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Title: Assessing alternative measures of tree canopy cover: Photo-interpreted NAIP and ground-based estimates

Author: Toney, Chris; Liknes, Greg; Lister, Andy; Meneguzzo, Dacia

Date: 2012

Source: In: McWilliams, Will; Roesch, Francis A. eds. 2012. Monitoring Across Borders: 2010 Joint Meeting of the Forest Inventory and Analysis (FIA) Symposium and the Southern Mensurationists. e-Gen. Tech. Rep. SRS-157. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 209-215.

Publication Series: Paper (invited, offered, keynote)

   Note: This article is part of a larger document. View the larger document

Description: In preparation for the development of the National Land Cover Database (NLCD) 2011 tree canopy cover layer, a pilot project for research and method development was completed in 2010 by the USDA Forest Service Forest Inventory and Analysis (FIA) program and Remote Sensing Applications Center (RSAC).This paper explores one of several topics investigated during the NLCD pilot. We compared estimates of tree canopy cover derived by photo-interpretation (PI) of 1-m resolution NAIP imagery to modeled estimates based on field-measured tree data collected on FIA plots in five study areas in Georgia, Michigan, Kansas, Utah, and Oregon, and to direct measurements of canopy cover by line intercept on FIA plots in Utah only. Photo-interpreted NAIP overestimated tree canopy cover (+10 to +20 percent canopy cover) at forested FIA plot locations compared with ground-based estimates derived from stem-mapped tree data or line intercept field measurements. Oblique viewing angles at sample locations away from the image nadir, and excessive shadowing in some NAIP images, could be the primary reasons for overestimation of canopy cover by PI. We also examined canopy cover estimates derived from NAIP imagery using an automated algorithm implemented in image processing software, as an alternative to manual PI by humans. This initial test showed that automated PI of NAIP images by image analysis could be a feasible approach for generating canopy cover data at reduced time and cost, but the current rule set exacerbated the problem of overestimation.

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Citation:


Toney, Chris; Liknes, Greg; Lister, Andy; Meneguzzo, Dacia 2012. Assessing alternative measures of tree canopy cover: Photo-interpreted NAIP and ground-based estimates. In: McWilliams, Will; Roesch, Francis A. eds. 2012. Monitoring Across Borders: 2010 Joint Meeting of the Forest Inventory and Analysis (FIA) Symposium and the Southern Mensurationists. e-Gen. Tech. Rep. SRS-157. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 209-215.

 


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