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Effect of leaf-on and leaf-off canopy conditions on forest height retrieval and modelling with ICESat-2 data

Authors :
Jialu Zhou
Yunyuan Deng
Sheng Nie
Jing Fu
Cheng Wang
Wenwu Zheng
Yue Sun
Source :
International Journal of Digital Earth, Vol 16, Iss 2, Pp 4831-4847 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

ABSTRACTIce, Cloud, and land Elevation Satellite-2 (ICESat-2) provides effective photon-counting light detection and ranging (LiDAR) data for estimating forest height across extensive geographical areas. Although prior studies have illustrated canopy conditions during leaf-on and leaf-off phases may influence ICESat-2 derived forest heights, a comprehensive understanding of this effect remains incomplete. This study seeks to comprehensively assess how varying canopy conditions (leaf-on/leaf-off) affect ICESat-2 forest height retrieval and modelling. First, the accuracies of ICESat-2 terrain and canopy heights under leaf-on and leaf-off conditions were validated. Second, random forest algorithm was utilized to model forest height by integrating ICESat-2, Sentinel-2, and other ancillary datasets. Finally, we evaluated the influence of leaf-on and leaf-off conditions on forest height retrieval and modelling. Results reveal higher consistency between ICESat-2 and airborne LiDAR-derived terrain heights compared to the agreement between two canopy height datasets. Accuracies of ICESat-2 terrain and canopy heights are higher under leaf-off conditions in contrast to leaf-on conditions. Notably, the accuracies of ICESat-2 terrain and canopy heights under various conditions are closely linked to canopy cover. Furthermore, the accuracy of forest height modelling can be enhanced by combining ICESat-2 data collected during both leaf-on and leaf-off seasons with further eliminating low-quality samples.

Details

Language :
English
ISSN :
17538947 and 17538955
Volume :
16
Issue :
2
Database :
Directory of Open Access Journals
Journal :
International Journal of Digital Earth
Publication Type :
Academic Journal
Accession number :
edsdoj.fbfad4bbf6834bc292c44b9a88d39af0
Document Type :
article
Full Text :
https://doi.org/10.1080/17538947.2023.2285807