Spatiotemporal Changes in Vegetation Cover and Its Influencing Factors in the Loess Plateau of China Based on the Geographically Weighted Regression Model

Yang, Chen; Fu, Meichen; Feng, Dingrao; Sun, Yukun; Zhai, Guohui

doi:10.3390/f12060673

Cited by 25 publications

(16 citation statements)

References 37 publications

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“…GDP per capita was found to be positively correlated with water yield. This discovery is consistent with the research results of (Yang et al 2021, Sun et al 2017, Li et al 2018. The increased water yield with GDB per capita and the growth rate of construction land have a firm consistency, with correlation coefficients of 0.89 (p < 0.05) and 0.93 (p < 0.05), respectively.…”

Section: Water Yield Change's Driving Factorssupporting

confidence: 91%

“…While the study of Yang et al (2021) shows that the correlation of GDP per capita to vegetation cover (and the result correlation with water yield) shows no clear pattern, it can be positively or negatively correlated. Research in the Loess Plateau, China, found that the relationship of GDP per capita to vegetation change (individually effect) was positive.…”

Section: Water Yield Change's Driving Factorsmentioning

confidence: 90%

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Spatial-temporal heterogeneity and driving factors of water yield services in Citarum river basin unit, West Java, Indonesia

2023

Archives of Environmental Protection

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Many countries, including Indonesia, face severe water scarcity and groundwater depletion. Monitoring and evaluation of water resources need to be done. In addition, it is also necessary to improve the method of calculating water, which was initially based on a biophysical approach, replaced by a socio-ecological approach. Water yields were estimated using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. The Ordinary Least Square (OLS) and geographic weighted regression (GWR) methods were used to identify and analyze socio-ecological variables for changes in water yields. The purpose of this study was:(1) to analyze the spatial and temporal changes in water yield from 2000 to 2018 in the Citarum River Basin Unit (Citarum RBU) using the InVEST model, and (2) to identify socio-ecological variables as driving factors for changes in water yields using the OLS and GWR methods. The findings revealed the overall annual water yield decreased from 16.64 billion m 3 year -1 in the year 2000 to 12.16 billion m 3 year -1 in 2018; it was about 4.48 billion m 3 (26.91%). The socio-ecological variables in water yields in the Citarum RBU show that climate and socio-economic characteristics contributed 6% and 44%, respectively. Land use/Land cover (LU/LC) and land configuration contribution fell by 20% and 40%, respectively.The main factors underlying the recent changes in water yields include average rainfall, pure dry agriculture, and bare land at 28.53%, 27.73%, and 15.08% for the biophysical model, while 30.28%, 23.77%, and 10.24% for the socio-ecological model, respectively. However, the social-ecological model demonstrated an increase in the contribution rate of climate and socio-economic factors and vice versa for the land use and landscape contribution rate. This circumstance demonstrates that the socio-ecological model is more comprehensive than the biophysical one for evaluating water scarcity.

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Section: Water Yield Change's Driving Factorssupporting

confidence: 91%

Section: Water Yield Change's Driving Factorsmentioning

confidence: 90%

Spatial-temporal heterogeneity and driving factors of water yield services in Citarum river basin unit, West Java, Indonesia

2023

Archives of Environmental Protection

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“…In this study, a Geographically Weighted Regression (GWR) model was used to reveal the interpretability of land use type changes on vegetation cover restoration, considering spatial autocorrelation and spatial heterogeneity 37 . The formula is as follows:…”

Section: Geographically Weighted Regression Modelmentioning

confidence: 99%

Evaluation of Vegetation Restoration Effectiveness along the Yangtze River Shoreline and Its Response to Land Use Changes

