Coupling spectral unmixing and multiseasonal remote sensing for temperate dryland land-use/land-cover mapping in Minqin County, China

Abstract

Temperate dryland ecosystems in China are undergoing accelerated changes due to natural and anthropogenic disturbances. Using the Minqin oasis as a case study area, this article examined linear spectral mixture analysis (LSMA) with the fixed four-image endmember (EM) model comprising sand, green vegetation, saline land, and dark materials (i.e. the degraded symptoms/EMs) for temperate dryland land-use and land-cover mapping. Dryland covers defined by landscape seasonality of the four EMs at the subpixel level are more easily interpreted to achieve acceptable accuracy, and allow better understanding of the processes of land degradation, such as two distinct salt/water movements were found in the study area. The Minqin oasis faces a significant challenge that requires a long-term monitoring system to understand the relationship between land-use decisions and ecological consequences. The approach developed with the mutiseasonal LSMA, representing dryland land-cover seasonality with the common surface degradation types (i.e. the four EMs) in a tree-structure framework, promises a robust and operative tool for land degradation assessment and monitoring and would be applied in a more different dryland environment in the future.