Spatial simulations of soil content, storage, and quality indices in an archipelago off the Yangtze River Estuary, China

Abstract

Comprehensively revealing the spatial pattern of soil condition is vital for exploring the evolution mechanism of island ecosystem and providing reference for ecological maintenance. However, it is difficult to meet the demands of comprehensiveness and accuracy in mapping the soil condition in an archipelago that contains remote islands. Such an archipelago, namely, Shengsi Archipelago off the Yangtze River Estuary, China, was selected as the study area. Field survey was conducted on part of islands that have relatively high accessibility in the archipelago, and remote sensing data that cover the entire study area was adopted. An island soil index system, including soil content, storage, and quality indices, was proposed to represent the island soil integrated condition. Soil content indices are original soil measured data, and soil storage and quality indices are composite indices that are determined based on soil content indices. Then, a predictor system based on remote sensing and the 10-fold cross-validation were used to conduct the spatial simulations of soil indices. The results validated that the combination of soil measured data sourced by field survey could respond more sensitively to remote sensing data and integrate with it better than the original soil measured data, thereby increasing the simulation accuracies of soil storage and quality indices to higher levels than the corresponding soil content indices and achieving the spatial exhibition of soil integrated condition. The spatial pattern of soil indices in Shengsi Archipelago indicated that islands or areas with good vegetation condition but low soil salinity, land surface aridity, and human interference generally had good soil integrated condition. Then, suggestions to improve the island soil integrated condition were proposed from perspectives of different essential components of the island ecosystem. The study has provided a practical method for comprehensively mapping the soil condition in areas with low accessibility.