基于地理探测器模型的珠三角植被覆盖度时空变化驱动力分析

沈明潭; 谭炳香; 侯瑞霞; 于航; 贺晨瑞; 黄逸飞

doi:10.13961/j.cnki.stbctb.2023.06.039

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基于地理探测器模型的珠三角植被覆盖度时空变化驱动力分析

试验研究

- 基于地理探测器模型的珠三角植被覆盖度时空变化驱动力分析
- Driving Force Analysis of Spatio-temporal Changes in Vegetation Coverage in Pearl River Delta Based on Geographic Detector Model
- 水土保持通报 2023年43卷第6期页码：336-345
- 作者机构：
  
  1. 中国林业科学研究院资源信息研究所,北京,100091
  2. 国家林业和草原局林业遥感与信息技术重点实验室,北京,100091
  3. 国家林业和草原科学数据中心,北京,100091
- 作者简介：
- 基金信息：
  
  广东省林业局项目“珠三角森林城市群质量提升关键技术研究”（2021KJCX009）
- DOI：10.13961/j.cnki.stbctb.2023.06.039
  中图分类号： S718.553;P431.5;Q412.1
- 纸质出版：2023
- 稿件说明：
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沈明潭, 谭炳香, 侯瑞霞, 等. 基于地理探测器模型的珠三角植被覆盖度时空变化驱动力分析[J]. 水土保持通报, 2023,43(6):336-345.

Shen Mingtan, Tan Bingxiang, Hou Ruixia, et al. Driving Force Analysis of Spatio-temporal Changes in Vegetation Coverage in Pearl River Delta Based on Geographic Detector Model[J]. Bulletin of Soiland Water Conservation, 2023, 43(6): 336-345.
沈明潭, 谭炳香, 侯瑞霞, 等. 基于地理探测器模型的珠三角植被覆盖度时空变化驱动力分析[J]. 水土保持通报, 2023,43(6):336-345. DOI： 10.13961/j.cnki.stbctb.2023.06.039.

Shen Mingtan, Tan Bingxiang, Hou Ruixia, et al. Driving Force Analysis of Spatio-temporal Changes in Vegetation Coverage in Pearl River Delta Based on Geographic Detector Model[J]. Bulletin of Soiland Water Conservation, 2023, 43(6): 336-345. DOI： 10.13961/j.cnki.stbctb.2023.06.039.

摘要

[目的] 探究珠三角植被覆盖度空间分布和时空变化的驱动力，为该地区生态环境的保护提供科学参考。[方法] 基于Landsat 5 TM和Landsat 8 OLI数据，利用像元二分模型反演珠三角2000，2005，2010，2015和2020年5个时期的植被覆盖度，分析珠三角植被覆盖度的空间格局和时空变化的过程。并结合5个时期的年降水量、年均温度、人口密度和土地利用，采用相关系数和地理探测器等方法开展研究。[结果] ①珠三角植被覆盖度在空间上表现为中部较低，边缘区域较高的分布格局，在佛山市、中山市、珠海市、广州市西南部、东莞市和深圳市较低，肇庆市、江门市和惠州市较高。植被覆盖度总体上表现为改善的趋势，改善的面积比例为64.99%，在时间上存在阶段性的差异，2010—2015年期间高植被覆盖度（80%以上）增长的面积最明显； ②影响因素对植被覆盖度的驱动有明显的区域差异性，年降水量和土地利用程度起抑制作用的面积大于起促进作用的面积，年均温度和人口密度起促进作用的面积大于起抑制作用的面积； ③植被覆盖度空间格局因子探测表明土地利用程度的解释力最强，交互探测表明年均温度与土地利用程度交互作用的解释力最高，年降水量、年降水量与年均温度交互作用的解释力在2000，2005，2010，2015和2020年5个时期的时间序列上表现为减弱的趋势，其余影响因素及其交互作用的解释力都呈现上升的趋势。植被覆盖度时空变化因子探测也表明土地利用程度变化的解释力最强，而交互探测表明年降水量变化与土地利用程度变化交互作用的解释力最高。[结论] 土地利用程度是影响珠三角植被覆盖度时空变化的主导因素，人为影响不断增强，双因素的交互作用明显大于单因素的作用。

Abstract

[Objective] The driving forces of the spatial distribution and spato-temporal changes in fractional vegetation coverage (FVC) in the Pearl River delta were analyzed in order to provide a scientific reference for the protection of the ecological environment in the region. [Methods] A binary pixel model was used with Landsat 5 TM and Landsat 8 OLI data to invert the vegetation coverage of the Pearl River delta in 2000

2005

2010

2015

and 2020. The spatial pattern and spatio-temporal changes in FVC in the Pearl River delta were analyzed. Annual precipitation

average annual temperature

population density

and land use data during the five study periods were analyzed using correlation coefficients and the geographical detector method. [Results] ① Vegetation coverage in the Pearl River delta was lower in the middle of the region and higher in the marginal regions. Vegetation coverage was lower in Foshan

Zhongshan

Zhuhai

Southwestern Guangzhou

Dongguan City

and Shenzhen City

and higher in Zhaoqing

Jiangmen City

and Huizhou City. Overall

vegetation coverage increased over time

with 64.99% of the total area showing increases in vegetation coverage. There were stage differences in time

and the area with highest vegetation coverage (more than 80%) increased most significantly during 2010-2015. ② There were obvious regional differences in the driving factors of FVC. Annual precipitation and land use had more inhibiting effects than promoting effects

and average annual temperature and population density had more promoting effects than inhibiting effects. ③ The spatial pattern factor detection of FVC showed that the explanatory power of land use degree was the strongest

while the interactive detection showed that the explanatory power of annual average temperature and land use degree interaction was the highest. For the explanatory power of annual precipitation

annual precipitation and annual temperature interaction showed a weakening trend in the time series of 2000

2005

2010

2015

and 2020. The explanatory power of other influencing factors and their interactions showed an increasing trend. The spatial-temporal FVC change factor detection also indicated that the explanatory power of land use degree change was the strongest

while the interactive detection indicated that annual precipitation change and land use degree interaction had the highest explanatory power. [Conclusion] Land use degree was the dominant factor affecting the temporal and spatial changes of vegetation coverage in the Pearl River delta. Human influence continues to increase

and the interaction of the two factors is significantly greater than the effect of a single factor.

关键词

Keywords

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