Rapid Classification of Landsat TM Imagery for Phase 1 Stratification Using the Automated NDVI Threshold Supervised Classification (ANTSC) Methodology

Abstract

FIA annual inventories require rapid updating of pixel-based Phase 1 estimates. Scientists at the Southern Research Station are developing an automated methodology that uses a Normalized Difference Vegetation Index (NDVI) for identifying and eliminating problem FIA plots from the analysis. Problem plots are those that have questionable land use/land cover information. Four Landsat TM scenes in Georgia have been classified using this methodology. A cross-validation approach was used to assess accuracy. The results are compared with an alternative methodology: the Iterative Guided Spectral Class Rejection (IGSCR) methodology.

Parent Publication

• Proceedings of the fourth annual Forest Inventory and Analysis symposium

Citation

Cooke, William H.; Jacobs, Dennis M. 2005. Rapid Classification of Landsat TM Imagery for Phase 1 Stratification Using the Automated NDVI Threshold Supervised Classification (ANTSC) Methodology. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J., eds. Proceedings of the fourth annual forest inventory and analysis symposium; Gen. Tech. Rep. NC-252. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station. 81-86