A Customized Image Classification Framework to Develop Regional-scale, High-resolution Conifer Maps

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The substantial distributional expansion and infill of pinyon (Pinus monophylla) and juniper (Juniperus sp.) trees (hereafter, "conifer") into sagebrush (Artemisia spp.) ecosystems in Nevada and northeastern California since the late 1800s threatens the ecological function and economic viability of these ecosystems and represents a major contemporary challenge facing land and wildlife managers. Conifer expansion into sagebrush systems can lower resilience to disturbance and resistance to invasion, reduce forage for cattle, increase soil erosion from water runoff, and promote wildfire activity. Even relatively low conifer cover represents a primary threat to wildlife populations such as the greater sage-grouse (Centrocercus urophasianus; hereafter, "sage-grouse"). Conifer cover as low as 5% decreases sage-grouse survival and population persistence. Therefore, managers require accurate and high-resolution maps of conifer distribution and abundance across broad geographic extents to help guide land management decisions that better target areas for conifer treatment projects, especially for sage-grouse habitat restoration in sites characterized by scattered, isolated trees. However, previously available remotely sensed layers at regional extents lacked the spatial resolution or accuracy to meet this need. Researchers developed a framework to map conifers at a high resolution (1 m) across the majority of Nevada and northeastern California using image classification. Digital orthophoto quad tiles from the National Agriculture Imagery Program (2010 and 2013) were used to classify conifers using an automated feature extraction process.. Overall accuracy was more than 86% across all mapped areas for both image validation and ground referencing methods. Four sets of full-extent maps were provided for land managers: (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at 1-meter resolution; (3) a 900-meter resolution raster representing percentages of conifer canopy cover within each cell; and (4) 1-meter resolution canopy cover classification rasters derived from a 50-meter radius moving window analysis. These products improve upon or complement existing conifer maps for the western U.S. and will facilitate sagebrush ecosystem restoration through an accurate understanding of conifer distribution and abundance at multiple spatial scales.




Spatial layers produced using automated feature extraction methods across greater sage-grouse habitat in Nevada and California depict: a) conifer presence or absence at a 1-meter resolution, b) continuous conifer canopy cover at 900-meter resolution raster, and c) example of using canopy cover bins at a 1-meter resolution produced from a 50-meter radius moving window to depict progressive phases of conifer expansion.


Author Name
Peter Coates
Author Email