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Large-scale estimation of aboveground biomass in miombo woodlands using airborne laser scanning and national forest inventory data

Timothy Gregoire and 7 other contributors

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    Abstract

    Airborne laser scanning (ALS) has been proposed as a reliable remote sensing technique for supporting biomass and carbon stock estimation under the United Nations Collaborative Program on Reducing Emissions from Deforestation and Forest Degradation in developing countries (UN-REDD). Under the United Nations Framework Convention on Climate Change (UNFCCC), developing countries can receive financial benefits from REDD+ activities upon the implementation of reliable measuring, verification, and reporting mechanisms. As a UN-REDD country, Tanzania has implemented the National Forestry Resources Monitoring and Assessment (NAFORMA) program as a cost-efficient solution for providing an appropriate level of precision required for sustainable forest management practices, and for international reporting on carbon pools and carbon pools change estimates at national and regional scales. The main objective of the study was to investigate various design- and model-based sampling strategies incorporating ALS measurements for estimation of aboveground biomass (AGB) in miombo woodlands. The field data consisted of 65 clusters containing 513 circular NAFORMA ground plots located in Liwale District (15,867 km(2)), southeastern Tanzania, on which the aboveground tree biomass was estimated using locally developed allometric models. The ALS measurements were acquired along 32 parallel flight lines oriented in the east west direction, covering nearly 26% of Liwale District The flight lines were spaced 5 km apart and were distributed over the ground plots. Compared to the uncertainty (standard error) of the field-based estimate (4.79 Mg ha(-1)), the uncertainties of the ALS-assisted AGB estimates were consistently lower, varying from 1.73 Mg ha(-1) up to 252 Mg ha(-1) under two-stage cluster sampling, and 1.96 Mg ha(-1) for double sampling with regression estimation. Finally, strengths and shortcomings of using the NAFORMA inventory for ALS-assisted biomass estimation were discussed, underlining the implications of the field inventory design. Importantly, this study reveals the difficulty of accommodating a double sampling for stratification design, which was employed for NAFORMA, with an ALS survey having the flight lines systematically positioned over the landscape. (C) 2016 Elsevier Inc. All rights reserved.