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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorAvitabile, V.
dc.contributor.authorSuijker, W.
dc.date.accessioned2016-07-19T17:00:40Z
dc.date.available2016-07-19T17:00:40Z
dc.date.issued2016
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/22774
dc.description.abstractThis explorative study provides a characterisation of forest gain processes and related carbon sequestration in Indonesia from 1990-2015. Satellite imagery and biomass datasets are analysed to characterise forest gain and related carbon sequestration. Global forest resource assessments from the Food and Agricultural Organisation (FAO, 2010), the Joint Research Centre (JRC, 2014) and Hansen et al. (2013) are compared. The identified areas of forest gain are visually interpreted using satellite imagery to validate whether gain occurred and to characterise for relevant attributes such as origin, former coverage, tree canopy cover density and dispersion pattern. The characterised gain is used to quantify related carbon sequestration using biomass data from Langner et al. (2014) and IPCC (2006). The results reveal significant discrepancies between the existing datasets. Dissimilarities are found in the magnitude and the location of forest gain and related carbon sequestration. Compared to all Indonesian territory, the proportions of forest gain are 0.4% for FAO, 0.6% for JRC and 3.1% for Hansen. Carbon sequestration due to forest gain is estimated at 698.6 tons C per km² per year for FAO. For JRC and Hansen this is 600.8 and 883.5 tons C per km² per year respectively. The origin of forest gain is predominantly natural gain. For FAO natural carbon sequestration is estimated at 5.2 times planted carbon sequestration. For JRC this ratio is 2.2 to 1.
dc.description.sponsorshipUtrecht University
dc.format.extent2457435
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleCharacterising forest gain and related carbon sequestration using existing datasets
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsForest Gain, Carbon Sequestration, Land-use Monitoring, Visual Interpretation, Data Resemblance
dc.subject.courseuuGeographical Information Management and Applications (GIMA)


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