LAND USE AND LAND COVER PREDICTION AND ITS IMPACT ON SURFACE RUNOFF
Keywords:
Land use and land cover prediction, surface runoff estimation, geoinformatics, CA-Markov model, Land Change ModelerAbstract
Due to the rapid growth of Mahasarakham University (MSU), land use and land cover (LULC) change takes place on the campus and in its vicinity, and various types of environmental impacts occur in the area. The Mmain objectives are to quantify the characteristics of the LULC change, to identify an optimum LULC change model for a LULC prediction, and to examine the effect of the LULC changes on the surface runoff at in Mueang Maha Sarakham and Kantharawichai districts of Maha Sarakham province. The 3 main components of the research methodology are the LULC assessment by visual interpretation, an optimum predictive LULC change model identification, and the impact of the LULC changes on surface runoff. The study revealed that the dominant LULC type during 2001-2011 was agricultural land, while the urban and built-up areas had been continuously increased by conversion of agricultural and forest lands. The overall accuracy and K hat coefficient for the LULC data in 2011 were 98.12% and 96.02%, respectively. It was found that an optimum predictive LULC change model was the CA-Markov model which provided higher accuracy than the Land Change Modeler. Also, most of the urban and built-up area sub-classes during 2001-2021 had continuously increased except for the dormitory sub-class, while the agricultural land, except the field crop, had continuously decreased. This study also demonstrated that there is strongly related the change of the urban area on has a strong effect on the surface runoff depth. Likewise, the level of urbanization is strongly associated with the mean surface runoff depth zonation. Evidence from the study suggests that the LULC changes have an effect on the surface runoff characteristics. In conclusion, it appears that geoinformatics technology and the LULC change model can be used as tools for a LULC change and environmental impact assessment.
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