Back to Search
Start Over
Forest terrain and canopy height estimation using stereo images and spaceborne LiDAR data from GF-7 satellite.
- Source :
- Geo-Spatial Information Science; Jun2024, Vol. 27 Issue 3, p811-821, 11p
- Publication Year :
- 2024
-
Abstract
- Accurate estimation of forest terrain and canopy height is crucial for timely understanding of forest growth. Gao Fen-7 (GF-7) Satellite is China's first sub-meter-level three-dimensional (3D) mapping satellite for civilian use, which was equipped with a two-line-array stereo mapping camera and a laser altimeter system that can provide stereo images and full waveform LiDAR data simultaneously. Most of the existing studies have concentrated on evaluating the accuracy of GF-7 for topographic survey in bare land, but few have in-depth studied its ability to measure forest terrain elevation and canopy height. The purpose of this study is to evaluate the potential of GF-7 LiDAR and stereo image for forest terrain and height measurement. The Airborne Laser Scanning (ALS) data were utilized to generate reference terrain and forest vertical information. The validation test was conducted in Pu'er City, Yunnan Province of China, and encouraging results have obtained. The GF-7 LiDAR data obtained the accuracy of forest terrain elevation with RMSE of 8.01 m when 21 available laser footprints were used for results verification; meanwhile, when it was used to calculate the forest height, R<superscript>2</superscript> of 0.84 and RMSE of 3.2 m were obtained although only seven effective footprints were used for result verification. The canopy height values obtained from GF-7 stereo images have also been proven to have high accuracy with the resolution of 20 m × 20 m compared with ALS data (R<superscript>2</superscript> = 0.88, RMSE = 2.98 m). When the results were verified at the forest sub-compartment scale that taking into account the forest types, further higher accuracy (R<superscript>2</superscript> = 0.96, RMSE = 1.23 m) was obtained. These results show that GF-7 has considerable application potential in forest resources monitoring. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10095020
- Volume :
- 27
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Geo-Spatial Information Science
- Publication Type :
- Academic Journal
- Accession number :
- 178418917
- Full Text :
- https://doi.org/10.1080/10095020.2023.2249037