A Remote Sensing Approach Abandoned Areas in the Classifcation Optimization of Land Use : A Case Study of Salaya, Phutthamonthon District, Nakhon Pathom

Abstract

This research proposes methodology to identify the Idle land found in agricultural zones of Phutthamonthon District, Nakhon Pathom using remote sensing data. The chosen remote sensing data for locating the Idle land plots is NDVI time-series imagery. It is found that the identified idle land plots have NDVI value close to zero. Its trend remains, approximately, at the same level for the whole period of the time. On the other hand, the agricultural areas possess a higher degree of NDVI variation. The NDVI values can reach to more than 0.5 during the growing season. The overall accuracy values are reported at a high level of 88.80 percent, 79.20 percent, and 77.80 percent when Maximum Likelihood Classifier, Mahalanobis Distance Classifier, and Spectral Angle Mapper Classifier are in use, respectively. The classification accuracy confirms that the proposed methodology can be used to identify the idle land of the study area. It is hope that the method proposed in this study can be applied to other similar agricultural areas.