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Forestry Carbon Sequestration and Trading: a Case study of Mau Forest Complex in Kenya
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management.
2015 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Sustainable development
The essay/thesis is mainly on sustainable development according to the University's criteria
Abstract [en]

The global temperature is at an all-time high, the polar ice is melting, the sea levels are rising and the associated disasters are a time bomb. These variations in temperature are thought to trace roots to anthropogenic sources. In order to mitigate these changes and slow down the rate of warming, several efforts have been made locally and internationally. One of the agreed up-on way to do this is by using forests as reservoirs for carbon since carbon is one of those greenhouses gasses responsible for the warming. Mau forest, in Kenya, is one of those ecosystems where degradation has happened tremendously, though still viewed as a potential site for reclamation.

Using GIS and remote sensing analysis of Landsat images, the study sought to compare various change detection techniques, find the amount of biomass lost or gained in the forest and the possible income accrued in case the forest is placed under the Kyoto protocol’s Clean Development Mechanism (CDM). Various vegetation ratios were used in the study ranging from NDVI, NDII to RSR. The results obtained from these ratios were not quite convincing as setting threshold for the ratios to separate dense forest from other forms of vegetation was not straightforward. As a consequence, the three ratios NDVI, NDII and RSR were combined and substituted for RGB bands respectively. A classification was done using this combination and the results compared to classifications based on tasselled cap and principal component analysis (PCA).

The results of the various methods showed that the forest has lost its biomass over time. The methods indicated that the section of the forest studied lost between 8088 ha and 9450 ha of dense forest land between 1986 and 2010. This is between 29% and 35% of forest cover lost depending on the various methods of change detection used. This acreage when converted into forest biomass at a rate of 236 Mg.ha-1 gives a value of between 1908768 tons and 2230200 tons of carbon. If the Mau forest were registered as Kyoto compliant, then in the carbon market, this would have been a loss of between $24.1m and $ 28.2m according to California carbon dashboard (28th, May 2015). This is a huge sum of money if paid to a rural community as benefits from carbon sequestration via forestry. Such are the amounts that a community can earn by protecting a forest for the purposes of carbon sequestration and trading.

Place, publisher, year, edition, pages
2015. , 33 p.
Keyword [en]
carbon, indices, NDVI, change detection, biomass, remote sensing
National Category
Geosciences, Multidisciplinary
URN: urn:nbn:se:hig:diva-20870OAI: diva2:882491
Subject / course
Educational program
Geomatics – master’s programme (one year) (swe or eng)
2015-06-09, 11:215, Kungsbäcksvägen 47, 801 76 Gävle, Sweden, Gävle, 14:00 (English)
Available from: 2016-01-29 Created: 2015-12-15 Last updated: 2016-01-29Bibliographically approved

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Department of Industrial Development, IT and Land Management
Geosciences, Multidisciplinary

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