Bangladesh has undergone dramatic land use and land cover changes (LULCC) in recent years, but no quantitative analysis of LULCC drivers at the national scale exists so far. Here, we quantified the drivers of major LULCC in combination with biophysical and socioeconomic observations at the sub-district level. We used Landsat satellite data to interpret LULCC from 2000 to 2010 and employed a Global Surface Water Dataset to account for the influences of water seasonality. The results suggest that major LULCC in Bangladesh occur between agricultural land and waterbodies and between forest and shrubland. Exclusion of seasonal waterbodies can improve the accuracy of our LULCC results and driver analysis. Although the gross gain and loss of agricultural land are large on the local scale, the net change (gross gain minus gross loss) at a country scale is almost negligible. Climate dynamics and extreme events and changes in urban and rural households were driving the changes from forest to shrubland in the southeast region. The conversion from agricultural land to standing waterbodies in the southwest region was mainly driven by urban household dynamics, population growth, distance to cities and major roads, and precipitation dynamics. This study, which is the first effort accounting for water seasonality and quantifying biophysical and socioeconomic drivers of LULCC at the national scale, provides a perspective on overall LULCC and underlying drivers over a decadal time scale and national spatial scale and can serve as a scientific basis for developing land policies in Bangladesh.

Arid and semi-arid areas in North China are facing the challenge of a rising aeolian desertification risk (ADR) due to the intertwined effects of complex natural processes and intensified anthropogenic activities. An accurate quantitative assessment of the relationship between ADR and its determinants is beneficial for understanding the driving mechanisms of aeolian desertification and for controlling future desertification. Previous studies have failed to quantify the relative role of determinants driving ADR and have been limited in assessing their interactive impacts. In this study, a spatial variance analysis-based geographical detector methodology is used to quantify the effects of geological, physical, and human factors on the occurrence of ADR in an area characterized by mountains and hills in northern China. It is found that soil type, precipitation, and wind velocity are the major determinants of ADR, which implies that geological and physical elements (e.g., soil attribute) and climatic factors (e.g., precipitation and wind velocity) rather than human activities have played a greater role in the incidence of ADR. Particularly, the results show that the interaction of various determinants causes significant non-linearly enhanced impacts on the ADR. The findings of our study will assist local inhabitants and policy makers in developing measures for wind prevention and sand control to mitigate the effects of desertification in the region.