Spatio-Temporal Separating Analysis of NDVI Evolution and Driving Factors: A Case Study in Nanchang, China

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 f...

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Bibliographic Details
Published in:Sustainability 2024-12, Vol.16 (23), p.10494
Main Authors: Li, Jiatong, Wu, Hua, Zhu, Jiaqi, Xu, Yue, Guo, Qiyun, Li, Huishan, Xie, Xue, Liu, Sihang
Format: Article
Language:English
Subjects:
Algorithms
Climate change
Comparative analysis
Computer centers
Correlation analysis
Distribution
Environmental aspects
Feature selection
GDP
Geography
Gross Domestic Product
Machine learning
Measurement
Optical properties
Plant communities
Precipitation
Rain
Rivers
Sensors
Time series
Topography
Trends
Vegetation
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Summary: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.
ISSN:2071-1050
2071-1050
DOI:10.3390/su162310494