Terrestrial Carbon Storage Estimation in Guangdong Province (2000–2021)

Wei Wang, Yueming Hu, Xiaoyun Mao (), Ying Zhang, Liangbo Tang and Junxing Cai
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Wei Wang: College of Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Yueming Hu: College of Tropical Crops, Hainan University, Haikou 570228, China
Xiaoyun Mao: College of Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Ying Zhang: Tangshan Vocational and Technical College, Tangshan 063000, China
Liangbo Tang: College of Biology and Agriculture, Shaoguan University, Shaoguan 512005, China
Junxing Cai: College of Biology and Agriculture, Shaoguan University, Shaoguan 512005, China

Data, 2025, vol. 10, issue 4, 1-5

Abstract: (1) Terrestrial ecosystems are critical carbon sinks, and the accurate assessment of their carbon storage is vital for understanding global carbon cycles and formulating climate change mitigation strategies. (2) This study integrated vegetation indices, meteorological factors, land use data, soil/vegetation types, field sampling, and a convolutional neural network (CNN) model to estimate the carbon storage of terrestrial ecosystems in Guangdong Province. (3) Total carbon storage increased by 0.11 Pg from 2000 to 2021, with vegetation carbon gains (+0.19 Pg) offsetting soil carbon losses (−0.08 Pg), with the latter primarily being driven by reduced soil carbon in forest ecosystems. (4) Northern and eastern Guangdong exhibit high potential for enhancing carbon storage capacity, which is crucial for achieving regional carbon peaking and neutrality targets.

Keywords: terrestrial ecosystems; carbon storage; spatiotemporal patterns; convolutional neural network; Guangdong province (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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