Abstract
ABSTRACT Under the pressure of SDG15.3.1 compliance, it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary. From the view of geographical scale, six zoning units were divided in the Yellow River Basin with ‘climate-meteorology-geomorphology’ as the main controlling factor, and a salinization inversion model was constructed for each zoning unit. Appropriate surface parameters were selected to construct a three-dimensional feature space according to the individual geographical zones. Based on the cloud data processing capability of the Google Earth Engine platform, a feature space inversion process was applied for automatic inversion of salinization. Salinization distribution maps of the Yellow River Basin in 2015 and 2020 were obtained at 30 m resolution by classifying the salinization inversion result. The distribution and spatiotemporal variation of salinization as well as the causes of salinization were analyzed. Reasonable prevention and control suggestions were subsequently proposed. This study could also be scaled up to larger and more complex geographical regions.
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