Analysis of ALOS PALSAR and TerraSAR-X Data for Protected Area Mapping: A case of the Bwindi Impenetrable National Park-Uganda J.R Otukei a, b  T. Blaschke b , M. Collins c , Y. Maghsoudi c a Department of Geomatics and Land Management, Makerere University, P.O. Box 7062 Kampala Uganda b Centre for GeoInformatics, University of Salzburg, Hellbrunerstrasse 34, 5020 Salzburg Austria c Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada Abstract-The main purpose of this study was to investigate the potential of Quad-pol L-band ALOS PALSAR and Dual-pol X-band TerraSAR (TSX) data, as well as derived TSX image texture for land cover mapping. A per- pixel classification was performed using non-parametric decision tree method. Classifications involving the HH, VV and HH/VV TSX polarimetric band(s) resulted in kappa indices of 0.4326, 0.3577 and 0.4657 respectively. In contrast, classifications involving the HH, HV, VV, HH/HV, VV/HV, HH/VV, HH/HV/VV and HH/HV/VH/VV bands of ALOS PALSAR data resulted in corresponding kappa indices of 0.2972, 0.3395, 0.3269, 0.7141, 0.7058, 0.4697, 0.7311 and 0.7177. A further analysis was carried out using the image textures derived from the HH polarisation of TSX data. Three different categories of textures were analysed: SAR specific (SARTEX), textures based on grey level concurrence matrices (GLCM) and textures based on SAR image histogram (HISTEX). These resulted in kappa indices of 0.6740, 0.6655 and 0.7166 respectively. Moreover, a classification using two original TSX polarisations provided a kappa index of 0.4657. This showed an improvement in the classification accuracies by 45%, 43% and 52% respectively. On the basis of the resulting accuracies, it can be concluded that analysis of data with high polarisation increases the classification accuracy of land cover information derived from SAR data. Furthermore, inclusion of derived SAR textures in the classification process, provide a potential for improved land cover identification and mapping in the tropics. 1 Introduction The Bwindi Impenetrable National Park (BINP) is facing pressure due to demand for arable land and habitat resources [1]. While the land cover within the protected core zone is still undisturbed, the surrounding areas, originally gazetted as forest reserves, have been completely cleared for cultivation. The conversion of tropical forests in areas such as the BINP into other land cover types has severe long term environmental and social economic consequences both locally and globally [2]. In order to mitigate the effects of global warming as well as protect the wide range of biodiversity, there is need to conserve the forests cover. This can be supported through accurate and up-to-date land cover information. However, the production of accurate and up-to-date thematic land cover maps in the tropical environments is hindered by many factors including the high costs and cloud cover [3]. Data from Synthetic Aperture Radar (SAR) systems are envisaged to play a key role for mapping and monitoring of protected areas, especially in tropical areas with persistent cloud cover [4-7]. This is due to the ability to acquire data 348 978-1-4577-1005-6/11/$26.00 ©2011 IEEE IGARSS 2011