Canopy cover classes of conifers within the Bi-State area of California and Nevada sage-grouse habitat (2017)
Dates
Publication Date
2017
Start Date
2010-07-01
End Date
2013-08-01
Citation
Coates, P.S., Gustafson, K.B., Roth, C.L., Chenaille, M.P., Ricca, M.A., Mauch, Kimberly, Sanchez-Chopitea, Erika, Kroger, T.J., Perry, W.M., and Casazza, M.L., 2017, Geospatial data for object-based high-resolution classification of conifers within the geographic range of the Bi-State Distinct Population Segment of greater sage-grouse in California and Nevada: U.S. Geological Survey data release, https://doi.org/10.5066/F7G15ZRN.
Summary
This raster dataset depicts percent canopy cover derived from 1-m conifer classifications. 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 Bi-State 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, the conifer polygons underwent post-processing [...]
Summary
This raster dataset depicts percent canopy cover derived from 1-m conifer classifications. 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 Bi-State 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, the conifer polygons underwent post-processing steps to improve results. This included removing small polygons and masking of vegetation that were frequently misclassified (riparian, mountain mahogany, and sagebrush). However, these data did not undergo final modifications to correct for hard seamline transitions or serious errors of omission/commission. Feature classes were converted to 1 x 1 meter cell binary rasters, then mosaicked by PMU in Erdas Imagine.
Canopy cover percentages were calculated by summing all binary conifer raster cell values within a 50-m radius neighborhood (equivalent to 7845 m2) and dividing by the total number of pixels within the neighborhood. To accommodate land managers, cell values were reclassified according to multiple intervals of percent canopy cover up to 50%. Individual intervals were maintained below 10% to provide land managers and researchers the most flexibility for identifying biological significance to sage-grouse and early phases of woodland succession. Output cell values correspond to the following class breaks:
Class 0: 0%
Class 1: greater than 0 to 1%
Class 2: greater than 1 to 2%
Class 3: greater than 2 to 3%
Class 4: greater than 3 to 4%
Class 5: greater than 4 to 5%
Class 6: greater than 5 to 6%
Class 7: greater than 6 to 7%
Class 8: greater than 7 to 8%
Class 9: greater than 8 to 9%
Class 10: greater than 9 to 10%
Class 11: greater than 10 to 15%
Class 12: greater than 15 to 20%
Class 13: greater than 20 to 25%
Class 14: greater than 25 to 30%
Class 15: greater than 30 to 35%
Class 16: greater than 35 to 40%
Class 17: greater than 40 to 45%
Class 18: greater than 45 to 50%
Class 19: greater than 50%
These data were created to provide land and wildlife managers with an additional resource to aid in planning and management decisions within the geographic range of the Bi-State Distinct Population Segment of greater sage-grouse.
Rights
The authors of these data require that data users contact them regarding intended use and to assist with understanding limitations and interpretation. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
