Simulating National-scale Deforestation in the Philippines Using Land Cover Change Models
Jean Meir Jardeleza*, Charlotte Kendra Gotangco, and
Maria Aileen Leah Guzman
Department of Environmental Science, 3/F Manila Observatory,
Ateneo de Manila University, Quezon City 1108 Philippines
After the year 2010, a century of rapid decline in Philippine forest cover was reversed due to a deliberate National Greening Program (NGP). Drivers that can sustain or counter this increase can be better investigated through the help of land change models. However, such models are not yet in mainstream use for planning in the Philippines. Hence, this study used two models – FOREST-SAGE and GEOMOD – to simulate forest conditions based on anthropogenic drivers and to evaluate model applicability in the Philippines. The performance of each model was assessed using the root-mean-square error (RMSE), mean absolute error (MAE), Kappa, national average tree cover percentage, and common deforestation hotspots with reference datasets. Validation with Climate Change Initiative Land Cover dataset (CCI-LC) yielded similar results between the models: 2015 tree cover maps with RMSE of 22–25% tree cover, MAE of 10–12% tree cover, and moderate agreement with reference map based on Kappa (0.4–0.6); and 2010–2015 change maps with RMSE of 8–9% tree cover, MAE of 1–2% tree cover, and agreement due to chance based on Kappa (0.01–0.03). Validation with MODerate Resolution Imaging Spectroradiometer-Vegetation Continuous Field (MODIS-VCF) maps yielded similar MAE results (10% tree cover) between the models. Validating FOREST-SAGE end-time and change maps with MODIS-VCF yielded better RMSE results than GEOMOD (RMSE of 13% tree cover for FOREST-SAGE; 22% tree cover for GEOMOD). However, GEOMOD tree cover maps yielded better Kappa than FOREST-SAGE (0.60 for GEOMOD; 0.01 for FOREST-SAGE). Results suggest that FOREST-SAGE is more applicable in the Philippines for provincial extent studies that aim to quantitively track forest cover change, while GEOMOD is more applicable for national extent studies that use categorical data. Results also suggest that input parameter settings must be improved to simulate spatial distribution of forest cover.
Changes within tropical forests in the past decades have received considerable attention due to the rapid rate of deforestation, affecting regional and global changes in biodiversity and climate (Mas et al. 2007, Li et al. 2016). One of the countries that underwent such rapid deforestation is the Philippines – from 70% of the country’s total land area in 1900 to 50% in 1950 and to less than 19% by 1990 (Kummer 1992). Although the decline in forest cover lessened in 2003 to 2010 (FMB, pers. comm., 13 Oct 2015), it was only after 2010 that a 3.29% annual increase in forest cover was observed (FAO 2015). The reported increase in Philippine forest cover has been attributed to the implementation of the NGP in 2011. The NGP was a deliberate attempt to increase forest cover by planting 1.5 billion trees covering about 15,000 km2 from 2011 to 2015. The program has been extended to 2028, through Executive Order No. 193 (Office of the President of the Philippines 2015), to cover an additional 71,000 km2 of unproductive and denuded land for reforestation and to sustain the forest cover increase from the initial NGP. Land use and land cover change (LULCC) models may be useful in attaining the goal to sustain forest cover by providing a cost-effective means of studying forests over massive spatial extents. . . . read more
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