解读黄河流域的空间代码:优化土地利用功能和区分识别策略的新框架
Tonghui Yu1, Xuan Huang1, Xi Chen1
1School of Business, Xinyang Normal University, Xinyang, 464000, China.
Journal of environmental management
|June 14, 2025
概括
这项研究引入了一个基于网格的框架来评估黄河流域的土地利用功能 (LUF),揭示了与生态功能下降一起加强的生产和生活功能. 该研究确定了改善空间规划和土地治理的关键驱动因素和区域.
科学领域:
- 环境科学 环境科学
- 地理 地理 地理 地理.
- 空间规划 空间规划 空间规划
背景情况:
- 传统的土地使用功能评估方法往往是宏观的,对于生态敏感地区缺乏精度.
- 黄河流域 (YRB) 需要精细的空间规划,以平衡领土发展和生态保护.
- 现有的方法难以提供以功能为导向的土地治理,适合区域特点.
研究的目的:
- 开发和验证一个新的,基于网格的框架,用于评估和划分黄河流域 (YRB) 的土地使用功能 (LUF).
- 提高空间规划的精度,促进生态敏感地区的平衡领土发展.
- 通过整合多源数据和先进的识别模型来支持精细的,以功能为导向的土地治理.
主要方法:
- 使用78个城市的网格级数据 (2012-2022年) 构建生产-生活-生态 (PLE) 评估系统,包括遥感,兴趣点 (POI) 和社会经济指标.
- 应用地理探测器和地理加权回归 (GWR) 模型来确定影响LUF差异化的关键自然和社会经济驱动因素.
- 使用联合机械平衡模型和比较优势指数来分类18种土地使用功能区 (LUFZ).
主要成果:
- 观察到生产和生活功能显著加强;高价值生活功能区域从1.95%增加到7.53%.
- 生态功能下降,高价值生态面积在2012年至2022年期间从34.15%减少到29.59%.
- 生活占主导地位的土地扩大 (35.30%至35.59%),而生态占主导地位的土地收缩 (27.23%至24.90%),确定了18个不同的LUFZ.
结论:
- 拟议的基于电网的框架为准确的LUF识别和优化提供了一种综合性和可扩展的方法.
- 路面区域的动态受到人口密度,道路网络密度和降雨的重大影响,突出显示了自然和社会经济因素的相互作用.
- 这项研究为像YRB这样的生态脆弱地区的差异化领土空间治理提供了关键的理论支持.
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