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International Institute for Geo-information Science & Earth Observation (ITC) 2002

Estimating terrestrial carbon sequestered in aboveground woody biomass from remotely sensed data : the use of SEBAL and CASA algorithms in a semi arid area of Serowe Botswana

Nenge Namayanga, L.

Titre : Estimating terrestrial carbon sequestered in aboveground woody biomass from remotely sensed data : the use of SEBAL and CASA algorithms in a semi arid area of Serowe Botswana

Auteur : Nenge Namayanga, L.

Etablissement de soutenance : International Institute for Geo-information Science & Earth Observation (ITC) Netherlands

Grade : Master of Science Degree in Environmental Systems Analysis and Management (2002)

Résumé
Lack of cheaper, precise, universally applicable, and environmentally benign approaches in the quantification of carbon sequestered in aboveground woody biomass has contributed to the controversial ratification and slow implementation of the Kyoto Protocol. However, the drafting of the Kyoto Protocol has made the subject of carbon sequestration become stronger and more important. Many researchers have shown that dry matter (biomass) is a timeintegrated product of fractional photosynthetically active radiation ( ƒ PAR) and incoming solar radiation (K ↓ ). This research study explored the use of remote sensing and GIS in the estimation of carbon sequestered in a semi-arid area through the use of the Surface Energy Balance Algorithm for Land (SEBAL) and the Carnegie Ames, Stanford Approach (CASA). Having allometrically estimated the aboveground woody biomass in-situ and consequently the amount of carbon sequestered in t/ha, remotely sensed data was used to estimate the amount of carbon sequestered over the same area. Field estimations of fresh weight aboveground woody biomass in Serowe-Botswana gave an average biomass stock of 13 ± 3 t/ha translating to 3.9 ± 0.5 tC/ha over the entire study area. Carbon stock values ranged from 52 tC/ha in the sandveld stratum to 150 tC/ha in the escarpment woodland. The SEBAL-CASA remote sensing approach yielded a negative value of 11 ± 0.7 t/ha convertible to a negative value of 5 ± 0.3 tC/ha. The estimated difference for the two approaches thence gave a value of 8.93 suggesting the acceptance of the alternate hypothesis. However, trends of the estimates of these methods correlate well. The high difference suggested by the statistics could be interpreted as the uncertainties associated with the use of limited meteorological data in the remote sensing approach. A carbon conversion factor specifically generated for the study area by means of laboratory analysis was found to be 0.43 and comparable to the factors of 0.46 and 0.5. Although the results in this study show a significant difference between the two methods, the remote sensing approach shows potential to accurately estimate carbon. Relationships between water, carbon and energy have been explored and gave an insight in the possible application of remote sensing in carbon monitoring and management projects when carbon becomes an internationally tradable commodity.

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