Identification and separation of massive and debris lime stones by integrated application of remote sensing and geomorphology approaches (Case study: Bahadoran region in Yazd province)

Mountains are usually formation origin of their neighbor land surface features such as hillsides and plains. In these situations and due to spectral fusion of different land attributes, remote sensing (RS) technique cannot separate lithology units of mountainous regions from their neighbor areas. Therefore, some problems and errors may occur in application of RS technique for generation of geology maps and in separation of these units from other similar units. These errors almost arise from carrying and propagation of primary clastic materials from mountain ranges to hillsides and their surrounding land surfaces. These regions almost have similar spectral signatures and therefore, as an example, identification of massive from debris lime stones through RS technique becomes a challenge. Main objective of this study is to integrate RS and geomorphology approaches for identification of different geomorphology units and finally separation of debris lime stones from massive lime stones in Bahadoran region, Yazd province. For this purpose, a Landsat ETM+ image was acquired together with band ratios, principal component analysis and factor analysis approaches to generate lime stone distribution map. Additionally a knowledge-based image interpretation approach was used for recognition of lithology units and generation of a new limestone distribution map. The first map then was compared with the second one by Kappa statistics. Results of this study show that the second approach (integration of RS and geomorphology sciences) can better generate the lime stone distribution map compared with the first one. Kappa statistics of the two approaches were 0.73 and 0.51, respectively.