Canopy Height Integration for Precise Forest Aboveground Biomass Estimation in Natural Secondary Forests of Northeast China Using Gaofen-7 Stereo Satellite Data

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.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2024-12-27
DOI
https://doi.org/10.3390/rs17010047
Citations
3
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.62

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Canopy Height Integration for Precise Forest Aboveground Biomass Estimation in Natural Secondary Forests of Northeast China Using Gaofen-7 Stereo Satellite Data

Z.F. Zhang, Wenyi Fan, Di Wu, Huabing Huang et al.
3 citations
Remote Sensing
Remote Sensing and LiDAR Applications
0.62
article

Canopy Height Integration for Precise Forest Aboveground Biomass Estimation in Natural Secondary Forests of Northeast China Using Gaofen-7 Stereo Satellite Data

Z.F. Zhang, Wenyi Fan, Di Wu, Huabing Huang, Caixia Liu
article en
3 citations

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.

Remote SensingVol. 17(1)
Sun Yat-sen University (CN), Ministry of Natural Resources (CN), Aerospace Information Research Institute (CN), Heilongjiang Institute of Technology (CN), State Key Laboratory of Remote Sensing Science (CN), Northeast Forestry University (CN), Heilongjiang University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Life in Land
Openalex Percentile: Top 34%
Remote Sensing and LiDAR Applications
0.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.