延河流域生态敏感性与景观格局空间自相关性

doi:10.13866/j.azr.2025.09.17

Abstract

Abstract:

To explore the distribution and intrinsic connections between ecological sensitivity and landscape patterns in the Yanhe River Basin, this study employed ArcGIS 10.8 and Fragstats 4.2 to analyze their spatial autocorrelation. The results demonstrated that (1) Ecological sensitivity in the Yanhe River Basin exhibits significant spatial variation. The extremely, moderately, and highly sensitive areas spanned 473.04 km², 1921.21 km², and 1272.15 km², accounting for 6.12%, 24.87%, and 16.47% of the total area, respectively, and primarily consisting of water areas, forestlands, and cultivated lands. (2) The spatial autocorrelation between ecological sensitivity and landscape pattern was significant. The number of patches (NP) and edge density (ED) were positively correlated with ecological sensitivity, indicating that higher landscape fragmentation in the Yanhe River Basin led to stronger ecological sensitivity. The largest patch index (LPI) and average patch area (Area_Mp) were negatively correlated with ecological sensitivity. The implementation of forestry ecological projects such as converting farmland to forests (grassland), increased the proportion of large patches in the Yanhe River Basin, effectively reducing ecological sensitivity. Therefore, future ecological protection strategies for the Yanhe River Basin should consider the spatial autocorrelation pattern and tailor measures to different regions, thereby further enhancing ecological protection and promoting high-quality development in the Basin.

Key words: ecological sensitivity, landscape pattern, mobile window method, spatial autocorrelation

JIANG Yongqing, LUO Fujia, LI Jiong, LIU Guangquan, LIU Changhai, AI Ning. Spatial autocorrelation between ecological sensitivity and landscape pattern in the Yanhe River Basin[J].Arid Zone Research, 2025, 42(9): 1742-1752.

Figures/Tables 11

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References 29

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数据类型	数据来源	分辨率	时间
土地利用类型（LUCC）数据	中国科学院资源环境科学与数据中心（http://www.resdc.cn）	30 m	2023年
数字高程模型（DEM）数据	地理空间数据云（https://www.gscloud.cn）	30 m	2023年
延河流域矢量边界	中国科学院资源环境科学与数据中心（https://www.resdc.cn）	矢量数据	2023年
归一化植被指数（NDVI）数据	国家青藏高原科学数据中心（https://data.tpdc.ac.cn）	250 m	2023年

准则层	评价因素	评价标准					权重
准则层	评价因素	极度敏感	高度敏感	中度敏感	轻度敏感	不敏感	权重
地形因子	高程/m	≥2000	1500~2000	1000~1500	500~1000	≤500	0.184
	坡度/（°）	>45°	30°~45°	15°~30°	5°~15°	0°~5°	0.175
	坡向	南	东南、西南	东、西	东北、西北	平地、北坡	0.033
水因子	水体缓冲区/m	<100	100~200	200~500	500~1000	>1000	0.193
植被因子	NDVI	>0.8	0.6~0.8	0.4~0.6	0.2~0.4	<0.2	0.203
土地利用因子	土地利用类型	水体	林地	草地	耕地	建设用地	0.212

景观指数	含义	景观指数	含义
斑块数量（NP）	斑块总数，反映景观破碎化程度。数量越多，破碎化越高	边缘密度（ED）	不同土地利用类型间交互程度，影响物种扩散和能量流动
斑块丰富度（PR）	斑块类型多样性指标，多样性越高，生态系统的稳定性越强	景观形状指数（LSI）	斑块形状复杂程度，关联物种栖息和扩散难度
最大斑块指数（LPI）	优势斑块占比，对维持生态系统的重要功能有关键作用	平均斑块面积（Area_Mp）	斑块平均大小，反映生态系统抗干扰能力

景观指数	Moran's I	Z值	P值	关联方向	典型区域
NP	0.1782	20.8672	0.001	正协同	安塞区（HH）
ED	0.1287	15.4398	0.001	正协同	宝塔区（HH）
LPI	-0.2138	-25.4522	0.001	负向权衡	宝塔区（LH）
Area_Mp	-0.1742	-20.4881	0.001	负向权衡	延长县（HL）
LSI	0.1287	15.4393	0.001	正协同	延长县（LL）
PR	0.2943	34.3730	0.001	正协同	宝塔区（HH）

Spatial autocorrelation between ecological sensitivity and landscape pattern in the Yanhe River Basin

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