Assessing agricultural drought at a regional scale using LULC classification, SPI, and vegetation indices: case study in a rainfed agro-ecosystem in Central Mexico

摘要

Satellite observations of the spectral properties of vegetation can provide insights on crop conditions and yield, and, furthermore, can monitor the impact of droughts. In the case of rainfed crops grown for self-sufficiency, a drought can result in significant human suffering, highlighting the need to understand how droughts affect the landscape in such regions. This paper uses remote sensing to assess the phenomenological impacts of two isolated droughts, distinguishing the response of different vegetation covers in semiarid developing regions where rainfed agriculture is common. Using the standardized precipitation index, one normal and two dry years were selected (2000, 2005, and 2011, respectively). An original protocol for land use land cover (LULC) classification that combines climatic, topographic, and reflectance information from 18 Landsat ETM+ images was applied to subsequently distinguish drought effects in different classes through the selected years. Finally, two vegetation indices (normalized difference vegetation index (NDVI) and vegetation condition index (VCI)) were calculated to detect drought severity impacts over the different LULC classes. This approach was tested in Central Mexico and provided accurate information on the location and extent of areas affected by drought. The proposed approach can be used as a system for drought risk management in semi-arid developing regions.