Climate change and increasing urbanization are two primary factors responsible for the
increased risk of serious flooding around the world. The prediction and monitoring of the …

Accurately mapping land use/land cover changes (LULCC) and forest disturbances provides
valuable information for understanding the influence of anthropogenic activities on the …

The objective of this study was to develop a theoretical framework based on machine
learning, the hydrodynamic model, and the analytic hierarchy process (AHP) to assess the …

Flooding is one of the most widespread and catastrophic natural disasters. The exposure of
cropland to floods is directly related to the quality of cropland and food security, so it is …

Land consolidation (LC) in China is an important means by which we can increase the
quantity and improve the quality of cultivated land. At present, large areas of cultivated land …

Flood models based on traditional hydrodynamic modeling encounter significant difficulties
with real-time predictions, require enormous computational resources, and perform poorly in …

The analysis of temporal and spatial variability in risk has garnered significant research
attention, particularly regarding flash flood disasters in the context of warming and wetting …

Spatiotemporal land use change evaluation and quantification are essential for supporting
and enhancing land use policies and for the sustainable management of land resources. To …

We assess the economic and environmental impacts on agriculture of flooding under
projected climate change, including land-use change as an adaption response to floods …

Natural disasters such as floods can significantly impact agriculture, especially in rice crop
areas. The synergy of optical and synthetic aperture radar (SAR) images can be utilized to …