Assessing the Accuracy of GEDI Data for Canopy Height and Aboveground Biomass Estimates in Mediterranean Forests

Iván Dorado-Roda,Juan Guerra-Hernández,Sergio Godinho,Carlos Silva,Adrián Pascual,Eduardo González-Ferreiro,Pablo Rodríguez-Gonzálvez,Brigite Botequim

doi:10.3390/rs13122279

Abstract

Global Ecosystem Dynamics Investigation (GEDI) satellite mission is expanding the spatial bounds and temporal resolution of large-scale mapping applications. Integrating the recent GEDI data into Airborne Laser Scanning (ALS)-derived estimations represents a global opportunity to update and extend forest models based on area based approaches (ABA) considering temporal and spatial dynamics. This study evaluates the effect of combining ALS-based aboveground biomass (AGB) estimates with GEDI-derived models by using temporally coincident datasets. A gradient of forest ecosystems, distributed through 21,766 km2 in the province of Badajoz (Spain), with different species and structural complexity, was used to: (i) assess the accuracy of GEDI canopy height in five Mediterranean Ecosystems and (ii) develop GEDI-based AGB models when using ALS-derived AGB estimates at GEDI footprint level. In terms of Pearson’s correlation (r) and rRMSE, the agreement between ALS and GEDI statistics on canopy height was stronger in the denser and homogeneous coniferous forest of P. pinaster and P. pinea than in sparse Quercus-dominated forests. The GEDI-derived AGB models using relative height and vertical canopy metrics yielded a model efficiency (Mef) ranging from 0.31 to 0.46, with a RMSE ranging from 14.13 to 32.16 Mg/ha and rRMSE from 38.17 to 84.74%, at GEDI footprint level by forest type. The impact of forest structure confirmed previous studies achievements, since GEDI data showed higher uncertainty in highly multilayered forests. In general, GEDI-derived models (GEDI-like Level4A) underestimated AGB over lower and higher ALS-derived AGB intervals. The proposed models could also be used to monitor biomass stocks at large-scale by using GEDI footprint level in Mediterranean areas, especially in remote and hard-to-reach areas for forest inventory. The findings from this study serve to provide an initial evaluation of GEDI data for estimating AGB in Mediterranean forest.

Highlights

Our results demonstrate that a specific second metric related to canopy cover (CCGEDI ) from Light Detection and Ranging (LiDAR) waveforms is potentially useful for improving most of the models (Table 6)
The results showed the accuracy in canopy height from the Level 2A (L2A) products using upper metrics from Airborne Laser Scanning (ALS)
Our study highlighted the difficulty in differentiating aboveground biomass (AGB) and characterizing vegetation structure under sparse forest cover, which is characteristic of Mediterranean forests

Summary

Introduction

Based on the general FAO definition of forests, there were an estimated 88 million ha of forest area in Mediterranean countries in 2015, occupying the 10.04% of the total area of Remote Sens. 2021, 13, 2279 these countries and representing 2.20% of the world’s total forest area [1]. Effective large-scale monitoring of Mediterranean forest ecosystem has a critical role for adapting to climate change [3,4]. Panel on Climate Change (IPCC) is to use a combination of Earth observation (EO) data and field-based inventories to estimate the forest area, carbon stocks, and changes [5]. Nationwide surveys in the form of a National Forest Inventory (NFI) have contributed by means of extensive fieldwork campaigns to monitor the dynamics of the Land Use, Land

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