Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019

Zhongbing Chang (1) , Lei Fan (2) , Wigneron J.-P. (3) , Ying-Ping Wang (4) , Philippe Ciais (5) , Jérôme Chave (6) , Rasmus Fensholt (7) , Jing M. Chen (8) , Wenping Yuan (9) , Weimin Ju (10) , Xin Li (1) , Fei Jiang (10) , Mousong Wu (10) , Xiuzhi Chen (9) , Yuanwei Qin (11) , Frédéric Frappart (3, 12) , Xiaojun Li (3) , Mengjia Wang (3) , Xiangzhuo Liu (3) , Xuli Tang (1) , Sanaa Hobeichi (13) , Mengxiao Yu (1) , Mingguo Ma (2) , Qing Xiao (1) , Jianguang Wen , Weiyu Shi , Dexin Liu , Junhua Yan

1 CAS - Chinese Academy of Sciences [Beijing]
2 Southwest University [Chongqing]
3 UMR ISPA - Interactions Sol Plante Atmosphère
4 CSIRO Atmospheric Research
5 LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]
6 EDB - Evolution et Diversité Biologique
7 ITU - IT University of Copenhagen
8 University of Toronto
9 SYSU - Sun Yat-Sen University [Guangzhou]
10 NJU - Nanjing University
11 OU - University of Oklahoma
12 LEGOS - Laboratoire d'études en Géophysique et océanographie spatiales
13 UNSW - University of New South Wales [Sydney]

Over the past 2 to 3 decades, Chinese forests are estimated to act as a large carbon sink, yet the magnitude and spatial patterns of this sink differ considerably among studies. Using 3 microwave (L- and X-band vegetation optical depth [VOD]) and 3 optical (normalized difference vegetation index, leaf area index, and tree cover) remote-sensing vegetation products, this study compared the estimated live woody aboveground biomass carbon (AGC) dynamics over China between 2013 and 2019. Our results showed that tree cover has the highest spatial consistency with 3 published AGC maps (mean correlation value R = 0.84), followed by L-VOD (R = 0.83), which outperform the other VODs. An AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to 2019. The performance of the AGC estimation model was good (root mean square error = 0.05 Pg C and R² = 0.90 with a mean relative uncertainty of 9.8% at pixel scale [0.25°]). Results of the AGC estimation model showed that carbon uptake by the forests in China was about +0.17 Pg C year⁻¹ from 2013 to 2019. At the regional level, provinces in southwest China including Guizhou (+22.35 Tg C year⁻¹), Sichuan (+14.49 Tg C year⁻¹), and Hunan (+11.42 Tg C year⁻¹) provinces had the highest carbon sink rates during 2013 to 2019. Most of the carbon-sink regions have been afforested recently, implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.

Domains: Sciences of the Universe [physics]

Zhongbing Chang, Lei Fan, Wigneron J.-P., Ying-Ping Wang, Philippe Ciais, et al.. Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019. Journal of remote sensing., 2023, 3, ⟨10.34133/remotesensing.0005⟩. ⟨insu-03993153⟩