Nonlinear Responses of Vegetation Phenology to Climate Change and Urbanization: A Case Study in Beijing, China
Vegetation serves as an indicator of ecological change, and phenology is an important indicator for evaluating vegetation growth and development. Analyzing the spatiotemporal characteristics of vegetation phenology and its driving factors is of great significance for analyzing the carbon, water, and...
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Veröffentlicht in: | IEEE journal of selected topics in applied earth observations and remote sensing 2024, Vol.17, p.5390-5402 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Vegetation serves as an indicator of ecological change, and phenology is an important indicator for evaluating vegetation growth and development. Analyzing the spatiotemporal characteristics of vegetation phenology and its driving factors is of great significance for analyzing the carbon, water, and energy balance of terrestrial ecosystems. To better assess the impact of external environmental changes on vegetation phenology and comprehend the changing trends of phenology, this study employed phenological parameters as response variables and incorporated meteorological and urbanization factors as explanatory variables. A generalized additive model (GAM) was constructed meticulously to investigate how vegetation phenology responds to climate change and urbanization in Beijing, as well as to predict vegetation phenology. The results showed that there were nonlinear relationships between the vegetation phenological parameters, i.e., start of season (SOS) and end of season (EOS), and external environmental changes. R^{2} of the GAM predicted SOS and EOS with respect to the observed data increased to 0.622 and 0.756, respectively. The prediction effects in each region of the urban-rural gradient zone were better with the root-mean-square error of approximately 4-7 days. This study demonstrates that the GAM considers the nonlinear relationships between vegetation phenology and external environmental factors. The validation results based on the observed data show that the models are reliable, and the findings can provide theoretical references for urban development planning and ecological environmental protection in Beijing. |
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ISSN: | 1939-1404 2151-1535 |
DOI: | 10.1109/JSTARS.2024.3367734 |