TREE PLANTING PRIORITIZATION IN NATIONAL CAPITAL REGION, PHILIPPINES USING REMOTE SENSING, ANALYTIC HIERARCHY PROCESS AND GIS
Keywords: urban green spaces, AHP, planting priority index, spatial statistics, Moran’s I
Abstract. The need for trees in cities is rapidly increasing because of global warming, rapid population growth, and urbanization. To maximize the benefits of trees, areas of greatest need should be identified and prioritized. In this study, a geospatial framework for tree planting prioritization is developed for NCR using remotely sensed datasets, AHP, and GIS. A Planting Priority Index (PPI) for NCR is derived based on five criteria with corresponding weights calculated based on ratings from 18 experts – air quality (25.2%), tree cover (23.8%), land cover (17.8%), population (17.4%), and land surface temperature (15.8%). The AHP resulted in a consistency ratio (CR) value of 1.7% and a consensus value of 53.2%. PPI values were calculated and statistically significant prioritization clusters and outliers were identified using Anselin Local Moran’s I statistics. The resulting PPI and cluster maps showed that the high-priority areas for tree planting clustered near the region’s center and northwest portion covering the cities of Malabon, South Caloocan, Navotas, Quezon City, Marikina, San Juan, and Mandaluyong, while the low priority areas were found mostly along the region’s outskirts at cities of Pasay, Las Piñas, Muntinlupa, Taguig, Valenzuela, and North Caloocan. The generated maps showing PPI values across the region may aid local government agencies and environmental organizations in evaluating and recalibrating their local greening programs. The workflow presented in this study can also be adopted in other regions with localized variables and site-specific goals relevant to tree planting and greening programs.