Comparison of multi-source remote sensing data for estimating and mapping above-ground biomass in the West Usambara tropical montane forests
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Date
2023-06
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Journal ISSN
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Publisher
Elsevier B.V.
Abstract
Above-ground biomass (AGB) estimation is important to better understand the carbon cy-
cle and improve the efficiency of forest policy and management activities. AGB estimation
models, using a combination of field data and remote sensing data, can largely replace
traditional survey methods for measuring AGB. There are, however, critical steps for map-
ping AGB based on satellite data with an acceptable degree of accuracy, such as choice
of remote sensing data, the proper statistical modelling method, and remote sensing pre-
dictor variables, at known field locations. This study sought to identify the optimal op-
tical and synthetic aperture radar (SAR) remote sensing imagery from five sensors (Plan-
etScope, Sentinel-2, Landsat 8 OLI, ALOS-2/PALSAR-2, and Sentinel-1) to model 159 field-
based AGB values from two montane forests under semiparametric (Generalized Additive
Model; GAM) and non-parametric (eXtreme Gradient Boosting; XGB) approaches using in-
formation from four groups of predictor variables (spectral bands/polarizations, vegetation
indices, textures, and a combination of all). The study’s results showed that PlanetScope
(rRMSE = 69.19%; R 2 = 0.161) was the most precise optical sensor while ALOS-2/PALSAR-2
(rRMSE = 70.76; R 2 = 0.165) was the most precise amongst the SAR sensors. XGB mod-
els generally resulted in those with lower prediction errors as compared to GAMs for the
five sensors. Models having textures of vegetation indices and polarization bands achieved
greater accuracy than models that incorporated spectral bands/polarizations and vegeta-
tion indices only. The study recommends that PlanetScope and ALOS-2/PALSAR-2 remote
sensing data using the XGB-based technique is an appropriate approach for accurate lo-
cal and regional estimation of tropical forest AGB particularly for complex montane forest
ecosystems.
Description
Above-ground biomass (AGB) is crucial factor for forest ecosystems to carry out their ecological functions and is a vital
indicator of the capacity of forests to sequester carbon. The Global Climate Observing System recognizes AGB as a key pp.1-14