Understanding the driving forces of land use/cover change (LUCC) is a requisite to mitigate and manage effects and consequences of LUCC. This study aims to analyze drivers of LUCC in New England, USA. It combines meta-study, GIS, and machine learning to identify the important factors of LUCC in the area. Firstly, we conducted a meta-study of the research on LUCC in the New England area and specifically focused on the driving forces analysis. The meta-analysis revealed that the LUCC studies in the research area were highly related with many other research topics, and population and economic factors were the most mentioned drivers of the LUCC. The drivers of LUCC in this study area for the past several decades were relatively well analyzed. However, the study of the main driving forces of recent LUCC is lacking. Then, the determinants of LUCC for the recent years were quantitatively assessed using the random forests (RF) model along with geospatial data processing. Two planning regions in Connecticut and one planning region in Massachusetts were selected to serve as the case study areas. Investigated variables included environmental and biophysical variables, location measures of infrastructure and existing land use, political variables, and demographic and social variables. These drivers were examined for their relations with LUCC processes. Their importance as driving forces was ranked by the RF method. The results show both consistency and inconsistency between the meta-analysis and the RF method. We found that this mixed method can enhance our understanding of driving forces of LUCC and improve the selection quality of important drivers for modeling LUCC. With more solid information, better land management advices for sustainable development may also be provided.
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