Mapping high-resolution forest aboveground biomass of China using multisource remote sensing data. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Yang, Qiuli; Niu, Chunyue; Liu, Xiaoqiang; Feng, Yuhao; Ma, Qin; Wang, Xuejing; Tang, Hao; Guo, Qinghua
• Is Part Of: GIScience & remote sensing. Volume 60:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: Forest AGB -- in situ measurements -- canopy height -- high resolution -- China; Geodesy -- Periodicals; Cartography -- Periodicals; Aerial photogrammetry -- Periodicals; Remote sensing -- Periodicals; 526.05
• DOI: 10.1080/15481603.2023.2203303
• Languages: English
• ISSNs: 1548-1603

Abstract

ABSTRACT: Forest aboveground biomass (AGB) estimation is crucial for carbon cycle studies and climate change mitigation actions. However, because of limitations in timely and reliable forestry surveys and high-resolution remote sensing data, producing a fine resolution and spatial continuous forest AGB map of China is challenging. Here, we combined 4789 ground-truth AGB measurements and multisource remote sensing data such as a recently released forest canopy-height product, optical spectral indexes, topographic data, climatological data, and soil properties to train a random forest regression model for forest AGB estimation of China at 30-m resolution. The accuracy of the estimated AGB can yield R 2 = 0.67 and RMSE = 70.71 Mg/ha. The nationwide estimates show that the average forest AGB and total forest carbon storage were 97.57 ± 23.85 Mg/ha and 11.06 Pg C for the year 2019, respectively. The value of AGB uncertainty ranges from 0.68 Mg/ha to 37.80 Mg/ha, and the average AGB uncertainty was 4.32 ± 1.75 Mg/ha. The forest AGB estimates of China in this study correspond reasonably well with the AGB estimates derived from the forestry and grassland statistical yearbook at the provincial level (R 2 = 0.61, RMSE = 30.15 Mg/ha). In addition, we found that previous AGB products generally underestimate the forest AGB compared with our estimated AGB at the pixel-level and ground-truth AGB measurements. The high-resolution forest AGB map provides an important alternative data source for forest carbon cycle studies and can be used as a baseline map for forest management and conservation practices.