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U.S. Geological Survey, Western Ecological Research Center

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Decision in resource management are generally based on a combination of sociopolitical, economic, and environmental factors, and may be biased by personal values. These three components often contradict each other resulting in controversy. Controversies can usually be reduced when solid scientific evidence is used to support or refute a decision. However, it is important to recognize that data often do little to alter antagonists' positions when differences in values are the bases if the dispute. But, supporting data can make the decision more defensible, both legally and ethically, especially if the data supporting all opposing viewpoints are included in the decision-making process. Resource management decisions...
Categories: Publication; Types: Citation
In 2010 the U.S. Geological Survey (USGS), Coastal and Marine Geology Program completed three cruises to map the bathymetry of the main channel and shallow intertidal mudflats in the southernmost part of south San Francisco Bay. The three surveys were merged to generate comprehensive maps of Coyote Creek (from Calaveras Point east to the railroad bridge) and Alviso Slough (from the bay to the town of Alviso) to establish baseline bathymetry prior to the breaching of levees adjacent to Alviso and Guadalupe Sloughs as part of the South Bay Salt Pond Restoration Project (http://www.southbayrestoration.org). Since 2010 we have conducted four additional surveys to monitor bathymetric change in this region as restoration...
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This raster dataset depicts percent canopy cover derived from 1-m conifer classifications when aggregated to 30-m cells. Conifer features were classified from 2010, 2012, and 2013 NAIP Digital Ortho Quarter Quads (DOQQ) using the Feature Analyst 5.0 extension for ArcGIS 10.1. Tiles were organized and grouped by Nevada Department of Wildlife Population Management Unit (PMU) locations, plus a 10 km area beyond the PMU extent. Analysts visually identified conifers in the imagery using false color infrared settings and digitized multiple trees per tile as training locations for classification. After performing hierarchical learning and clutter removal with Feature Analyst to remove non-conifer features on output shapefiles,...
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