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ContextQuantifying landscape-scale vegetation disturbances by surface coal mining (SCM) is crucial for assessing and mitigating its negative impacts on the environment. Methods for detecting such disturbances in woody ecosystems exist, but these methods do not work well for deserts and grasslands in arid and semiarid regions because of their sensitive responses to precipitation variations.ObjectivesThe objective of this study was to develop a new index to reliably detect the locations and spatial extents of SCM-induced vegetation disturbances in dryland regions in the face of fluctuating precipitation.MethodsWe have developed a vegetation disturbance index (VDI) that combines MODIS EVI data with precipitation data to detect vegetation disturbances by SCM on the Mongolian Plateau during 2000-2015. The VDI is computed by comparing vegetation production per unit precipitation for a given year with a multi-year mean, and by considering distances from coal-mining areas.ResultsOur results show that the VDI was able to adequately distinguish vegetation disturbances by SCM from climate-driven vegetation changes in five selected sites across the Mongolian Plateau.ConclusionsThe VDI provides an effective tool for quantifying the locations, spatial extents, and severity of vegetation disturbances by SCM in arid and semiarid regions.