TY - JOUR
T1 - Estimating regional forest cover in East Texas using Advanced Very High Resolution Radiometer (AVHRR) data
AU - Sivanpillai, Ramesh
AU - Srinivasan, R.
AU - Smith, Charles T.
AU - Messina, Michael G.
AU - Wu, X. Ben
N1 - Funding Information:
This study was conducted as part of the first author's doctoral dissertation research at Texas A&M University. Technical support provided by Mr. Thomas Spencer and Mr. Curt Stripling of Texas Forest Service, are gratefully acknowledged. We would like to extend our thanks to Dr. R. Jayakrishnan (Boyle Engineering Corporation, FL), Dr. P. Chen (BREC, TAMUS, Temple, TX) and Dr. B. Narasimhan (SSL, TAMU) for their valuable support to download and preprocess AVHRR data. We thank Mr. Damon Holzer (NOAA, WA) for his assistance with GIS data processing. Contributions of Dr. William Cooke III, USDA-Forest Service were valuable for successful completion of this research. Partial financial support was provided to the first author by the Texas Agricultural Experiment Station (TAES) and the Heep Foundation for conducting this study. We would like to thank the two anonymous reviewers for their valuable comments and suggestions.
PY - 2007/2
Y1 - 2007/2
N2 - This study tested the degree to which single date, near-nadir AVHRR image could provide forest cover estimates comparable to the phase I estimates obtained from the traditional photo-based techniques of the Forest Inventory and Analysis (FIA) program. FIA program is part of the United States Department of Agriculture-Forest Service (USFS). A six-county region in east Texas was selected for this study. Manual identification of ground control points (GCPs) was necessary for geo-referencing this image with higher precision. Through digital image classification techniques forest classes were separated from other non-forest classes in the study area. Classified AVHRR imagery was compared to two verification datasets: photo-center points and the USFS FIA plots. The overall accuracy values obtained were 67 and 71%, respectively. Analyses of the error matrices indicated that the AVHRR image correctly classified more forested areas than non-forested areas; however, most of the errors could be attributed to certain land cover and land use classes. Several pastures with tree cover, which were field-identified as non-forest, were misclassified as forest in the AVHRR image using the image classification system developed in this study. Recently harvested and young pine forests were misclassified as non-forest in the imagery. County-level forest cover estimates obtained from the AVHRR imagery were within the 95% confidence interval of the corresponding estimates from traditional photo-based methods. These results indicate that AVHRR imagery could be used to estimate county-level forest cover; however, the precision associated with these estimates was lower than that obtained through traditional photo-based techniques.
AB - This study tested the degree to which single date, near-nadir AVHRR image could provide forest cover estimates comparable to the phase I estimates obtained from the traditional photo-based techniques of the Forest Inventory and Analysis (FIA) program. FIA program is part of the United States Department of Agriculture-Forest Service (USFS). A six-county region in east Texas was selected for this study. Manual identification of ground control points (GCPs) was necessary for geo-referencing this image with higher precision. Through digital image classification techniques forest classes were separated from other non-forest classes in the study area. Classified AVHRR imagery was compared to two verification datasets: photo-center points and the USFS FIA plots. The overall accuracy values obtained were 67 and 71%, respectively. Analyses of the error matrices indicated that the AVHRR image correctly classified more forested areas than non-forested areas; however, most of the errors could be attributed to certain land cover and land use classes. Several pastures with tree cover, which were field-identified as non-forest, were misclassified as forest in the AVHRR image using the image classification system developed in this study. Recently harvested and young pine forests were misclassified as non-forest in the imagery. County-level forest cover estimates obtained from the AVHRR imagery were within the 95% confidence interval of the corresponding estimates from traditional photo-based methods. These results indicate that AVHRR imagery could be used to estimate county-level forest cover; however, the precision associated with these estimates was lower than that obtained through traditional photo-based techniques.
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U2 - 10.1016/j.jag.2006.05.002
DO - 10.1016/j.jag.2006.05.002
M3 - Article
AN - SCOPUS:33846132899
VL - 9
SP - 41
EP - 49
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
SN - 1569-8432
IS - 1
ER -
