Research Papers

Estimating live forest carbon dynamics with a Landsat-based curve-fitting approach

[+] Author Affiliations
Todd A. Schroeder

Department of Forest Science, Oregon State University, College of Forestry, Corvallis, OR 97331

Andrew Gray

Pacific Northwest Research Station, USDA Forest Service, Corvallis Forest Sciences Laboratory, Corvallis, OR 97331

Mark E. Harmon

Department of Forest Science, Oregon State University, College of Forestry, Corvallis, OR 97331

David O. Wallin

Department of Environmental Science, Western Washington University, Huxley College of the Environment, Bellingham, WA 98225

Warren B. Cohen

Pacific Northwest Research Station, USDA Forest Service, Corvallis Forest Sciences Laboratory, Corvallis, OR 97331

J. Appl. Remote Sens. 2(1), 023519 (May 9, 2008). doi:10.1117/1.2937821
History: Received December 21, 2007; Revised April 25, 2008; Accepted May 5, 2008; May 9, 2008; Online May 09, 2008
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Abstract

Direct estimation of aboveground biomass with spectral reflectance data has proven challenging for high biomass forests of the Pacific Northwestern United States. We present an alternative modeling strategy which uses Landsat's spatial, spectral and temporal characteristics to predict live forest carbon through integration of stand age and site index maps and locally calibrated Chapman-Richards curves. Predictions from the curve-fit model were evaluated at the local and landscape scales using two periods of field inventory data. At the pixel-level, the curve-fit model had large positive bias statistics and at the landscape scale over-predicted study area carbon for both inventory periods. Despite the over-estimation, the change in forest carbon estimated by the curve-fit model was well within the standard error of the inventory estimates. In addition to validating the curve-fit models carbon predictions we used Landsat data to evaluate the degree to which the field inventory plots captured the forest conditions of the study area. Landsat-based frequency histograms revealed the systematic sample of inventory plots effectively captured the broad range of forest conditions found inthe study area, whereas stand age trajectories revealed a temporally punctuated shift in landuse which was not spectrally detected by the inventory sample.

© 2008 Society of Photo-Optical Instrumentation Engineers

Topics

Carbon

Citation

Todd A. Schroeder ; Andrew Gray ; Mark E. Harmon ; David O. Wallin and Warren B. Cohen
"Estimating live forest carbon dynamics with a Landsat-based curve-fitting approach", J. Appl. Remote Sens. 2(1), 023519 (May 9, 2008). ; http://dx.doi.org/10.1117/1.2937821


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