Modelling Aboveground Biomass of Miombo Woodlands in Niassa Special Reserve, Northern Mozambique

Orlando A Macave,Aniceto Chaúque,Ana I Ribeiro,Romana Bandeira,Cristina Branquinho,Robert Washington-Allen,Natasha S Ribeiro

doi:10.3390/f13020311

Orlando A Macave, Aniceto Chaúque + Show 5 more

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https://doi.org/10.3390/f13020311

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Abstract

Aboveground biomass (AGB) estimation plays a crucial role in forest management and carbon emission reporting, especially for developing countries wishing to address REDD+ projects. Both passive and active remote-sensing technologies can provide spatially explicit information of AGB by using a limited number of field samples, thus reducing the substantial budgetary cost of field inventories. The aim of the current study was to estimate AGB in the Niassa Special Reserve (NSR) using fusion of optical (Landsat 8/OLI and Sentinel 2A/MSI) and radar (Sentinel 1B and ALOS/PALSAR-2) data. The performance of multiple linear regression models to relate ground biomass with different combinations of sensor data was assessed using root-mean-square error (RMSE), and the Akaike and Bayesian information criteria (AIC and BIC). The mean AGB and carbon stock (CS) estimated from field data were estimated at 56 Mg ha−1 (ranging from 11 to 95 Mg ha−1) and 28 MgC ha−1, respectively. The best model estimated AGB at 63 ± 20.3 Mg ha−1 for NSR, ranging from 0.6 to 200 Mg ha−1 (r2 = 87.5%, AIC = 123, and BIC = 51.93). We obtained an RMSE % of 20.46 of the mean field estimate of 56 Mg ha−1. The estimation of AGB in this study was within the range that was reported in the existing literature for the miombo woodlands. The fusion of vegetation indices derived from Landsat/OLI and Sentinel 2A/MSI, and backscatter from ALOS/PALSAR-2 is a good predictor of AGB.

Highlights

Forest ecosystems have become the focus of international efforts to mitigate the effects of climate change due to their role in carbon sequestration, combating desertification, maintaining biodiversity and protecting soil and water resources [1]
Our results from the stand data indicated that the mean Aboveground biomass (AGB) in Niassa Special Reserve (NSR) was 56 Mg ha−1, ranging from 11 to 95 Mg ha−1 (Table 3)
These estimations are within the range that was reported in the existing literature for this type of forest

Summary

Introduction

Forest ecosystems have become the focus of international efforts to mitigate the effects of climate change due to their role in carbon sequestration, combating desertification, maintaining biodiversity and protecting soil and water resources [1]. The miombo woodlands are the largest dryland forest ecosystem in Sub-Saharan Africa, with an area that extends to approximately 1.9 million km distributed across seven countries (Mozambique, Malawi, Tanzania, Zimbabwe, Zambia, Angola, and Democratic Republic of Congo [4,5]). These countries are among the poorest globally, and the high dependence of the human population on these woodlands imposes many challenges in conserving this important ecosystem [6,7,8]. This financing mechanism was globally adopted to compensate developing countries for actions taken to reduce carbon dioxide from atmosphere [10,11]

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