Factors and their relationships affecting land use change during 1988-2007 and predicting future land use by clue-s model in Huai Thap Salao watershed, Changwat Uthai Thani

Abstract

GIS and remote sensing data interpretation, field investigation, and laboratory analysis were carried out to investigate dynamic spatial patterns of land use changes and to identify driving factors that caused land use changes during 1988-2007 in Huai Thap Salao watershed, Changwat Uthai Thani. Besides, the purpose of study was to simulate model of land use changes using CLUE-s model to predict the future land use change in current. Dynamic spatial patterns of land use changes in Huai Thap Salao watershed during 1988-2007 were detected from remote sensing interpretation and field surveys that were complied into a GIS database. Various maps were constructed from those relevant parameters derived from the database. Deforestation which the major change was mostly found in the central part (Huai Rabam stream) and the eastern part (Huai Thap Salao and Huai Rang stream) of Huai Thap Salao watershed. The affecting parameters, namely elevation, slope, mean annual precipitation, distance to streams, distance to roads, distance to villages and soil textures were analyzed by logistic regression analysis. The result revealed that the forest land had been changed to agriculture land and were related to the distance to villages and the distance to roads in Huai Thap Salao watershed during 1988-2007. The CLUE-s model was simulated from two scenarios, namely, scenario without restriction area and scenario with reserved area in 2027. Without restriction area, the result revealed that the highest rate of deforestation would be 63% (from previously 68% in 2007) and mostly in the central part of Huai Thap Salao watershed whereas with reserved area, it revealed that the mostly increased land use category would be urban and built-up land surrounding Amphoe Lan Sak in the eastern part of Huai Thap Salao watershed. The final results from this research can be used as a spatial data for decision making in handling, monitoring, and controlling the land use and forest management in order to enhance the land use and forest management efficiency.