RMIT University
Browse

Intercomparison of Real and Simulated GEDI Observations across Sclerophyll Forests

journal contribution
posted on 2024-11-02, 20:32 authored by Sven Huettermann, Simon JonesSimon Jones, Mariela Soto-BerelovMariela Soto-Berelov, Samuel HislopSamuel Hislop
Forest structure is an important variable in ecology, fire behaviour, and carbon management. New spaceborne lidar sensors, such as the Global Ecosystem Dynamics Investigation (GEDI), enable forest structure to be mapped at a global scale. Virtual GEDI-like observations can be derived from airborne laser scanning (ALS) data for given locations using the GEDI simulator, which was a tool initially developed for GEDI’s pre-launch calibration. This study compares the relative height (RH) and ground elevation metrics of real and simulated GEDI observations against ALS-derived benchmarks in southeast Australia. A total of 15,616 footprint locations were examined, covering a large range of forest types and topographic conditions. The impacts of canopy cover and height, terrain slope, and ALS point cloud density were assessed. The results indicate that the simulator produces more accurate canopy height (RH95) metrics (RMSE: 4.2 m, Bias: ?1.3 m) than the actual GEDI sensor (RMSE: 9.6 m, Bias: ?1.6 m). Similarly, the simulator outperforms GEDI in ground detection accuracy. In contrast to other studies, which favour the Gaussian algorithm for ground detection, we found that the Maximum algorithm performed better in most settings. Despite the determined differences between real and simulated GEDI observations, this study indicates the compatibility of both data sources, which may enable their combined use in multitemporal forest structure monitoring.

History

Journal

Remote Sensing

Volume

14

Number

2096

Issue

9

Start page

1

End page

16

Total pages

16

Publisher

MDPI

Place published

Switzerland

Language

English

Copyright

Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Former Identifier

2006116822

Esploro creation date

2023-01-06

Usage metrics

    Scholarly Works

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC