艾比湖流域植被时空变化及驱动力分析

doi:10.12118/j.issn.1000–6060.2021.199

摘要/Abstract

摘要：

植被是反映陆地生态系统变化的敏感因子之一,对维持和调节生态系统稳定具有重要作用。以生态脆弱区艾比湖流域为研究区,采用地理探测器模型,研究艾比湖流域自然、人文因子及其交互作用对植被时空覆盖变化的影响,分析各影响因子促进植被生长的适宜范围(类别)。结果表明：（1） 2000—2020年艾比湖流域归一化植被指数（NDVI）呈现增加趋势,增速为0.035·(10a)^-1,生态环境得到有效改善,改善区域主要分布在中西部,显著提高地区主要位于艾比湖中部,严重退化地区零散分布在艾比湖中部中心位置。（2）土地利用类型、植被类型和土壤类型因素对植被NDVI空间分布的影响力大于其他因子,是主要影响因子。自然、人文因子之间对植被NDVI的交互作用以非线性增强和双因子增强效应为主,不存在独立关系。（3）耕地、栽培植被、人为土、中起伏山地、高程2177~2558 m、年降水量228~245 mm、年均气温4.74~5.25 ℃、坡向157.5°~202.5°以及坡度25°~35°,适合植被生长。研究结果将为艾比湖流域的生态保护提供科学依据。

关键词: 归一化植被指数（NDVI）, 植被变化, 地理探测器, 艾比湖流域

Abstract:

Vegetation is one of the sensitive factors reflecting the changes of the land ecosystem and plays an essential role in maintaining and regulating ecosystem stability. In this study, the Ebinur Lake Basin with complex terrain is located northwest of Xinjiang, China and has severe ecological and environmental degradation. Additionally, the ecological environment spatial specificity is obvious. Previous studies have only discussed the influence of climate and elevation on vegetation normalized difference vegetation index (NDVI) in the Ebinur Lake Basin. However, no research has been conducted on other natural and human activity factors, such as the type of vegetation and land use. Additionally, the most relevant analyses could not reveal the complex spatial anisotropy of the Ebinur Lake Basin and study the driver factors of NDVI variation quantitatively. Therefore, this paper takes the ecologically fragile area, i.e., the Ebinur Lake Basin, as the research area. The MODIS vegetation NDVI data from 2000 to 2020 and unary linear regression methods are used to analyze the characteristics of vegetation NDVI from 2000 to 2020. Then, the geographic detector model is used to investigate the influence of natural and human factors and their interaction with vegetation coverage. Furthermore, analyzing the appropriate range (categories) of various influencing factors promotes vegetation growth. The results are as follows. (1) From 2000 to 2020, the average vegetation cover in the Ebinur Lake Basin increased at the rate of 0.035·(10a)^-1, medium grade (0.4-0.6), medium and high grade (0.6-0.8), and high grade (0.8-1.0) vegetation area increased significantly. The ecological environment was effectively improved. The improved areas were distributed in the central and western regions. The significantly improved areas were located in the central part of the Ebinur Lake Basin. Meanwhile, severely degraded areas were scattered in the central part of the Ebinur Lake Basin. (2) The land use type, vegetation type, and soil type factors had a greater influence on the spatial distribution of vegetation NDVI than other factors as the main influencing factors. Elevation was the secondary factor. The precipitation, geomorphological type, temperature, slope, and slope had little direct impact on the spatial distribution of vegetation in the Ebinur Lake Basin. Compared with natural factors, human factors played a leading role in vegetation NDVI changes in the Ebinur Lake Basin. The interaction between natural and human factors on vegetation NDVI was dominated by nonlinear and double-factor enhancements, and there was no independent relationship. (3) Cultivland, cultivated vegetation, artificial soil, medium-undulating mountains, elevation range of 2177-2558 m, precipitation range of 228-245 mm, temperature range of 4.74-5.25 ℃, aspect of 157.5°-202.5°, and slope of 25°-35° were suitable for vegetation growth. This study explored the vegetation spatial differentiation and driving mechanism using the geographic detector model. The results of this study will provide a scientific basis for the ecological protection of the Ebinur Lake Basin.

Key words: normalized vegetation index (NDVI), vegetation change, geographic detector, Ebinur Lake Basin

任立清. 艾比湖流域植被时空变化及驱动力分析[J]. 干旱区地理, 2022, 45(2): 467-477.

REN Liqing. Spatiotemporal change and driving force of vegetation in Ebinur Lake Basin[J]. Arid Land Geography, 2022, 45(2): 467-477.

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因子类型	探测因子	指标
地形	X1	坡度/(°)
	X2	坡向/(°)
	X3	高程/m
土壤	X4	土壤类型
植被	X5	植被类型
地貌	X6	地貌类型
气候	X7	年均气温/℃
	X8	年降水量/mm
人类活动	X9	土地利用类型

依据	交互作用
q（X1∩X2）<Min[q（X1）,q（X2）]	非线性减弱
Min[q（X1）,q（X2）]<q（X1∩X2）<Max[q（X1）,q（X2）]	单因子非线性减弱
q（X1∩X2）>Max[q（X1）,q（X2）]	相互增强
q（X1∩X2）=q（X1）+q（X2）	独立
q（X1∩X2）>q（X1）+q（X2）	非线性增强

因子	坡度	坡向	高程	土壤类型	植被类型	地貌类型	年均气温	年降水量	土地利用类型
坡度	0.03
坡向	0.09+	0.01
高程	0.21+	0.25+	0.14
土壤类型	0.34+	0.40+	0.42+	0.27
植被类型	0.38+	0.39+	0.46++	0.47++	0.34
地貌类型	0.11+	0.13+	0.22+	0.33++	0.41++	0.08
年均气温	0.21+	0.20+	0.35+	0.48+	0.47+	0.24+	0.08
年降水量	0.25+	0.23+	0.38+	0.51+	0.47+	0.27+	0.11++	0.09
土地利用类型	0.52+	0.50+	0.64+	0.61++	0.58++	0.55+	0.56+	0.55+	0.46

土地利用类型	耕地	林地	草地	水域	城乡工矿居民用地	未利用土地
耕地
林地	N
草地	Y	Y
水域	Y	Y	Y
城乡工矿居民用地	N	N	N	N
未利用土地	Y	Y	Y	N	N
植被NDVI均值	0.73	0.66	0.42	0.25	0.54	0.21

植被类型	其他	针叶林	灌丛	荒漠	草原	草甸	高山植被	栽培植被
其他
针叶林	Y
灌丛	Y	N
荒漠	N	Y	Y
草原	Y	Y	Y	Y
草甸	Y	Y	Y	Y	Y
高山植被	N	Y	Y	Y	Y	Y
栽培植被	Y	Y	N	Y	Y	Y	Y
植被NDVI均值	0.27	0.59	0.69	0.29	0.39	0.50	0.19	0.71