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Spaceborne LiDAR for characterizing forest structure across scales in the European Alps

Authors :
Lisa Mandl
Ana Stritih
Rupert Seidl
Christian Ginzler
Cornelius Senf
Source :
Remote Sensing in Ecology and Conservation, Vol 9, Iss 5, Pp 599-614 (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract The launch of NASA's Global Ecosystem Dynamics Investigation (GEDI) mission in 2018 opens new opportunities to quantitatively describe forest ecosystems across large scales. While GEDI's height‐related metrics have already been extensively evaluated, the utility of GEDI for assessing the full spectrum of structural variability—particularly in topographically complex terrain—remains incompletely understood. Here, we quantified GEDI's potential to estimate forest structure in mountain landscapes at the plot and landscape level, with a focus on variables of high relevance in ecological applications. We compared five GEDI metrics including relative height percentiles, plant area index, cover and understory cover to airborne laser scanning (ALS) data in two contrasting mountain landscapes in the European Alps. At the plot level, we investigated the impact of leaf phenology and topography on GEDI's accuracy. At the landscape‐scale, we evaluated the ability of GEDIs sample‐based approach to characterize complex mountain landscapes by comparing it to wall‐to‐wall ALS estimates and evaluated the capacity of GEDI to quantify important indicators of ecosystem functions and services (i.e., avalanche protection, habitat provision, carbon storage). Our results revealed only weak to moderate agreement between GEDI and ALS at the plot level (R2 from 0.03 to 0.61), with GEDI uncertainties increasing with slope. At the landscape‐level, however, the agreement between GEDI and ALS was generally high, with R2 values ranging between 0.51 and 0.79. Both GEDI and ALS agreed in identifying areas of high avalanche protection, habitat provision, and carbon storage, highlighting the potential of GEDI for landscape‐scale analyses in the context of ecosystem dynamics and management.

Details

Language :
English
ISSN :
20563485
Volume :
9
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Remote Sensing in Ecology and Conservation
Publication Type :
Academic Journal
Accession number :
edsdoj.456932ab1d8f4b55b17be9c451721d18
Document Type :
article
Full Text :
https://doi.org/10.1002/rse2.330