黄河“几字弯”土地退化中性评估及影响因素分析

doi:10.12118/j.issn.1000-6060.2025.296

摘要/Abstract

摘要：

实现土地退化中性（Land degradation neutrality，LDN）是应对土地退化全球环境挑战的重要路径。黄河“几字弯”作为黄河流域生态保护和高质量发展的重点区域，水土流失和荒漠化土地退化问题严峻。基于LDN评估框架，结合区域退化过程，构建了本地化多尺度LDN分析框架，运用地理加权回归（Geographically weighted regression，GWR）等方法系统测度并解析了2000—2023年该区域LDN实现状况的空间格局及其影响因素。结果表明：（1）像元尺度上土地改善区域大于退化区域，土地呈现改善、退化和稳定状态的面积占比分别为69.69%、23.74%和6.57%。（2）区域尺度上整体均未实现LDN目标，网格尺度有47.42%的土地实现了LDN，县域尺度有36.00%的土地实现了LDN，21个城市中仅有7个城市实现了LDN。（3） LDN主导影响因素存在空间异质性，风速、人口密度和高程在多数区域对LDN呈现负面效应，而降水量、实际蒸散发、土壤湿度和归一化植被指数等因素则对LDN呈现正面效应。研究结果可为LDN框架的区域化应用提供参考，为黄河“几字弯”土地退化治理提供决策依据。

关键词: 土地退化中性, 生态系统服务, 地理加权回归, 影响因素, 黄河“几字弯”

Abstract:

Achieving land degradation neutrality (LDN) is a crucial pathway for addressing the global environmental challenge of land degradation. As a key area for ecological protection and high-quality development in the Yellow River Basin, the “Ji Zi Bend” section of the Yellow River faces serious soil erosion and desertification. Based on the LDN assessment framework, this study constructs a localized, multi-scale LDN analytical framework in combination with regional degradation processes. It systematically measures and analyzes the spatial patterns of LDN achievement and their influencing factors in the region from 2000 to 2023 by applying methods such as geographically weighted regression. The results show that (1) At the pixel scale, the area of land improvement exceeds that of degradation, with proportions of improved, degraded, and stabilized land accounting for 69.69%, 23.74%, and 6.57%, respectively. (2) At the regional scale, the LDN target has not yet been fully achieved, with 47.42% of land at the grid scale achieving LDN, 36.00% at the county scale achieving LDN, and only 7 out of 21 cities achieving LDN. (3) There is clear spatial heterogeneity in the dominant influencing factors of LDN. Wind speed, population density, and elevation generally exhibit negative effects on LDN in most areas, whereas precipitation, actual evapotranspiration, soil moisture, and the normalized difference vegetation index show positive effects on LDN. The findings provide a reference for the regionalized application of the LDN framework and a decision-making basis for land degradation management in the “Ji Zi Bend” section of the Yellow River.

Key words: land degradation neutrality, ecosystem services, geographically weighted regression, influencing factors, Yellow River’s “Ji Zi Bend”

张佳静, 王晓峰, 周潮伟, 周继涛, 白娟. 黄河“几字弯”土地退化中性评估及影响因素分析[J]. 干旱区地理, 2026, 49(4): 856-867.

ZHANG Jiajing, WANG Xiaofeng, ZHOU Chaowei, ZHOU Jitao, BAI Juan. Assessment of land degradation neutrality and analysis of influencing factors in Yellow River’s “Ji Zi Bend”[J]. Arid Land Geography, 2026, 49(4): 856-867.

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数据名称	分辨率	来源
降水量	1 km	国家青藏高原数据中心（https://data.tpdc.ac.cn/）
气温	1 km	国家青藏高原数据中心（https://data.tpdc.ac.cn/）
潜在蒸散发	1 km	国家青藏高原数据中心（https://data.tpdc.ac.cn/）
风速站点	-	美国国家海洋和大气管理局下设的国家环境信息中心（https://www.ncei.noaa.gov/data/global-summary-of-the-day/archive/）
归一化植被指数	1 km	美国国家航空航天局（https://ladsweb.modaps.eosdis.nasa.gov/）
土地利用类型	1 km	中国科学院资源环境科学与数据中心（http://www.resdc.cn/）
高程	90 m	中国科学院资源环境科学与数据中心（http://www.resdc.cn/）
土壤湿度	10 km	GLEAM4数据集^[19]（https://www.gleam.eu/?spm=a2ty_o01.29997173.0.0.693c570b1fEaPT）
实际蒸散发	4 km	TerraClimate数据集（https://www.climatologylab.org/）
人口密度	1 km	landscan（https://landscan.ornl.gov/）

数据类别	数据名称	简称	数据描述
自然环境	降水量/mm	PRE	统计单元的年均降水量
	气温/℃	TEM	统计单元的年均气温
	风速/m·s^-1	WIND	统计单元10 m高度风速
	实际蒸散发/mm	AET	统计单元实际蒸散发量
	潜在蒸散发/mm	PET	统计单元潜在蒸散发量
	土壤湿度/%	SM	统计单元土壤湿度
	归一化植被指数	NDVI	统计单元的归一化植被指数
	高程/m	DEM	统计单元的高程值
人类活动	人口密度/人·km^-2	POP	统计单元的人口密度
	新增耕地比例/%	GD	统计单元2023年比2000年新增耕地面积占比
	新增城镇比例/%	CZ	统计单元2023年比2000年新增建设用地占比

模型诊断信息	残差平方和	赤池信息准则	R²	校正后R²
OLS	275.7117	607.0568	0.2378	0.2361
GWR	144.2750	-1862.9000	0.6012	0.6004