Methods for estimating volume, biomass and tree species diversity using field inventory and airborne laser scanning in the tropical forests of Tanzania.
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Date
2015
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Publisher
Norwegian University of Life Sciences
Abstract
Deforestation and forest degradation in the tropical countries have reduced the extent of forest
and woodlands, which conserve biodiversity, provide essential resources to people and help
in mitigating climate change through carbon sequestration. Forest conservation projects need
methods for estimating tree species diversity to effectively generate information necessary for
implementing biodiversity management plans, while greenhouse gas reduction programmes
such REDD* (Reducing Emissions from Deforestation and Forest Degradation) require
robust methods to estimate volume and aboveground biomass (AGB). Such methods are also
needed in the context of general forest management planning. The four papers included in this
thesis are aimed to test and evaluate methods for estimating volume. AGB. and tree species
diversity using field and remotely sensed data in the tropical forests and woodlands of
Tanzania. In paper 1. tree models for estimating total, merchantable stem, and branch volume
applicable for the entire miombo woodlands of Tanzania were developed. In Paper II. Ill. and
IV the potential of airborne laser scanning (AI.S) data for predicting AGB and measures of
tree species diversity was tested and evaluated. The results have shown that ALS data can be
used for predicting AGB with reasonable accuracy by using both parametric and nonparametric
approaches. Effects of plot size on the AGB estimates were investigated and the
results indicated that the prediction accuracy of AGB in ALS-assisted inventories improved
as the plot size increased. Finally, the results showed that measures of tree species diversity
and particularly tree species richness and Shannon diversity index, can potentially be
predicted by using ALS data.
Description
PhD Thesis
Keywords
Tree species diversity, Biomass, Field inventory, Airborne laser scanning, Deforestation, Tanzania