fill the gap between the US and Canada were mosaicked together. Landsat images from June or July 2000-2002 were used to be consistent with timing of other data layers. Landcover across the layers were crosswalked and standardized into 5 classes: crop, grassland, other/non-habitat, woody vegetation and water/wetlands.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: AAFC,
AAFC,
Academics & scientific researchers,
Conservation NGOs,
Conservation planning,
The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 National Aerial Imagery Program (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 LandUse/LandCover (LULC) categories. This process involved stitching together more reliable sources for specific categories to...
Categories: Data;
Types: Citation,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Complete,
Data,
EARTH SCIENCE,
EARTH SCIENCE,
EARTH SCIENCE > LAND SURFACE,
This dataset depicts vegetation and landcover at a broad scale for Tule Lake National Wildlife Refuge. It was created through interpretation of aerial imagery (NAIP orthophotography) acquired in August 2014 by the USDA. Ecognition software was then used to create segments of the imagery and those segments were manually classified by a GIS Analyst with the help of refuge biologists and staff with expert knowledge of the local conditions. The GIS Analyst also made a reconnaissance trip to the area in the fall of 2014 to assist with image interpretation. No systematically collected field data were available to create a classification at a finer level, such as the Alliance or Associate level and so this product does...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: California (CA),
Tule Lake NWR,
USFWS,
Vegetation,
habitat,
The National Landcover Database (NLCD) from the United States (2001) and the Agriculture and Agri-Food Canada (AAFC) (2000), and a classified Landsat TM scene to fill the gap between the US and Canada were mosaicked together. Landsat images from June or July 2000-2002 were used to be consistent with timing of other data layers. Landcover across the layers were crosswalked and standardized into 5 classes: crop, grassland, other/non-habitat, woody vegetation and water/wetlands.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: AAFC,
Academics & scientific researchers,
Conservation NGOs,
Conservation planning,
Datasets/Database,
The Province of British Columbia, Ministry of Forests, Lands, & Natural Resource Operations, in partnership with Simon Fraser University and the Alaska Coastal Rainforest Center, led a third workshop to develop cross-boundary geospatial and climate data sets in support of regional conservation applications across NPLCC international boundaries. The workshop will provide opportunities for communicating and discussing priorities for the exchange, development and unification of geospatial and climate datasets.
Categories: Data,
Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: AK-0,
Academics & scientific researchers,
Alaska,
B.C. North Cascades,
B.C. North Cascades,
Area estimates of land cover and land cover change are often based on reference class labels determined by analysts interpreting satellite imagery and aerial photography. Different interpreters may assign different reference class labels to the same sample unit. This dataset include land cover attributes for the year 2000 assigned by 7 image analysts, working independently of each other, to a set of 300 sample locations from a region of the Pacific Northwest of the United States. This data was used in an evaluation of the impact of interpreter variability on variance estimation.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Earth Resources Observation and Science (EROS) Center,
LCMAP,
Land Use Change,
Land Use/ Land Cover,
Landcover,
Priority resources are the set of biological, ecological, and cultural features and ecological processes collaboratively identified as most important, and are the focus of the PFLCC’s planning and scientific efforts. These are based on the draft set of priority resources established by the first Conservation Target Working Group of the PFLCC. The priority resources established in this working group are as follows: coastal uplands, cultural, estuarine, freshwater aquatic, freshwater forested wetlands, freshwater non-forested wetlands, hardwood forested uplands, high pine and scrub, landscape connectivity, marine, pine flatwoods and dry prairie, and working lands. The majority of these priority resources are based...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Conservation,
Conservation Plan/Design/Framework,
Datasets/Database,
Design,
Landcover,
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