Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020

The Loess Plateau is one of the most severely affected regions by soil erosion in the world, with a fragile ecological environment. Vegetation plays a key role in the region’s ecological restoration and protection. This study employs the Geographical Detector (Geodetector) model to quantitatively as...

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Main Authors: Zhihong Yao, Yichao Huang, Yiwen Zhang, Qinke Yang, Peng Jiao, Menghao Yang
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Land
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Online Access:https://www.mdpi.com/2073-445X/14/2/303
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author Zhihong Yao
Yichao Huang
Yiwen Zhang
Qinke Yang
Peng Jiao
Menghao Yang
author_facet Zhihong Yao
Yichao Huang
Yiwen Zhang
Qinke Yang
Peng Jiao
Menghao Yang
author_sort Zhihong Yao
collection DOAJ
description The Loess Plateau is one of the most severely affected regions by soil erosion in the world, with a fragile ecological environment. Vegetation plays a key role in the region’s ecological restoration and protection. This study employs the Geographical Detector (Geodetector) model to quantitatively assess the impact of natural and human factors, such as temperature, precipitation, soil type, and land use, on vegetation growth. It aims to reveal the characteristics and driving mechanisms of vegetation cover changes on the Loess Plateau over the past 26 years. The results indicate that from 1995 to 2020, the vegetation coverage on the Loess Plateau shows an increasing trend, with a fitted slope of 0.01021 and an R<sup>2</sup> of 0.96466. The Geodetector indicates that the factors with the greatest impact on vegetation cover in the Loess Plateau are temperature, precipitation, soil type, and land use. The highest average vegetation coverage is achieved when the temperature is between −4.8 and 2 °C or 12 and 16 °C, precipitation is between 630.64 and 935.51 mm, the soil type is leaching soil, and the land use type is forest. And the interaction between all factors has a greater effect on the vegetation cover than any single factor alone. This study reveals the factors influencing vegetation growth on the Loess Plateau, as well as their types and ranges, providing a scientific basis and guidance for improving vegetation coverage in this region.
format Article
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institution DOAJ
issn 2073-445X
language English
publishDate 2025-02-01
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record_format Article
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spelling doaj-art-58779857d50744dbb0371af2ff40b40e2025-08-20T02:44:53ZengMDPI AGLand2073-445X2025-02-0114230310.3390/land14020303Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020Zhihong Yao0Yichao Huang1Yiwen Zhang2Qinke Yang3Peng Jiao4Menghao Yang5College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, ChinaCollege of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, ChinaCollege of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, ChinaDepartment of Urban and Resource Sciences, Northwest University, Xi’an 710069, ChinaYellow River Institute of Hydraulic Research, Zhengzhou 450003, ChinaCollege of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, ChinaThe Loess Plateau is one of the most severely affected regions by soil erosion in the world, with a fragile ecological environment. Vegetation plays a key role in the region’s ecological restoration and protection. This study employs the Geographical Detector (Geodetector) model to quantitatively assess the impact of natural and human factors, such as temperature, precipitation, soil type, and land use, on vegetation growth. It aims to reveal the characteristics and driving mechanisms of vegetation cover changes on the Loess Plateau over the past 26 years. The results indicate that from 1995 to 2020, the vegetation coverage on the Loess Plateau shows an increasing trend, with a fitted slope of 0.01021 and an R<sup>2</sup> of 0.96466. The Geodetector indicates that the factors with the greatest impact on vegetation cover in the Loess Plateau are temperature, precipitation, soil type, and land use. The highest average vegetation coverage is achieved when the temperature is between −4.8 and 2 °C or 12 and 16 °C, precipitation is between 630.64 and 935.51 mm, the soil type is leaching soil, and the land use type is forest. And the interaction between all factors has a greater effect on the vegetation cover than any single factor alone. This study reveals the factors influencing vegetation growth on the Loess Plateau, as well as their types and ranges, providing a scientific basis and guidance for improving vegetation coverage in this region.https://www.mdpi.com/2073-445X/14/2/303Loess PlateauNDVIvegetation coverland usegeographical detector model
spellingShingle Zhihong Yao
Yichao Huang
Yiwen Zhang
Qinke Yang
Peng Jiao
Menghao Yang
Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020
Land
Loess Plateau
NDVI
vegetation cover
land use
geographical detector model
title Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020
title_full Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020
title_fullStr Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020
title_full_unstemmed Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020
title_short Analysis of the Spatial–Temporal Characteristics of Vegetation Cover Changes in the Loess Plateau from 1995 to 2020
title_sort analysis of the spatial temporal characteristics of vegetation cover changes in the loess plateau from 1995 to 2020
topic Loess Plateau
NDVI
vegetation cover
land use
geographical detector model
url https://www.mdpi.com/2073-445X/14/2/303
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