基于地理探测器的滏阳河流域植被覆盖时空变化与驱动力分析

doi:10.13745/j.esf.sf.2023.2.79

地学前缘 ›› 2023, Vol. 30 ›› Issue (5): 526-540.DOI: 10.13745/j.esf.sf.2023.2.79

基于地理探测器的滏阳河流域植被覆盖时空变化与驱动力分析

陈康¹^,²^,³^,⁴(), 丁永康¹^,²^,³^,⁴^,^*(), 张笑晨¹^,²^,³^,⁴

1.河北地质大学水资源与环境学院, 河北石家庄 050031
2.河北省水资源可持续利用与开发重点实验室, 河北石家庄 050031
3.河北省水资源可持续利用与产业结构优化协同创新中心, 河北石家庄 050031
4.河北省高校生态环境地质应用技术研发中心, 河北石家庄 050031

收稿日期:2023-03-09 修回日期:2023-04-06 出版日期:2023-09-25 发布日期:2023-10-20
通讯作者: 丁永康
作者简介:陈康(1982—),男,副教授,硕士生导师,主要研究方向为地下水环境。E-mail: chenkang@hgu.edu.cn
基金资助:
中国地质调查局地质调查项目(DD20160238);河北省教育厅高等教育教学改革研究与实践项目(2020GJJG224);河北地质大学青年科技基金项目(QN202143)

Spatiotemporal dynamics and control factors of vegetation cover in the Fuyang River Basin based on geographical detector model

CHEN Kang¹^,²^,³^,⁴(), DING Yongkang¹^,²^,³^,⁴^,^*(), ZHANG Xiaochen¹^,²^,³^,⁴

1. School of Water Resources and Environment, Hebei GEO University, Shijiazhuang 050031, China
2. Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Shijiazhuang 050031, China
3. Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang 050031, China
4. Hebei Center for Ecological and Environmental Geology Research, Shijiazhuang 050031, China

Received:2023-03-09 Revised:2023-04-06 Online:2023-09-25 Published:2023-10-20
Contact: DING Yongkang

摘要/Abstract

摘要：

滏阳河位于河北省境内,作为子牙河系两大支流之一,流经多座城市和乡村,对流域内的生态环境和经济发展起着重要作用。文章基于2000—2020年月尺度MOD13A1(500 m)遥感数据,采用一元线性回归和Hurst指数法分析了区内植被时空变化趋势,借助Person相关分析方法对降水量和温度与归一化植被指数(NDVI)进行相关性分析,利用地理探测器模型将区内降水量、温度、植被类型、土壤类型和海拔等自然因子,土地利用类型、人口密度和GDP等人为因子进行统计划分,探讨了各驱动因子对NDVI变化的影响程度,利用模型进行了因子探测、交互作用探测和风险区探测,明确了驱动因子与NDVI间的驱动力大小以及利于植被生长的最适因子数值范围或类型,为生态保护和可持续发展提供参考和依据。结果表明:(1)2000—2020年,区内植被覆盖度总体呈现增长的趋势,每年NDVI平均值为0.76,Slope指数平均值为0.000 5,Hurst指数平均值为0.48,据指数空间叠加结果,区内植被覆盖变化以未来改善为主;(2)区内NDVI与降水量之间整体呈现正相关关系,NDVI与温度之间相关性不强,相对而言,NDVI年际变化与降水量关系更密切;(3)区内单个驱动因子对NDVI的影响程度由大到小排序为:降水量>人口密度>GDP>土地利用类型>土壤类型>温度>海拔>植被类型,其中前3个因子的q值均大于0.2,作为影响区内的主要驱动因子;(4)区内双因子组合驱动力明显高于单因子驱动力,因子间的交互作用以双因子增强关系为主,其中NDVI变化受降水量和人口密度的交互作用影响最大,q值为0.59,降水量同其他因子间的交互作用处于主导地位;(5)根据区内风险区探测结果,以降水量464.73~500.03 mm、温度15.14~15.23 ℃、海拔3~133 m、人口密度551.36~2 059.96人·km^-2、GDP 1 756.77~7 507.15元·km^-2的数值范围和以栽培植被、初育土、耕地为主要类型的区域,有利于植被的生长。

