Estimating the Effects of Natural and Anthropogenic Activities on Vegetation Cover : Analysis of Zhejiang Province, China, from 2000 to 2022
department or school: Forestry, Faculty of
department or school: Non UBC
data provider: DSpace
identifier citation: Remote Sensing 17 (8): 1433 (2025)
creator: Chen, Lv
creator: Li, Chong
creator: Pan, Chunyu
creator: Yan, Yancun
creator: Jiao, Jiejie
creator: Zhou, Yufeng
creator: Wang, Xiaoxian
creator: Zhou, Guomo
issued: 2025-05-15T15:41:21Z
issued: 2025-04-17
description: Zhejiang Province, a pivotal economically developed region within China’s Yangtze River Delta, requires systematic investigation of spatiotemporal vegetation dynamics and their drivers to formulate targeted ecological protection policies and optimize vegetation restoration strategies. Utilizing the Google Earth Engine (GEE) platform, this study applied the Kernel Normalized Difference Vegetation Index (kNDVI) to assess vegetation responses to climate variability and human activities in Zhejiang Province from 2000 to 2022. Analytical methods included simple linear regression, Theil Sen trend analysis (Sen), Mann Kendall test (MK), Hurst index, partial correlation analysis, and correlation analysis. The results show: (1) The kNDVI exhibited a significant upward trend (0.001/year), covering 61.5% of the province. The Hurst index analysis revealed that 69.1% of vegetation changes exhibited anti-sustainability characteristics, with future vegetation degradation areas (56.4%) projected to exceed improvement areas (28.1%). (2) Human activities (57.11%) contributed more to kNDVI changes than climate change (42.89%). (3) Against the backdrop of climate change, kNDVI demonstrated a positive partial correlation with temperature (coefficient: 0.44) but exhibited a negative correlation with precipitation (coefficient: −0.056), confirming temperature as the dominant climatic driver. Overall, vegetation dynamics in Zhejiang Province from 2000 to 2022 were jointly driven by climate change and human activities.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/91147
note: Academic Editor: Lenio Soares GalvaoReceived: 12 February 2025Revised: 21 March 2025Accepted: 29 March 2025Published: 17 April 2025Citation: Chen, L.; Li, C.; Pan, C.; Yan,Y.; Jiao, J.; Zhou, Y.; Wang, X.; Zhou, G.Estimating the Effects of Natural andAnthropogenic Activities onVegetation Cover: Analysis ofZhejiang Province, China, from 2000 to2022. Remote Sens. 2025, 17, 1433.https://doi.org/10.3390/rs17081433Copyright: © 2025 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license(https://creativecommons.org/licenses/by/4.0/).ArticleEstimating the Effects of Natural and Anthropogenic Activitieson Vegetation Cover: Analysis of Zhejiang Province, China, from2000 to 2022Lv Chen 1,2, Chong Li 1,2,*, Chunyu Pan 1,3 , Yancun Yan 3, Jiejie Jiao 4, Yufeng Zhou 1,2, Xiaoxian Wang 5and Guomo Zhou 1,21 Key Laboratory of Carbon Sequestration and Emission Reduction in Agriculture and Forestry of ZhejiangProvince, Zhejiang A&F University, Hangzhou 311300, China; chentao@stu.zafu.edu.cn (L.C.);chunyu.pan@ubc.ca (C.P.); zhouyuf@zafu.edu.cn (Y.Z.); zhougm@zafu.edu.cn (G.Z.)2 School of Environmental and Resources Science, Zhejiang A&F University, Hangzhou 311300, China3 Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada;yancun@student.ubc.ca4 Zhejiang Academy of Forestry, Hangzhou 310023, China; 2023202012007@stu.zafu.edu.cn5 College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China;wxiaoxian2024@lzu.edn.cn* Correspondence: chongli@zafu.edu.cnAbstract: Zhejiang Province, a pivotal economically developed region within China’sYangtze River Delta, requires systematic investigation of spatiotemporal vegetation dy-namics and their drivers to formulate targeted ecological protection policies and optimizevegetation restoration strategies. Utilizing the Google Earth Engine (GEE) platform, this…
has type: Article
is shown at: 10.14288/1.0448900
language: eng
peer review status: Reviewed
provider: Vancouver : University of British Columbia Library
publisher: Multidisciplinary Digital Publishing Institute
publisher DOI: 10.3390/rs17081433
rights: CC BY 4.0
rights URI: https://creativecommons.org/licenses/by/4.0/
scholar level: Faculty
scholar level: Researcher
subject: human activities
subject: climate change
subject: vegetation monitoring
subject: google earth engine
subject: remote sensing
type: Text
identifier URI: http://hdl.handle.net/2429/91147