Using geobia and data fusion approach for land use and land cover mapping

Abstract

Land Use and Land Cover (LULC) maps play an important role in an environmental modelling, and for many years efforts have been made to improve and streamline the expensive mapping process. The aim of the study was to create LULC maps of three selected water catchment areas in South Poland using a Geographic Object-Based Image Analysis (GEOBIA) in order to highlight the advantages of this innovative, semi-automatic method of image analysis. The classifcation workfow included: multi-stage and multi-scale analyses based on a data fusion approach. Input data consisted mainly of BlackBridge (RapidEye) high resolution satellite imagery, although for distinguishing particular LULC classes, additional satellite images (LANDSAT TM5) and GIS-vector data were used. Accuracy as- sessment of GEOBIA classifcation results varied from 0.83 to 0.87 (Kappa), depending on the specifc catchment area. The main recognized advantages of GEOBIA in the case study were: performing of multi-stage and multi-scale image classifcation using different features for specifc LULC classes and the ability to using knowledge-based classifcation in conjunction with the data fusion approach in an effcient and reliable manner.