Footprint Size Design of Large-Footprint Full-Waveform LiDAR for Forest and Topography Applications: A Theoretical Study

Yang, Xuebo; Wang, Cheng; Xi, Xiaohuan; Wang, Yingjie; Zhang, Ying; Zhou, Guoqing

doi:10.1109/tgrs.2021.3054324

Cited by 13 publications

(1 citation statement)

References 37 publications

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“…Good-quality GEDI data were recognized as footprints in leaf-on season (leaf_off_flag equal to 0) with quality_flag equal to 1, degrade_flag equal to 0, landsat_water_persistence lower than 10%, urban_proportion equivalent to 0, and topographic slope lower than 25 • . The utility of 25 • of the topographic slope is considered conservative for canopy height measurements of the GEDI waveform [35,45,46]. Notably, GEDI used six waveform preprocessing algorithms that used different thresholds for detecting signals above the noise and smoothing waveforms.…”

Section: Gedi Datasets and Their Pre-processingmentioning

confidence: 99%

A Framework for Improving Wall-to-Wall Canopy Height Mapping by Integrating GEDI LiDAR

et al. 2022

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Spatially continuous canopy height is a vital input for modeling forest structures and functioning. The global ecosystem dynamics investigation (GEDI) waveform can penetrate a canopy to precisely find the ground and measure canopy height, but it is spatially discontinuous over the earth’s surface. A common method to achieve wall-to-wall canopy height mapping is to integrate a set of field-measured canopy heights and spectral bands from optical and/or microwave remote sensing data as ancillary information. However, due partly to the saturation of spectral reflectance to canopy height, the product of this method may misrepresent canopy height. As a result, neither GEDI footprints nor interpolated maps using the common method can accurately produce spatially continuous canopy height maps alone. To address this issue, this study proposes a framework of point-surface fusion for canopy height mapping (FPSF-CH) that uses GEDI data to calibrate the initial wall-to-wall canopy height map derived from a sub-model of FPSF-CH. The effectiveness of the proposed FPSF-CH was validated by comparison to canopy heights derived from (1) a high-resolution canopy height model derived from airborne discrete point cloud lidar across three test sites, (2) a global canopy height product (GDAL RH95), and (3) the results of the FPSF-CH sub-model without fusing with the GEDI canopy height. The results showed that the RMSE and rRMSE of FPSF-CH were 3.82, 4.05, and 3.48 m, and 18.77, 16.24, and 13.81% across the three test sites, respectively. The FPSF-CH achieved improvement over GDAL RH95, with reductions in RMSE values of 1.28, 2.25, and 2.23 m, and reductions in rRMSE values of 6.29, 9.01, and 8.90% across the three test sites, respectively. Additionally, the better performance of the FPSF-CH compared with its sub-model further confirmed the effectiveness of integrating GEDI data for calibrating wall-to-wall canopy height mapping. The proposed FPSF-CH integrates GEDI LiDAR data to provide a new avenue for accurate wall-to-wall canopy height mapping critical to applications, such as estimations of biomass, biodiversity, and carbon stocks.

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Section: Gedi Datasets and Their Pre-processingmentioning

confidence: 99%