Estimation of Forest Degradation with Remote Sensing and GIS Analysis – University of Copenhagen

Estimation of Forest Degradation with Remote Sensing and GIS Analysis

- the case of REDD+ in Tanzania

PhD defence

Klaus Dons


Our global climate system is changing and there is now broad agreement among climate scientists that changes are most likely human induced and primarily caused by CO2 emissions to the atmosphere. One important source of carbon emissions is forest disturbance by various anthropogenic activities. This has led to the establishment of a globally accepted forest based climate change mitigation system with the purpose to Reduce Emissions from Deforestation and forest Degradation while at the same time establish forest enhancement, sustainable management of forests, and forest conservation (REDD+). An indirect remote sensing (RS) approach has been suggested to map the infrastructure used for degradation rather than the actual change in forest canopy cover. This offers a way to delineate intact forest land and to model and estimate emissions from forest degradation in the non‐intact forest land – thereby simplifying Monitoring, Reporting and Verification as well as reducing monitoring costs. With dry forests in Tanzania as case, this PhD‐project assesses the applicability of direct and indirect RS approaches to estimate biomass loss by some of the most significant degradation activities here including charcoal production and wood extraction for fuel and construction. In the papers of this PhD dissertation various approaches and instruments were located, tested and recommended for application to identify and estimate subsistence wood extraction and charcoal production using optical satellites.

Principal Supervisor

Professor Carsten Smith-Hall, Department of Food and Resource Economics, University of Copenhagen

Assessment Committee

Professor Niels Strange, Department of Food and Resource Economics, University of Copenhagen (chairman);

Senior Research Associate Marije Schaafsma, Centre for Social and Economic Research on the Global Environment, University of East Anglia, UK;

Professor Rogers Ernest Malimbwi, Sokoine University of Agriculture, Morogoro, Tanzania.