关键词: 滏阳河流域, 归一化植被指数(NDVI), 时空动力学, 地理探测器, 气象因素, 驱动因子

Abstract:

The Fuyang River—flows through Handan, Xingtai and Hengshui areas of Hebei Province as a tributary of the Ziya River, confluencing with the Hutuo River at Cangzhou—plays an important role in the eco-environment and economic development of the Fuyang River Basin. Based on the 2000-2020 monthly MOD13A1 (500 m) dataset, the spatiotemporal dynamics of regional vegetation cover was analyzed by unary linear regression and Hurst index methods, and Pearson correlation analysis between the normalized difference vegetation index (NDVI) and temperature/precipitation was performed. In combination with geographical analysis by geographical detector method, natural factors such as precipitation, temperature, vegetation type, soil type and elevation, and human factors such as land use type, population density and GDP were evaluated through statistical analysis for their impact on regional vegetation cover. Furthermore, control-factor detection, two-factor interaction detection and risk area detection were carried out. Ultimately, the impact of each control factor on NDVI and the optimal value of each control factor for vegetation growth are calculated, which provided a reference and basis for ecological protection and sustainable development in the region. The results showed that (1) the regional vegetation cover had an overall increasing trend between 2000-2020, and the NDVI, Slope index and Hurst index annual means were 0.76, 0.0005 and 0.48, respectively. According to spatial superposition analysis, the regional vegetation-cover changes were mainly attributed to man-made improvements. (2) There was a positive correlation between NDVI and precipitation annual means, while NDVI interannual trends were more closely related to precipitation than temperature. (3) The control factors were ranked according to their influence on NDVI as precipitation > population density > GDP > land use type > soil type > temperature > elevation > vegetation type. The first three factors, with q values greater than 0.2, were considered the main control factors of regional vegetation cover. (4) The impact of a two-factor combination was significantly higher than that of a single factor, showing a two-factor enhancement effect; the precipitation-population density combination, with a q value of 0.59, had the highest impact, while combinations of precipitation and other factors had dominant effects. (5) Based on risk area detection, areas with precipitation of 464.73-500.03 mm, temperature of 15.14-15.23 ℃, altitude of 3-133 m, population density of 551.36-2059.96 people·km^-2, GDP of 1756.77-7507.15 yuan·km^-2, and an eco-environment with cultivated vegetation, nursery soil and cultivated land, were most favorable for vegetation growth.

Key words: Fuyang River Basin, NDVI, spatiotemporal dynamics, geographic detector, meteorological factors, control factors

中图分类号:

陈康, 丁永康, 张笑晨. 基于地理探测器的滏阳河流域植被覆盖时空变化与驱动力分析[J]. 地学前缘, 2023, 30(5): 526-540.

CHEN Kang, DING Yongkang, ZHANG Xiaochen. Spatiotemporal dynamics and control factors of vegetation cover in the Fuyang River Basin based on geographical detector model[J]. Earth Science Frontiers, 2023, 30(5): 526-540.

图/表 14

图1 滏阳河流域地理位置及气象站点分布

Fig.1 Geographical location of and distribution of meteorological stations in the Fuyang River Basin

表1 基于归一化植被指数(NDVI)的植被覆盖状况分类标准

Table 1 NDVI based classification standards for vegetation status

覆盖分区	NDVI
低覆盖度区域	0~0.2
中低覆盖度区域	>0.2~0.4
中覆盖度区域	>0.4~0.6
中高覆盖度区域	>0.6~0.8
高覆盖度区域	>0.8~1

表2 基于植被覆盖度变化一元线性方程的回归斜率(θslope)植被覆盖变化趋势分类标准

Table 2 θslope based classification standards for vegetation growth trend

程度	θ_slope	Z
明显退化	<-0.009 0	<-1.96
轻度退化	-0.009 0~<-0.000 9	-1.96~1.96
基本稳定	-0.000 9~<0.000 9	任意
轻度改善	0.000 9~<0.009 0	-1.96~1.96
明显改善	≥0.009 0	>1.96

