Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon

Abstract

NASA's Global Ecosystem Dynamic Investigation (GEDI) mission has been designed to measure forest structure using lidar waveforms to sample the earth's vegetation while in orbit aboard the International Space Station. In this paper, we used airborne large-footprint (LF) lidar measurements to simulate GEDI observations from which we retrieved ground elevation, vegetation height, and aboveground biomass (AGB). GEDI-like product accuracy was then assessed by comparing them to similar products derived from airborne small-footprint (SF) lidar measurements. The study focused on tropical forests and used data collected during the NASA and European Space Agency (ESA) AfriSAR ground and airborne campaigns in the Lope National Park in Central Gabon. The measurements covered a gradient of successional stages of forest development with different height, canopy density, and topography. The comparison of the two sensors shows that LF lidar waveforms and simulated waveforms from SF lidar are equivalent in their ability to estimate ground elevation (RMSE = 0.5 m, bias = 0.29 m) and maximum forest height (RMSE = 2.99 m,

Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data

“…In many recent studies, time series of synthetic aperture radar (SAR) data are analyzed to estimate biomass and its change over time from radar backscatter, for instance [5]. Based on the scientific evidence from local campaigns, dedicated spaceborne missions have been designed by space agencies in response to the urgent need of monitoring the health status of the forests of our planet: Global Ecosystem Dynamics Investigation Lidar (GEDI) from NASA [6], already operational, the forthcoming NASA-ISRO Synthetic Aperture Radar (NISAR) [7], and the forthcoming European Space Agency (ESA) BIOMASS [8].…”

An Analysis of Ground-Point Classifiers for Terrestrial LiDAR

“…Each collection platform has a unique associated scanner orientation, scan angle, point spacing, and laser footprint size, resulting in differences in their collected data [14][15][16][17][18][19][20]. ALS data typically exhibits an even point density distribution [19,21], a well-defined ground surface, a point spacing of roughly 0.5 m [22], and a laser footprint size of 10 cm-25 m [23]. Notably, a laser footprint size this large enables the collection of multiple returned points from a single laser pulse [24].…”

Impacto do manejo de precisão em florestas tropicais

“…Métricas de altura de dados Lidar em quatro parcelas de 1 hectares localizados em uma área de floresta umbrófila primária no estado do Acre. Cada uma das parcelas representa uma padrão distinto de estrutura da vegetação: (a) parcela com predominância de dossel aberto, presença de clareiras, árvores isoladas e ocorrência de espécies como bambu e cipós no estrato inferior da estrutura vertical; (b) parcela com clareiras em estágio de regeneração e presença de árvores jovens; (c) parcela com presença de árvores dominantes e co-dominantes, mas ainda com pequenas aberturas entre as copas; (d) parcela com predominância de dossel fechado, ausência de FIGUEIREDO; PAPA, 2014;LEFSKY, et al, 2002;SILVA, et al, 2018;STARK, et al, 2015;VASTARANTA, 2012…”

“…Um número crescente de estudos tem confirmado o uso do Lidar para estimar, modelar e caracterizar variáveis estruturais e ecológicas da cobertura florestal, como: individualização e abundância de árvores (FERRAZ et al, 2016;GORGENS et al, 2015;SILVA et al, 2016;YU et al, 2011); forma de copa (BARNES et al, 2017;FIGUEIREDO, 2014); índice de área foliar e perfil da vegetação (ALMEIDA et al, 2016;DETTO et al, 2015;STARK et al, 2012); área basal (MAGNUSSEN et al, 2012;LEFSKY et al, 1999); carbono e biomassa (D'OLIVEIRA et al, 2012;SILVA et al, 2015;MASCARO et al, 2011;GOBAKKEN, 2008;SILVA et al, 2018); e demografia das árvores (STARK et al, 2015).…”