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Article

Quantitative Assessment of Factors Influencing the Spatiotemporal Variation in Carbon Dioxide Fluxes Simulated by Multi-Source Remote Sensing Data in Tropical Vegetation

1
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
2
The Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572000, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
4
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
5
Space Information and Big Earth Data Research Center, College of Computer Science and Technology, Qingdao University, Qingdao 266071, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(24), 5677; https://doi.org/10.3390/rs15245677
Submission received: 17 October 2023 / Revised: 5 December 2023 / Accepted: 6 December 2023 / Published: 8 December 2023

Abstract

Vegetation plays a vital role in the global carbon cycle, a function of particular significance in regulating carbon dioxide fluxes within tropical ecosystems. Therefore, it is crucial to enhance the precision of carbon dioxide flux estimates for tropical vegetation and to explore the determinants influencing carbon sequestration. In this study, Landsat series images and Sentinel-2 Multispectral Instrument satellite data were used to invert vegetation biophysical parameters, thereby improving the timeliness and resolution of state variables from the boreal ecosystem productivity simulator (BEPS). The BEPS model at a 30 m resolution was developed to accurately capture tropical vegetation carbon dioxide fluxes across Hainan Island (HN) over the preceding two decades. The impacts of climate variations and anthropogenic activities on the carbon dioxide fluxes of tropical vegetation were further quantified using quantile regression models and a land-use transfer matrix. Results indicate significant increases in both net primary productivity (NPP) and net ecosystem productivity (NEP) in HN during the period 2000–2020, by 5.81 and 4.29 g C/m2 year, respectively. Spatial trends in vegetation carbon dioxide fluxes exhibited a consistent decline from inland regions to coastal zones. Anthropogenic activities were the dominant factor in the reduced stability of coastal NPP, while the post-2005 vegetation restoration promoted the southward expansion of high NPP (>1200 g C/m2) in the central part of HN. NPP in this tropical island was more sensitive to temperature than to precipitation, with a 1 °C temperature increase resulting in 4.1 g C/m2 reduction in dry-season NPP compared to wet-season NPP. Upgrades of cropland quality and grassland restoration have improved NPP yields, and land use transfers have resulted in a 0.301 Tg C net increase in NPP. This study provides new insight into the improvement of the carbon dioxide flux model at a finer scale for tropical vegetation and highlights ecological construction as an adaptation strategy to enhance the carbon sinks of tropical vegetation under negative climate change conditions.
Keywords: net primary productivity; net ecosystem productivity; boreal ecosystem productivity simulator (BEPS); climate factors; land use change net primary productivity; net ecosystem productivity; boreal ecosystem productivity simulator (BEPS); climate factors; land use change

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MDPI and ACS Style

Xu, R.; Zhang, J.; Wang, J.; Yao, F.; Zhang, S. Quantitative Assessment of Factors Influencing the Spatiotemporal Variation in Carbon Dioxide Fluxes Simulated by Multi-Source Remote Sensing Data in Tropical Vegetation. Remote Sens. 2023, 15, 5677. https://doi.org/10.3390/rs15245677

AMA Style

Xu R, Zhang J, Wang J, Yao F, Zhang S. Quantitative Assessment of Factors Influencing the Spatiotemporal Variation in Carbon Dioxide Fluxes Simulated by Multi-Source Remote Sensing Data in Tropical Vegetation. Remote Sensing. 2023; 15(24):5677. https://doi.org/10.3390/rs15245677

Chicago/Turabian Style

Xu, Ruize, Jiahua Zhang, Jingwen Wang, Fengmei Yao, and Sha Zhang. 2023. "Quantitative Assessment of Factors Influencing the Spatiotemporal Variation in Carbon Dioxide Fluxes Simulated by Multi-Source Remote Sensing Data in Tropical Vegetation" Remote Sensing 15, no. 24: 5677. https://doi.org/10.3390/rs15245677

APA Style

Xu, R., Zhang, J., Wang, J., Yao, F., & Zhang, S. (2023). Quantitative Assessment of Factors Influencing the Spatiotemporal Variation in Carbon Dioxide Fluxes Simulated by Multi-Source Remote Sensing Data in Tropical Vegetation. Remote Sensing, 15(24), 5677. https://doi.org/10.3390/rs15245677

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