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Desert Landscape Conservation Cooperative Boundary delineates the spatial extent of the DLCC. The vector boundary is available as both a shapefile and KML file. This is a derivative product of the LCCs shapefile produced by the U.S. Fish and Wildlife Service, accessed from http:/http://www.fws.gov/GIS/data/national/ in 2014. To access the KML file, click on the ScienceBase URL and then select Open in Google Earth (KML). To access the shapefile (FWS_LCC_DLCC.shp), click on FWS_LCC_DLCC.zip linked from this product profile. 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... The Desert Landscape Conservation Cooperative Land Cover Map shows land cover at a regional scale (1:2,500,000). The files provided are graphic design files that can be used to plot a publication-quality, poster-size map. Scale: 1:2,500,000 Map poster dimensions: 34 x 44 inches Data sources: Land cover from North American Environmental Atlas by the Commission for Environmental Cooperation, 2010. Physiographic regions from Natural Earth 1:10 million scale Physical Labels (3.0.0) derived from Patterson's Physical Map of the World, 2008. Hydrography, populated places, and political boundaries from National Atlas of the United States, 2004. File descriptions: DLCC_LandCover.ai is an Adobe Illustrator file. ... Project Area Analysis Tool - Service Definition. This Service Definition is optimized for ArcGIS Server. Rasters have been converted to the least common denominator (32-bit converted to 1,2, or 4-bit) where applicable/possible. All datasets projected to Web Mercator (aux sphere). Sea level rise projections produced by the University of Florida Geoplan Center. These projections measure sea level rise in meter increments up until 6 meters, the predicted sea level rise measure if both Greenland and the West Antarctic ice sheet melt. Sea level rise datasets selected from sketch tool, visualizing Mean Higher High Water and Mean Sea Level projections for 3 sea level change scenarios. Researchers from the University of Florida developed a sketch planning tool that can be used to conduct statewide and regional assessments of transportation facilities potentially vulnerable to climate trends. The project focused on the potential vulnerability of transportation infrastructure to the effects of possible future rates of sea level change (SLC) and increasing tidal datums (Mean Lower Low Water (MLLW), Mean Low Water (MWL), Mean Sea Lea Level (MSL), Mean High Water (MHW), and Mean Higher High Water (MHHW). US Army Corps of Engineers (USACE) sea level... In 2006, the Century Commission for a Sustainable Florida called for an identification of those lands and waters in the state that are critical to the conservation of Florida's natural resources. In response, the Florida Natural Areas Inventory, University of Florida Center for Landscape Conservation Planning, and Florida Fish & Wildlife Conservation Commission collaborated to produce CLIP - the Critical Lands and Waters Identification Project. CLIP is now being used to inform planning decisions by the Peninsular Florida Landscape Conservation Cooperative, coordinated by the U.S. Fish and Wildlife Service. Changes to the coastline and to coastal features, such as spits, barrier islands, estuaries, tidal guts and lagoons were mapped for over 22,000 km of coastline along the Bering Sea and Gulf of Alaska coasts in western Alaska. Changes to rivers and lakes near the coast were also captured. The analysis was based on time-series analysis of Landsat imagery, 1972–2013. An annual time-series of suitable Landsat imagery was compiled and analyzed for changes in near-infrared reflectance to identify areas that transitioned from land to water, or vice-versa, over the study period. The timing of changes was also identified. Thousands of coastal changes over the 42-year study period exceeded the 60-m pixel resolution of the... Source.


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