LAND-COVER MAPPING: A REMOTE SENSING APPROACH

SPOT (Systeme Pour l'Observation de la Terre) XS (multi-spectral) satellite sensor data were evaluated for mapping different land-covers/uses in the suburb of Rawalpindi to assess the impact of urbanization on the scrub forest dominated by Acacia modesta. Various data layers were generated and co-registered with the land-cover map. Field data collected using GPS were employed to evaluate the land-cover map. The results showed that several land-cover types can easily be identified and mapped while some land-covers were difficult to identify, as they could be confused with each other due to their similar spectral reflectance. Thirteen land-covers were mapped using fuzzy supervised likelihood classifier. The statistical evaluation of the classified image indicated an overall accuracy of 72.86 % with a kappa statistics of 0.70. The results suggest that extensive and massive clearance of reserve forest occurred in most of the forest stands. The existing scrub forest is becoming smaller and fragmented; only patches of mature forest are left in forest stand 6, 7 and 8, which are under threat from urban encroachment evincing that soon the remaining forest will be engulfed by concrete jungle if Rawalpindi Authority and the Forest Department of Rawalpindi District does not take immediate auction as a priority to save this national heritage. Cover types map derived could be used as a valuable base for the monitoring changes in land-cover pattern and deforestation assessment of the scrub forest of the study site