

Townsend, PA; Singh, A; Foster, JR; Rehberg, NJ; Kingdon, CC; Eshleman, KN; Seagle, SW (2012). A general Landsat model to predict canopy defoliation in broadleaf deciduous forests. REMOTE SENSING OF ENVIRONMENT, 119, 255265. Abstract Defoliation by insect herbivores can be a persistent disturbance affecting ecosystem functioning. We developed an approach to map canopy defoliation due to gypsy moth based on site differences in Landsat vegetation index values between nondefoliation and defoliation dates. Using field data from two study areas in the U.S. central Appalachians and five different years (2000, 2001, 2006, 2007, and 2008), we fit a sigmoidal model predicting defoliation as a function of the difference in the vegetation index. We found that the normalized difference infrared index (NDII, [Band 4 Band 5]/[Band 4 + Band 51) and the moisture stress index (Band 5/Band 4) worked better than visiblenear infrared indices such as NDVI for mapping defoliation. We report a global 2term fixedeffects model using all years that was at least as good as a mixedeffects model that varied the model coefficients by year. The final model was: proportion of foliage retained =1/(1 + exp(3.057  31.483. [NDIIbase year NDIIdisturbance year]). Crossvalidation by dropping each year of data and subsequently refitting the remaining data generated an RMS error estimate of 14.9% defoliation, a mean absolute error of 10.8% and a crossvalidation R2 of 0.805. The results show that a robust, general model of percent defoliation can be developed to make continuous rather than categorical maps of defoliation across years and study sites based on field data collected using different sampling methods. (C) 2012 Elsevier Inc. All rights reserved. DOI: 00344257 ISSN: 10.1016/j.rse.2011.12.023 