基于GEE的关中平原城市群植被时空演变及影响因素

靳紫含; 赵安周; 相恺政; 田新乐; 张向蕊

doi:10.13961/j.cnki.stbctb.2023.02.020

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基于GEE的关中平原城市群植被时空演变及影响因素

试验研究

- 基于GEE的关中平原城市群植被时空演变及影响因素
- Temporal and Spatial Evolution and Driving Factors of Vegetation Index in Guanzhong Plain Urban Agglomeration Based on GEE
- 水土保持通报 2023年43卷第2期页码：164-172
- 作者机构：
  
  河北工程大学矿业与测绘工程学院,河北,邯郸,056038
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“黄土高原城镇化—生态环境互馈机制及动态模拟”(42171212)
- DOI：10.13961/j.cnki.stbctb.2023.02.020
  中图分类号： X87;P237
- 纸质出版：2023
- 稿件说明：
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靳紫含, 赵安周, 相恺政, 等. 基于GEE的关中平原城市群植被时空演变及影响因素[J]. 水土保持通报, 2023,43(2):164-172.

Jin Zihan, Zhao Anzhou, Xiang Kaizheng, et al. Temporal and Spatial Evolution and Driving Factors of Vegetation Index in Guanzhong Plain Urban Agglomeration Based on GEE[J]. Bulletin of Soiland Water Conservation, 2023, 43(2): 164-172.
靳紫含, 赵安周, 相恺政, 等. 基于GEE的关中平原城市群植被时空演变及影响因素[J]. 水土保持通报, 2023,43(2):164-172. DOI： 10.13961/j.cnki.stbctb.2023.02.020.

Jin Zihan, Zhao Anzhou, Xiang Kaizheng, et al. Temporal and Spatial Evolution and Driving Factors of Vegetation Index in Guanzhong Plain Urban Agglomeration Based on GEE[J]. Bulletin of Soiland Water Conservation, 2023, 43(2): 164-172. DOI： 10.13961/j.cnki.stbctb.2023.02.020.

摘要

[目的

]

探究2000—2020年关中平原城市群植被时空变化特征及驱动因素，为区域生态文明建设提供科学指导。 [方法

]

基于Google Earth Engine(GEE)云平台，利用2000—2020年Landsat影像计算得到的增强型植被指数(enhanced vegetation index， EVI)，结合趋势分析、热点分析、地理探测器模型等方法分析了关中平原城市群年最大EVI(EVI

max

)变化格局及驱动因素。 [结果

]

①2000—2020年关中平原城市群年EVI

max

整体呈上升趋势，未发生变化的土地利用/覆盖类型年EVI

max

值均呈波动上升趋势，其中草地的上升速率最大。 ②空间上，关中平原城市群年EVI

max

值呈由南向北递减的趋势，高值区主要位于南部的秦岭山地。趋势分析结果表明年EVI

max

呈显著上升和显著下降的面积分别为70.16%和3.61%。 ③年EVI

max

的空间集聚特征表现为热点和冷点数量呈轻微下降和显著下降趋势，冷点区域逐渐转化为次冷点或次热点区域。 ④降水是影响关中平原城市群年EVI

max

空间分布的最主要因素，各影响因素的交互作用为非线性增强或双因子增强。 [结论

]

关中平原城市群2000—2020年植被总体呈上升趋势，降水对植被的影响起主导作用。

Abstract

[Objective] The temporal and spatial variation characteristics and driving factors of vegetation in the Guanzhong Plain urban agglomeration from 2000 to 2020 were studied in order to provide scientific guidance for the construction of regional ecological civilization. [Methods] Based on the Google Earth Engine (GEE) cloud platform

we used the enhanced vegetation index (EVI) data calculated from Landsat images from 2000 to 2020 combined with trend analysis

hot spot analysis

geographic detector model

and other methods to analyze the change pattern and driving factors of the annual maximum EVI (EVImax) in the Guanzhong Plain urban agglomeration. [Results] ① Annual EVImax showed a significant upward trend in the Guanzhong Plain urban agglomeration from 2000 to 2020. Annual EVImax values for the unchanged land use/cover types showed a fluctuating upward trend

among which the rate of increase for grassland was the largest. ② Spatially

the EVImax values showed a decreasing trend from south to north

and the high-value areas were mainly located in the Qinling Mountains in the southern Guanzhong Plain urban agglomeration. Trend analysis results showed that the areas where the annual EVImax increased and decreased significantly accounted for 70.16% and 3.61%

respectively

of the total area. ③ The spatial agglomeration characteristics of annual EVImax showed that the number of hot and cold spots showed a slight decrease and a significant downward trend

and the cold spots gradually transformed into sub-cold or sub-hot spots. ④ Precipitation was the most important factor affecting the spatial distribution of EVImax in the Guanzhong Plain urban agglomeration

and the interaction of each influencing factor was characterized as nonlinear enhancement or two-factor enhancement. [Conclusion] The vegetation of the Guanzhong Plain urban agglomeration showed an overall upward trend from 2000 to 2020

and annual precipitation was an important factor that determined vegetation growth status.

关键词

Keywords

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