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Michigan State University (2015)

Landscape carbon measurement in systems of trees outside of forests : The case of agroforestry systems in rural savannas of Senegal

Dieng, Moussa

Titre : Landscape carbon measurement in systems of trees outside of forests : The case of agroforestry systems in rural savannas of Senegal

Auteur : Dieng, Moussa

Université de soutenance : Michigan State University

Grade : Doctor of Philosophy (PhD) 2015

Résumé
Monitoring forest cover changes and carbon content at regional and global level by using remote sensing has advanced significantly for closed humid tropical forests, and several methods have been developed. On the other hand monitoring of cover and carbon for semi-arid savannas and woodlands has been under-studied, and more methods are needed. Further, for systems of Trees Outside of Forests in semi-arid regions, monitoring of cover and carbon has not advanced at all, and new methods are needed. In this dissertation, I developed methods for remote sensing-assisted carbon measurement and monitoring in semi-arid landscapes of Trees Outside of Forests (TOF) which include : (1) Plantation and Agroforestry systems (2) Other trees on farms : planted trees (3) Other trees on farms : remnant savanna trees In this study, remote sensing satellite techniques were used to estimate carbon at a landscape level in savanna systems. Remote sensing tree crown projection area (CPA) was used as a proxy to predict tree diameter at breast height (DBH). A relationship was established between remote sensing based crown projection area (CPA) and the field-based DBH. Both simple linear and non-linear regression analysis were applied to the Sokone and Karang sites in Senegal. The linear function presents a higher coefficient of determination (R 2 ) in both sites with respectively R2 = 0.71 and R 2 = 0.79 for Sokone and Karang sites. The non-linear model shows R-squared values ranged between 0.61 and 0.77 for Sokone and Karang sites respectively. The regression equations derived from the relationship between remote sensing-based crown projection area (CPA) and the field-based DBH are used to predict the DBH of all trees within the study area knowing their crown projection area from remote sensing. A general allometric equation that uses DBH as a parameter to calculate biomass and carbon per tree was used in this study. My findings show that : (1) A model that uses remote-sensing assisted landscape-scale carbon stock measurement has promise ; (2) The relationship between CPA detected from remote sensing and allometric scaling is something that can be refined but seems to be a workable approach and these refinements would include an improved relationship model using non-linear relationships, developing a local allometric equation using destructive sampling, and specific parameters for the savanna or tree type/species and explore the use of automated detection. This study’s findings will be useful for the Senegalese government and others with savanna systems. With 1,043,000 ha of savanna systems and trees outside of forests (TOF), my findings could be an important step for integrating TOF into the natural resource management scheme for carbon stock estimation and the reduction of greenhouse gas emissions in the forestry sector. The use of remote sensing will lower the costs of field sampling based methods in highly patchy woodland and TOF landscapes and increase the opportunity for small holders and communities of small holders to be engaged in carbon mitigation projects. My findings show that, with a minimum training, they will be able to do the tree measurements in their own farms

Mots clés : Ecology, Landscape carbon measurement, Savannas, Macroecology, Agroforestry, Remote sensing , Biological sciences, Forestry

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Page publiée le 3 septembre 2015, mise à jour le 28 août 2017