A dryland cover state mapping using catastrophe model in a spectral endmember space of OLI: a case study in Minqin, China

Abstract

ABSTRACTAlternative state theory with catastrophe conceptual model is very attractive for dryland zero net land degradation (ZNLD) management, but practically challenging for mapping cover state and pathway with conventional approaches. This paper developed a methodological framework in the generic spectral endmember space (SVD, soils and substrates, vegetation, and dark surface endmembers ) of Landsat-8 OLI (operational land imager) imagery to concretize the catastrophe model of dryland cover state based on the co-development of plant and soil variables in a landscape. A cover function index (LCI) was proposed together with cover type growth form as cover variables in multi-seasonal SVD space. Furthermore, ecological site (ES) and topographic wetness index (TWI) were used as the landscape variables. The four variables as the explanatory variates, soil organic matter (SOM) as a slow response variable of dryland cover state, were explored by classification and regression trees (CART) for the state space. Using the Minqin dryland system in China as a case study, CART explored 65.9% amounts of SOM variance of 85 training samples with the four explanatory variables, and the measured SOM had liner relationship with CART predicted SOM at 0.05 significant level with the explained 39% SOM variance for 10 test samples. In the learned transparent tree, the two alternative stable states were identified correctly and validated by another soil intrinsic clay content variable independently, one was the current highest average SOM (26.757 g kg−1) of perennial forest/shrub covers, the other was the bared or sparse vegetation cover with low average SOM (≤8.518 g kg−1) as a critical SOM limit in a given ecological site type. The mean clay content of the undesirable alternative states was all below 60 g kg−1 with severe soil physical degradation, and had a clear breaking gap with other states. Moreover, the SOM-LCI plane projected the unstable states being folded in the basins of the attraction of two alternative stable states (i.e. 0.39–0.76 LCI) with relative resilience analysis of pathways. In the 10 test sites, only 1 site of the state was not predicted correctly. The results suggest the model has a level of predictability for dryland cover state and its pathway. According to the estimated states, there has 12.74% study area improved and continued to recovering the desirable states, and the study area has already net improvement at the landscape level.Therefore, without the comparable series of historical data for adaptive management, the developed framework in SVD of Landsat imagery is a cost-effective and time-saving tool, which helps managers to assess and develop appropriate management with a more spatially diversified strategy for zero net land degradation using a space-for-time substitution in an era of unprecedented change.