MAPPING LAND COVER CHANGE AND MODELLING ITS IMPACTS ON THE INUNDATION RESPONSES OF THE AGUSAN MARSH, MINDANAO, PHILIPPINES

Abstract. Monitoring of environmental changes is one of the most popular applications of satellite remote sensing. In this study, we applied satellite remote sensing to map and monitor changes in land cover of Agusan Marsh, one of the most ecologically significant wetlands, and an important region of biodiversity in the Philippines. Multi-temporal land cover maps of the Agusan Marsh over a 22-year period from 1995 to 2017 were generated through Maximum Likelihood classification of Landsat 5, TM, ETM+ and OLI images. Post-classification change detection of the land-cover maps showed that more than 60% of the marsh is naturally vegetated during the mapping period. Agricultural/cultivated areas were the second dominant land cover and were found to be increasing through the years while wetland vegetation generally showed a downward trend. Two-dimensional (2D) flood modelling using HEC RAS was also performed to estimate how the Agusan Marsh would react to extreme rainfall events in terms of depth and extent of inundations. Simulation results showed that the Agusan Marsh responded differently for each year in terms of inundation depth and extent. These results of the combined satellite remote sensing + 2D modelling approach implemented in this study would be essential to better understand landscape patterns in the Agusan Marsh, including changes and interactions between human activities and natural phenomenon such as flooding for proper marsh management and improved decision-making.