Huang,

Li,

Liu

et al. 2023

Preprint

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Assessing the effectiveness of vegetation restoration along the Yangtze River shoreline and exploring the relationship between vegetation restoration and land use changes are essential for providing recommendations for sustainable management and environmental protection. However, the effect of vegetation restoration after the implementation of the Yangtze River Conservation Project is not well known. In this study, based on Sentinel-2 satellite imagery before (2016) and after (2022) the Yangtze River Conservation Project, as well as Dynamic World land use data, pixel-based binary models, transition matrices, and geographically weighted regression models were used to analyze the state and evolution of vegetation coverage in the Yangtze River shoreline region. The results indicated that there had been an increase in the area covered by high and high-medium vegetation levels. The proportion of vegetation cover shifting to better was 35.68%. Hotspots of vegetation coverage improvement were primarily distributed along the Yangtze River. In areas with vegetation coverage improvement, the main types of land use changes included the conversion of water to crops (22.79%), trees to crops (10.76%), crops to built area (10.76%). Conversion between crops and built area was a significant factor influencing vegetation coverage improvement, with average regression coefficients of 0.68 and 0.50, respectively.

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“…The NDVI can be used to characterize the degree of vegetation cover and has been widely applied in different fields of study [49][50][51][52], so it can be used to represent the vegetation cover in Chongqing. In our study vegetation cover is considered as the value to monitor the degree of vegetation growth.…”

Section: Research Frameworkmentioning

confidence: 99%

How Did the Mild and Humid Areas of China Turn Green? A Case Study on Chongqing

Zuo

Cheng

Zhang

et al. 2022

Forests

Self Cite

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Since the implementation of the Natural Forest Resources Protection Project (NFRP) and the Grain for Green Program (GFGP), two key ecological projects related to forestry, the vegetation cover in Chongqing, has improved significantly. Existing studies have revealed the effects of climate change and human activity on vegetation cover in arid regions. However, more studies are needed to reveal the influence of drivers on vegetation cover in mild and humid areas, to quantify the relative contribution of drivers and to analyze the overall land use characteristics in different regions. In this study, we used Theil–Sen slope analysis and the Mann–Kendall test to investigate the spatial and temporal changes in vegetation cover in Chongqing. Further, we used Pearson correlation analysis to analyze the correlations between vegetation cover and drivers, quantitatively analyzing the relative contributions of these drivers. Complex network model analysis was used for different regions to obtain their land-use system characteristics, and the Hurst index was adopted to predict future vegetation-cover changes. The results of this study showed that the average vegetation cover in Chongqing increased significantly from 2000 to 2020, and the overall greening trend was most obvious in winter. Precipitation and temperature influenced the vegetation cover of Chongqing city to a certain extent, and the positive correlation between vegetation cover and precipitation was more significant than that with temperature. In terms of the precipitation factor, the areas with significant positive correlations were mainly concentrated in the central and southern parts of Chongqing, which could be related to the higher precipitation in the southern part of the city. Under the combined influence of climate change and human activity, vegetation cover increased in 71.95% of the total area. Human activity had a relative contribution of 70.39% and 69.14% in the areas where vegetation cover decreased and increased, respectively. The analysis results of the complex network model showed that woodlands and grasslands contributed more to areas where the vegetation cover exhibited an increasing trend. In the future, it is estimated that 72.92% of the vegetation cover in Chongqing will exhibit a degradation trend. This study helps us further understand vegetation-cover changes in mild and humid areas, providing new research directions for informing forestry-related policies.

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Spatiotemporal Changes in Vegetation Cover and Its Influencing Factors in the Loess Plateau of China Based on the Geographically Weighted Regression Model

Cited by 25 publications

References 37 publications

Spatial-temporal heterogeneity and driving factors of water yield services in Citarum river basin unit, West Java, Indonesia

Spatial-temporal heterogeneity and driving factors of water yield services in Citarum river basin unit, West Java, Indonesia

Evaluation of Vegetation Restoration Effectiveness along the Yangtze River Shoreline and Its Response to Land Use Changes

How Did the Mild and Humid Areas of China Turn Green? A Case Study on Chongqing

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