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Investigating vegetation coverage and quantitatively evaluating environmental changes can serve as the science knowledge in ecological protection, resource management, and policy-making, promoting harmonious coexistence between human and nature. In this study, we had explored the separation in space and time of evolutionary characteristics and driving factors of NDVI in Nanchang City from 2000 to 2022 based on Hurst Exponent, ReliefF feature selection algorithm, Geographical detector and so on. The results are: (1) From temporal dimension, the average NDVI in Nanchang City was 0.453, showing an overall upward trend. Although the growth rate gradually slowed over time. (2) In terms of spatial changes, vegetation in Nanchang City overall exhibited a characteristic of reverse sustained development, showing trends of "improvement around rivers and lakes" and "large-scale degradation of urban land." (3) The ReliefF proved to be more suitable among the three algorithms in the temporal dimension-driven analysis. Human factors are the dominant factors significantly influencing the changes in NDVI, while meteorological factors are not as significant. (4) The driver-analysis of geographical dector shows that population density, nighttime lights, and land cover types emerged as significant driving factors. Regions where NDVI and human factors have negative correlation are primarily centred in the heart of Nanchang City and Jinxian County; while the positive correlations are found around rivers and lakes. This study delves into the changing patterns of vegetation cover in Nanchang City, providing scientific guidance for the protection and regulation the regional ecological environment to bring about a sustainable development.
Investigating vegetation coverage and quantitatively evaluating environmental changes can serve as the science knowledge in ecological protection, resource management, and policy-making, promoting harmonious coexistence between human and nature. In this study, we had explored the separation in space and time of evolutionary characteristics and driving factors of NDVI in Nanchang City from 2000 to 2022 based on Hurst Exponent, ReliefF feature selection algorithm, Geographical detector and so on. The results are: (1) From temporal dimension, the average NDVI in Nanchang City was 0.453, showing an overall upward trend. Although the growth rate gradually slowed over time. (2) In terms of spatial changes, vegetation in Nanchang City overall exhibited a characteristic of reverse sustained development, showing trends of "improvement around rivers and lakes" and "large-scale degradation of urban land." (3) The ReliefF proved to be more suitable among the three algorithms in the temporal dimension-driven analysis. Human factors are the dominant factors significantly influencing the changes in NDVI, while meteorological factors are not as significant. (4) The driver-analysis of geographical dector shows that population density, nighttime lights, and land cover types emerged as significant driving factors. Regions where NDVI and human factors have negative correlation are primarily centred in the heart of Nanchang City and Jinxian County; while the positive correlations are found around rivers and lakes. This study delves into the changing patterns of vegetation cover in Nanchang City, providing scientific guidance for the protection and regulation the regional ecological environment to bring about a sustainable development.
Investigating vegetation coverage and quantifying environmental changes offer critical insights for ecological protection, resource management, and policymaking. This study explores the spatial and temporal separation of evolutionary characteristics and driving factors of the NDVI in Nanchang City from 2000 to 2022, using methods such as the Hurst Exponent, the ReliefF feature selection algorithm, and geographical detectors. The results show the following observations: (1) Temporal analysis: the average NDVI in Nanchang City was 0.453, showing an overall upward trend, although the rate of increase gradually slowed over time. (2) Spatial analysis: vegetation in Nanchang City exhibited a pattern of sustained reverse development, with notable trends of “improvement around rivers and lakes” and “large-scale degradation of urban land”. (3) Feature selection: among the three algorithms tested, ReliefF proved most effective in analyzing temporal drivers of NDVI changes. Human factors were identified as the dominant drivers of NDVI variation, while meteorological factors were less significant. (4) Geographical driver analysis: The geographical detectors revealed that population density, nighttime lights, and land cover types were the primary drivers of vegetation change. Regions with a negative correlation between NDVI and human factors are mainly centered in the central area of Nanchang City and Jinxian County, whereas positive correlations were observed around rivers and lakes. This study delves into the changing patterns of vegetation cover in Nanchang City, offering scientific insights to guide the protection and management of the regional ecological environment, thereby promoting sustainable development.
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