Canopy Height Integration for Precise Forest Aboveground Biomass Estimation in Natural Secondary Forests of Northeast China Using Gaofen-7 Stereo Satellite Data
Year: 2024
Type: article
Abstract: Accurate estimates of forest aboveground biomass (AGB) are necessary for the accurate tracking of forest carbon stock. Gaofen-7 (GF-7) is the first civilian sub-meter three-dimensional (3D) mapping satellite from China. It is equipped with a laser altimeter system and a dual-line array stereoscopic mapping camera, which enables it to synchronously generate full-waveform LiDAR data and stereoscopic images. The bulk of existing research has examined how accurate GF-7 is for topographic measurements of bare land or canopy height. The measurement of forest aboveground biomass has not received as much attention as it deserves. This study aimed to assess the GF-7 stereo imaging capability, displayed as topographic features for aboveground biomass estimation in forests. The aboveground biomass model was constructed using the random forest machine learning technique, which was accomplished by combining the use of in situ field measurements, pairs of GF-7 stereo images, and the corresponding generated canopy height model (CHM). Findings showed that the biomass estimation model had an accuracy of R2 = 0.76, RMSE = 7.94 t/ha, which was better than the inclusion of forest canopy height (R2 = 0.30, RMSE = 21.02 t/ha). These results show that GF-7 has considerable application potential in gathering large-scale high-precision forest aboveground biomass using a restricted amount of field data.
Source: Remote Sensing
DOI: 10.3390/rs17010047
Authors: Caixia Liu, Huabing Huang, Zhiyu Zhang, Wenyi Fan, Di Wu
Institutions: Chinese Academy of Sciences, Aerospace Information Research Institute, State Key Laboratory of Remote Sensing Science, International Research Center of Big Data for Sustainable Development Goals, Sun Yat-sen University, Northeast Forestry University, Ministry of Natural Resources, Heilongjiang Institute of Technology
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $3,069
Awards: G2505561686, G8026922857
OpenAlex ID: W4405832402
