基于半监督学习模型的地质环境承载力评价: 以府谷县为例.

As an important part of territorial spatial planning, geological environment carrying capacity assessment has become a key link for the coordination between sustainable and high-quality development of human economic and social activities and geological environment protection. Fugu County of Shaanxi Province in the Yellow River Basin was taken as an example, the evaluation system and evaluation model of geological environment carrying capacity were established. Based on the comprehensive evaluation results, the impact degree of the influencing factors was further analyzed. The semi-supervised learning model was introduced to evaluate 17 kinds of influencing factors from five systems, such as physical geography and ecological environment. The results show that the semi-supervised learning model can improve the sensitivity of geological environment carrying capacity assessment and the regression prediction accuracy is high. The geological environmental carrying capacity of Fugu County is divided into 5 carrying capacity grades from low to high and the influencing factors under different grades have different effects. Among them, 7 influencing factors such as the susceptibility of collapse and landslide can be given priority to construct the evaluation system of geological environmental carrying capacity of soil and water conservation area on the Loess Plateau. [ABSTRACT FROM AUTHOR]

地质环境承载力评价作为国土空间规划中的重要组成部分, 成为人类经济社会活动可持续、高质量发展与地质环境 保护相协调的关键纽带。 以黄河流域生态环境脆弱区———陕西省府谷县为例, 建立地质环境承载力评价体系与评价模型, 在 综合评价结果的基础上, 进一步分析影响因素作用程度。 从自然地理、生态环境等 5 个系统选取 17 类影响因素, 引入半监督 学习模型进行评价。 结果表明: 半监督学习模型提升了地质环境承载力评价的敏感性, 回归预测精度较高; 府谷县地质环境 承载力由低至高划分为 5 个承载力等级分区, 不同等级下影响因素作用程度不同, 其中崩塌滑坡易发性等 7 项影响因素可优 先用于黄土高原水土保持区地质环境承载力评价体系的构建。 [ABSTRACT FROM AUTHOR]