Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: To determine which column and row each tile is in at any of the zoom levels use the following formulas:Column = floor((Xcentroid + 393216)/(2**(16-Level)))Row = floor(-1*(Ycentroid - 720896)/(2**(16-Level)))
Description: The amount of suitable habitat for poplar increases dramtically if irrigation is available. The ability to irrigate depends on landowners having water rights. Water rights information is not available for the majority of the AHB-NW five state region. The presence of photosynthetically active vegetation in otherwise dry agricultural areas during the summer suggests that the area is irrigated and therefore that the landowner has water rights. A data product called the Global Land Survey (GLS) can be used to determine the presence of photosynthetically active vegetation by calculating a Normalized Difference Vegetation Index, or NDVI, value. Comparing NDVI values to National Agriculture Imagery Program, NAIP, imagery enabled the developement of a model to predict water availability.
Copyright Text: University of Washington School of Environmental and Forest Sciences, ESRI, USGS, NASA
Description: MRLC classified each cell as some type of land cover. The 2006 MRLC NLCD data has 3 forest cover types 41 Deciduous Forest, 42 Evergreen Forest, and 43 Mixed Forest. These are areas dominated by trees generally greater than 5 meters tall, and greater than 20 percent of total vegetation cover. Any cell with one of these land cover types is considered forest. All other land cover types are considered non-forest. The source MRLC data was projected to Pacific Northwest Albers, resampled to the cell size we need, and aggregated to our minimum cell size of 256m cells.
Copyright Text: University of Washington School of Environemental and Forest Sciences, Natural Resource Spatial Informatics Group;
Fry, J., Xian, G., Jin, S., Dewitz, J., Homer, C., Yang, L., Barnes, C., Herold, N., and Wickham, J., 2011. Completion of the 2006 National Land Cover Database for the Conterminous United States, PE&RS, Vol. 77(9):858-864.
Description: The source GAP data was projected to Pacific Northwest Albers, clipped to the project extent, reclassified to our classes of interest, resampled to the cell size we need, and aggregated to our minimum cell size of 256m cells.
Copyright Text: University of Washington School of Environemental and Forest Sciences, Natural Resource Spatial Informatics Group;
US Geological Survey, Gap Analysis Program (GAP). May 2011. National Land Cover, Version 2
Description: The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2012 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season.Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites.Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data.Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL.The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.Any cell with one of the following classes, was considered non-agriculture. All other land cover types are considered agriculture.Class Description111 Open Water112 Perennial Ice/Snow121 Developed/Open Space122 Developed/Low Intensity123 Developed/Med Intensity124 Developed/High Intensity131 Barren141 Deciduous Forest142 Evergreen Forest143 Mixed Forest152 Shrubland171 Grassland Herbaceous190 Woody Wetlands195 Herbaceous WetlandsProcessing Steps1. Project From Albers Equal Area Conic to Pacific Northwest Albers maintaining original 30m cell size2. Resample from 30m cell size to 32m cell size using nearest method. This places cells into the Nested Grid structure.3. Reclassify the raster values to 1 for agriculture land cover types and 0 for all other land cover types.4. Use the Neighborhood > Block Statistics tool to count the number of 32m agriculture cells in each 256m cell, using base raster for extent and snap raster.5. Resample from the 32m cell size to the 256m cell size using the nearest method. Each 256m cell now has as its value the number of internal 32m cells that are agriculture.6. Divide each cell value by 64 to get the percent of each cell that is agriculture. Round each percent to the nearest integer.
Copyright Text: University of Washington School of Environemental and Forest Sciences, Natural Resource Spatial Informatics Group; USDA National Agricultural Statistics Service Cropland Data Layer. 2012. Published crop-specific data layer [Online]. Available at http://nassgeodata.gmu.edu/CropScape/ (accessed Feb. 27, 2013;). USDA-NASS, Washington, DC.
Description: The source GAP data was projected to Pacific Northwest Albers, clipped to the project extent, reclassified to our classes of interest, resampled to the cell size we need, and aggregated to our minimum cell size of 256m cells.
Copyright Text: University of Washington School of Environemental and Forest Sciences, Natural Resource Spatial Informatics Group;
US Geological Survey, Gap Analysis Program (GAP). May 2011. National Land Cover, Version 2
Description: The source GAP data was projected to Pacific Northwest Albers, clipped to the project extent, reclassified to our classes of interest, resampled to the cell size we need, and aggregated to our minimum cell size of 256m cells.
Copyright Text: University of Washington School of Environemental and Forest Sciences, Natural Resource Spatial Informatics Group;
US Geological Survey, Gap Analysis Program (GAP). May 2011. National Land Cover, Version 2