The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII-4/C7 APPLICATION OF OBJECT BASED IMAGE ANALYSIS FOR FOREST COVER ASSESSMENT OF MOIST TEMPERATE HIMALAYAN FOREST IN PAKISTAN

The study aims at developing forest cover inventory from high resolution satellite imagery (0.6m) of Ayubia National Park, NWFP, Pakistan. The 3372 ha study area is one of the best examples of existing moist temperate Himalayan forest in Pakistan. Landscapes composed of large number of heterogeneous and complex elements, exhibit multi-scale hierarchical dependencies. A multi-scale object based image analysis has been carried out for the forest cover assessment of the park. Image objects representing homogenous landscape components were delineated using image segmentation routine. This approach allows efficient inclusion of spatial concepts by segmenting the digital image according to image resolution and scale of expected objects. Following the multiresolution segmentation a classification tree was developed that used a fuzzy nearest neighbor classifier to assign respective class to image segments at their respective scale. After manual classification of unclassified or misclassified objects, overall accuracy of the final out put was around 90%. Keeping in view the operational advantages and limitation of object based technique of Definiens, the proposed methodology can be easily replicated to other parts of moist temperate Himalayan forests in Pakistan. In order to meet growing needs of harmonized land cover system, class definition of FAO’s Land Cover Classification System (LCCS) has been adopted. • Corresponding author: Sawaid Abbas, Remote Sensing Analyst, WWF – Pakistan. [email protected]