表3 驱动力大小判据区间及交互作用类型

Table 3 Geographical detector parameters used in this study

判据区间	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)]	双因子增强
q(X₁∩X₂)=q(X₁) + q(X₂)	独立
q(X₁∩X₂)>q(X₁) + q(X₂)	非线性增强

图2 2000—2020年滏阳河流域内各年NDVI变化趋势

Fig.2 2000-2020 NDVI interannual trends in the Fuyang River Basin

图3 2000—2020年滏阳河流域年均NDVI覆盖分区

Fig.3 Delineation of vegetation status in the Fuyang River Basin based on 2000-2020 NDVI annual means

图4 滏阳河流域植被覆盖度空间变化趋势与Hurst指数分布 (a) 2000—2020年变化趋势; (b) Hurst指数分布; (c) 未来变化趋势。

Fig.4 Delineation of vegetation growth trends in the Fuyang River Basin based on 2000-2020 average annual trends (a), Hurst indexes (b), and calculated future trends (b)

图5 滏阳河流域植被覆盖度空间变化趋势面积占比

Fig.5 Pie charts of vegetation growth trends in the Fuyang River Basin. (a) 2000-2020 average annual trends; (b) future trends.

图6 2000—2020年滏阳河流域年均降水量(a)及温度(b)空间分布

Fig.6 2000-2020 average annual precipitation (a) and temperature (b) in the Fuyang River Basin

图7 2000—2020年滏阳河流域NDVI与降水量(a)、温度(b)的相关系数空间分布

Fig.7 Pearson correlation coefficient maps of 2000-2020 average annual NDVI versus precipitation (a) and temperature (b) in the Fuyang River Basin

图8 2000—2020年滏阳河流域植被驱动因子海拔(a)、土壤类型(b)、植被类型(c)、土地利用类型(d)、人口密度(e)、GDP(f)的空间分布

Fig.8 2000-2020 vegetation control-factor detection results on altitude (a), soil type (b), vegetation type (c), land use type (d), population density (e) and GDP (f) in the Fuyang River Basin

表4 2000—2020年滏阳河流域植被NDVI各单驱动因子q值

Table 4 q values of NDVI controlling factors in the Fuyang River Basin calculated for the 2000-2020 period

滏阳河流域植被NDVI各单驱动因子q值
降水	温度	海拔	植被类型	土壤类型	土地利用类型	人口密度	GDP
0.37	0.11	0.03	0.02	0.16	0.22	0.31	0.24

表5 2000—2020年滏阳河流域植被NDVI驱动因子交互组合驱动力q值

Table 5 q values of two-factor combinations for the 2000-2020 period

驱动因子	植被NDVI驱动因子交互组合驱动力q值
驱动因子	降水量	温度	海拔	植被类型	土壤类型	土地利用类型	人口密度	GDP
降水量	0.37
温度海拔植被类型土壤类型土地利用类型人口密度 GDP	0.44 0.40 0.39 0.46 0.51 0.59 0.53	0.11 0.16 0.13 0.22 0.27 0.36 0.29	0.03 0.05 0.18 0.24 0.35 0.28	0.02 0.17 0.23 0.33 0.26	0.16 0.29 0.36 0.29	0.22 0.38 0.33	0.31 0.34	0.24

表6 2000—2020年滏阳河流域驱动因子探测指标适应类型或范围

Table 6 Optimal conditions for vegetation growth in the Fuyang River Basin based on 2000-2020 data

评价指标	植被覆盖度适宜范围(类型)	NDVI均值
降水量/mm	464.73~500.03	0.763 3
温度/℃	15.14~15.23	0.748 7
海拔/m	3~133	0.735 8
植被类型	栽培植被	0.826 5
土壤类型	初育土	0.760 0
土地利用类型	耕地	0.755 6
人口密度/(人·km^-2)	551.36~2 059.96	0.744 4
GDP/(元·km^-2)	1 756.77~7 507.15	0.730 7

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基于地理探测器的滏阳河流域植被覆盖时空变化与驱动力分析

Spatiotemporal dynamics and control factors of vegetation cover in the Fuyang River Basin based on geographical detector model

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