The integrated remote sensing (RS) and geographic information system (GIS) approach was utilized in this study to classify land use and land cover (LULC), detect changes based over time, and identify transition trends in the Marikina sub-watershed, Laguna de Bay watershed, Philippines. Landsat 5 Thematic Mapper (TM) imageries acquired in 1999 and 2006 were pre-processed and classified using a supervised classification technique with maximum likelihood classifier algorithm in RS and were used to develop maps of the sub-watershed and sub-subwatershed levels in a GIS platform. LULC change analysis revealed that, from 1999 to 2006, significant changes occurred in the sub-watershed as indicated by the increase of agricultural (11.76%) and orchard (4.52%) areas at the expense of brushland (16.56%) areas. Other LULC such as water bodies, built-up, forest, and grassland remain almost unchanged. In the sub-subwatershed level, Tayabasan experienced minimal change, whilst Tanay had the most transitions. Overall accuracy and kappa statistics were then derived using the confusion matrix, which resulted in 96.15% and 95.49% for 1999 imagery, and 93.82% and 92.73% for 2006 imagery, respectively. LULC persistence and transition trends were analyzed using land change modeler, while the Markov chain model has been utilized to predict the LULC distribution in 2020 pertinent to rates of change from 1999 to 2006. This study contributes not only to the understanding of the past and present landscape of the sub-watershed, but also provides an idea of the areas that need rehabilitation for the formulation of suitable mitigation measures and strategies toward the sustainable management of the sub-watershed.
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