A Comparison of LUCC Detection Algorithms in a Mesoamerican Lowland Tropical Forest

Abstract

land use and land cover changes occur throughout the world, but none is more concerning than tropical deforestation, much of it for agricultural purposes . rural-rural frontier migrant farmers such as those colonizing the sierra del lacandón national Park in Petén, guatemala act as a primary direct agent in this land cover conversion . this paper seeks to compare three different algorithms for monitoring changes in forested land cover, making use of freely available remotely sensed landsat images from two years, 1991 and 2000 . in the intervening 9 years, some forested land was converted to cropped, pasture, or fallow land, while other areas experienced no change . this paper contains a detailed description of the methods employed for three different change detection techniques, producing a total of five land change maps: multidate principal components analysis (PcA), normalized difference vegetation index (nDvi) image differencing, and brightness greenness wetness (BgW) image differencing . of the five land change maps produced, the greenness component of the BgW transformation had the highest overall accuracy, at 86%, and is conservative in detecting change . the amount of change detected by this algorithm represents approximately 300 km 2 of forest loss, or 11 .9% of the area examined .