Accuracy Evaluation and Impact Analysis of GEDI Ground Elevation and Canopy Height

doi:10.11873/j.issn.1004-0323.2022.5.1056

Remote Sensing Technology and Application

2022, Vol. 37

Issue (5): 1056-1070 DOI: 10.11873/j.issn.1004-0323.2022.5.1056

Accuracy Evaluation and Impact Analysis of GEDI Ground Elevation and Canopy Height

Zhihui Yuan^1,²(

),Sheng Nie²(

),Hebing Zhang¹,Cheng Wang²,Hongtao Wang¹,Xiaohuan Xi²

^1.School of Surveying and Land Information Engineering，Henan Polytechnic University，Jiaozuo 454100，China
^2.Key Laboratory of Digital Earth Science，Aerospace Information Research Institute，Chinese Academy of Sciences，Beijing 100094，China

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Abstract

Accurate extraction of ground elevation and vegetation canopy height is of great significance for the study of topography， ecology and so on. The new generation of Global Ecosystem Dynamics Investigation （GEDI） launched in December 2018 provides an unprecedented opportunity for accurate extraction of ground elevation and vegetation canopy height over large areas. The purpose of this paper is to verify the accuracies of ground elevation and canopy height extracted by GEDI using airborne LiDAR data， and to explore the influence of geographic positioning error， terrain slope， aspect， vegetation cover， azimuth， acquisition time， beam type and vegetation type on the estimation accuracy. The results show that the estimation accuracies of ground elevation and canopy height can be significantly improved by correcting the geolocation error of GEDI data. The main factor that affects the extraction accuracy of canopy height is vegetation cover， followed by slope； while the extraction accuracy of ground elevation is significantly affected by the aspect and slope. Additionally， the results also indicated that the estimation accuracy is high when the vegetation cover is more than 25%， and the accuracies of ground elevation and canopy height are the highest in gentle slope area with slope 0~5°. Overall， this study will provide a basis for the screening and application of GEDI data.

Key words: Space-borne LiDAR GEDI Ground elevation Canopy height Accuracy assessment

Received: 09 June 2021 Published: 13 December 2022

ZTFLH:

P237

Corresponding Authors: Sheng Nie E-mail: 211904020014@home.hpu.edu.cn;niesheng@aircas.ac.cn

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	Zhihui Yuan
	Sheng Nie
	Hebing Zhang
	Cheng Wang
	Hongtao Wang
	Xiaohuan Xi

Cite this article:

Zhihui Yuan,Sheng Nie,Hebing Zhang,Cheng Wang,Hongtao Wang,Xiaohuan Xi. Accuracy Evaluation and Impact Analysis of GEDI Ground Elevation and Canopy Height. Remote Sensing Technology and Application, 2022, 37(5): 1056-1070.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2022.5.1056 OR http://www.rsta.ac.cn/EN/Y2022/V37/I5/1056

Fig.1 Study area and GEDI spot distribution map

Table 1 Parameter and path extraction of GEDI data products L2A and L2B

Table 2 Analysis table of different parameters corresponding to each experimental area

Fig.2 Scatter plot of GEDI canopy height and ground elevation estimation in each experimental area

Fig.3 RMSE changes of DTM and CHM before and after translation

Fig.4 Scatter plot of GEDI canopy height and ground elevation estimation in each experimental area after translation

Fig.5 Importance level ranking of canopy height and ground elevation

Fig.6 The order of importance level of canopy height and ground elevation in each experimental area

Fig.7 Variation of RMSE and R² of DTM with different slopes

Fig.8 Variation of RMSE and R² of CHM with different slopes

Fig.9 Variation of RMSE and R² of DTM with different aspect

Fig.10 Variation of RMSE and R² of CHM with different aspect

Fig.11 RMSE and R² variation of DTM with different coverage

Fig.12 Variation of RMSE and R² of CHM with different coverage

Fig.13 RMSE and R² change diagram of DTM with different azimuth in NIWO experimental area

Fig.14 Variation of RMSE and R² of CHM at different azimuth in NIWO experimental area

Fig.15 RMSE and R² variation of DTM at different acquisition time

Fig.16 RMSE and R² variation of CHM at different acquisition time

Fig.17 RMSE and R² diagrams of DTM with different beam types

Fig.18 RMSE and R² diagrams of CHM with different beam types

Fig.19 RMSE and R² diagrams of DTM of different vegetation types

Fig.20 RMSE and R² variation of CHM in different vegetation types

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