Methods for estimating volume, biomass and tree species diversity using field inventory and airborne laser scanning in the tropical forests of Tanzania

Ernest William Mauya successfully defended his doctoral thesis, “Methods for estimating volume, biomass and tree species diversity using field inventory and airborne laser scanning in the tropical forests of Tanzania”, on October 28, 2015.

The topic for the trial lecture was “Using airborne laser scanning in the Tanzanian national forest inventory to estimate changes to biomass and carbon stocks over time for REDD+/MRV – Application and Challenges”. We congratulate!

Thesis 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 I, tree models for estimating total, merchantable stem, and branch volume applicable for the entire miombo woodlands of Tanzania were developed. In Paper II, III, and IV the potential of airborne laser scanning (ALS) 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 non-parametric 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.

Supervisors

Professor Tron Eid (main supervisor) (INA, NMBU)
Professor Erik Næsset (INA, NMBU)
Professor Terje Gobakken (INA, NMBU)
Dr. Ole Martin Bollandsås (INA, NMBU)
Dr. Eliakimu Zahabu (Dept. of Forest Mensuration and Management, Sokoine University of Agriculture)

Evaluation committee

Dr. Ross Nelson (Hydrospheric and Biospheric Sciences Lab, NASA/Goddard Space Flight Center)
Associate Professor Henrik Meilby (Dept. of Food and Natural Resource Management, Copenhagen University)
Professor Ole Hofstad (INA, NMBU)

Reference

  • Mauya, E. W.. ((2015). Methods for estimating volume, biomass and tree species diversity using field inventory and airborne laser scanning in the tropical forests of tanzania.). PhD Thesis.
    [Bibtex]
    @PhdThesis{Mauya2015,
    Title = {Methods for estimating volume, biomass and tree species diversity using field inventory and airborne laser scanning in the tropical forests of Tanzania},
    Author = {Mauya, E.W.},
    School = {Norwegian University of Life Sciences},
    Year = {2015},
    Owner = {hanso},
    Timestamp = {2016.03.02},
    Url = {https://static02.nmbu.no/mina/forskning/drgrader/2015-Mauya.pdf}
    }