Data and code files for "A novel interpretable artificial intelligence (XAI) approach for revealing the spatiotemporal variation and driving factors of soil salinization in a semi-arid region"

The repository contains the data files used to simulate the spatiotemporal distribution of soil salinity in western Jilin Province, China, including the locations of the data points, soil salinity (EC), and all the environmental variables for models. It also contains the code files for the RF model and the three XAI techniques employed in the paper.本仓库包含用于模拟中国吉林省西部土壤盐渍化时空分布的全部数据文件，涵盖数据测点位置、土壤含盐量（电导率EC）以及模型训练所需的所有环境变量。此外，本仓库还收录了论文中使用的随机森林（Random Forest, RF）模型代码，以及所采用的三种可解释人工智能（eXplainable Artificial Intelligence, XAI）技术的实现代码。