Ponce Hernandez, Raul

In this thesis, a methodological framework for the assessment and monitoring of forest degradation based on remote sensing techniques and field data, as part of the REDD+ programme, is presented. The framework intends to support the implementation of a national Monitoring, Verification and Report (MRV) system in developing countries. The framework proposed an operational definition of forest degradation and a set of indicators, namely Canopy Cover (CC), Aboveground Biomass (AGB) and Net Primary Productivity (NPP), derived from remote sensing data. The applicability of the framework is tested in a sub-deciduous tropical forest in the Southeast of Mexico. The results from the application of the methodological framework showed that the higher rates of forest degradation, 1596-2865 ha·year-1, occur in areas with high population density. Estimations of aboveground biomass in these degraded areas span from 1 to 24 Mg·ha-1, with a rate of carbon fixation ranging from 130 to 246 gC·m2·year. The results also showed that 43 % of the forests of the study area remain with no evident signs of degradation, as detected by the indicators selected, during the period evaluated. The integration of the different elements conforming the methodological framework for the assessment and monitoring of forest degradation enabled the identification of areas that maintain a stable condition and areas that change over the period evaluated. The methodology outlined in this thesis also allows for the identification of the temporal and spatial distributions of forest degradation based on the indicators selected, and it is expected to serve as the basis for operations of the REDD+ programme with the appropriate adaptations to the area in turn.

Author Keywords: Forest degradation, Monitoring, REDD+, Remote Sensing, Tropical forest