Next Article in Journal
Impact of Conservation in the Futian Mangrove National Nature Reserve on Water Quality in the Last Twenty Years
Previous Article in Journal
FireYOLO-Lite: Lightweight Forest Fire Detection Network with Wide-Field Multi-Scale Attention Mechanism
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China

by
Dejin Dong
1,*,
Ziliang Zhao
2,
Hongdi Gao
3,
Yufeng Zhou
2,
Daohong Gong
4,
Huaqiang Du
2 and
Yuichiro Fujioka
5
1
Graduate School of Integrated Sciences for Global Society, Kyushu University, Motooka 744, Nishi-ku, Fukuoka 819-0395, Japan
2
School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China
3
Zhejiang Forest Resources Monitoring Center, Hangzhou 310020, China
4
School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
5
Faculty of Social and Cultural Studies, Kyushu University, Motooka 744, Nishi-ku, Fukuoka 819-0395, Japan
*
Author to whom correspondence should be addressed.
Forests 2024, 15(7), 1245; https://doi.org/10.3390/f15071245 (registering DOI)
Submission received: 12 June 2024 / Revised: 14 July 2024 / Accepted: 15 July 2024 / Published: 17 July 2024

Abstract

As global climate change intensifies and human activities escalate, changes in vegetation cover, an important ecological indicator, hold significant implications for ecosystem protection and management. Shandong Province, a critical agricultural and economic zone in China, experiences vegetation changes that crucially affect regional climate regulation and biodiversity conservation. This study employed normalized difference vegetation index (NDVI) data, combined with climatic, topographic, and anthropogenic activity data, utilizing trend analysis methods, partial correlation analysis, and Geodetector to comprehensively analyze the spatiotemporal variations and primary driving factors of vegetation cover in Shandong Province from 2001 to 2020.The findings indicate an overall upward trend in vegetation cover, particularly in areas with concentrated human activities. Climatic factors, such as precipitation and temperature, exhibit a positive correlation with vegetation growth, while land use changes emerge as one of the key drivers influencing vegetation dynamics. Additionally, topography also impacts the spatial distribution of vegetation to a certain extent. This research provides a scientific basis for ecological protection and land management in Shandong Province and similar regions, supporting the formulation of effective vegetation restoration and ecological conservation strategies.
Keywords: climate change; geodetector; normalized difference vegetation index (NDVI); trend analysis; vegetation cover change climate change; geodetector; normalized difference vegetation index (NDVI); trend analysis; vegetation cover change

Share and Cite

MDPI and ACS Style

Dong, D.; Zhao, Z.; Gao, H.; Zhou, Y.; Gong, D.; Du, H.; Fujioka, Y. Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China. Forests 2024, 15, 1245. https://doi.org/10.3390/f15071245

AMA Style

Dong D, Zhao Z, Gao H, Zhou Y, Gong D, Du H, Fujioka Y. Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China. Forests. 2024; 15(7):1245. https://doi.org/10.3390/f15071245

Chicago/Turabian Style

Dong, Dejin, Ziliang Zhao, Hongdi Gao, Yufeng Zhou, Daohong Gong, Huaqiang Du, and Yuichiro Fujioka. 2024. "Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China" Forests 15, no. 7: 1245. https://doi.org/10.3390/f15071245

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop