South and Southeast Asia (SSEA) has been a hotspot for land use and land cover change (LULCC) in the past few decades. The identification and quantification of the drivers of LULCC are crucial for improving our understanding of LULCC trends. So far, the biophysical and socioeconomic drivers of forest change have not been quantified at the regional scale, particularly for SSEA. In this study, we quantify the biophysical and socioeconomic drivers of forest change on a country-by-country basis in SSEA using an integrated quantitative methodology, which systematically accounts for previously published driver information and regional datasets. We synthesize more than 200 publications to identify the drivers of the forest change at different spatial scales in SSEA. Subsequently, we collect spatially explicit proxy data to represent the identified drivers. We quantify the dynamics of forest and agricultural land from 1992 to 2015 using the Climate Change Initiative (CCI) land cover data developed by the European Space Agency (ESA). A geographically weighted regression method is employed to quantify the spatially heterogeneous drivers of forest change. Our results show that socioeconomic drivers are more important than biophysical drivers for the conversion of forest to agricultural land in South Asia and maritime Southeast Asia. In contrast, biophysical drivers are more important than socioeconomic drivers for the conversion of agricultural land to forest in maritime Southeast Asia and less important in South Asia. Both biophysical and socioeconomic drivers contribute approximately equally to both changes in the mainland Southeast Asia region. By quantifying the dynamics of forest and agricultural land and the spatially explicit drivers of their changes in SSEA, this study provides a solid foundation for LULCC modeling and projection.
- Johnson's Relative Weight
- South and Southeast Asia
- geographically weighted regression
ASJC Scopus subject areas
- Global and Planetary Change
- Environmental Chemistry
- General Environmental Science