Filters: Tags: {"type":"Resource Type","name":"coverage"} (X)
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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,
This is a test of the Resource Type as a non-project.Added the Resource Types in the following order:Now the resources are: 1) model, 2) project.
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,
This region-wide coordinated bird monitoring program, supported by state, federal, tribal, nongovernmental organizations, and two statewide bird conservation partnerships, is designed to provide spatially-referenced baseline data for science-based biological planning and conservation design for the Great Northern LCC and its partners that is directly comparable with other landscapes and BCRs. We are requesting a third year of funding to continue sampling in BCR10 Montana and Idaho to enhance our ability to make robust inference to bird populations on grassland, shrublands, and riparian systems. These data currently are being used by project partners to develop spatially-explicit models that will allow assessment...
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