This is my PhD thesis, as part of CIFOR's Global Comparative Study (GCS) on REDD+ (Phase 2). I am currently working as postdoctoral researcher within Phase 3 of the GCS.
The new Paris Agreement, approved by 195 countries under the auspice of the United Nations Framework Convention on Climate Change (UNFCCC), calls for limiting global warming to "well below" 2°Celsius. An important part of the climate agreement relates to reducing emissions from deforestation and forest degradation, and enhancing carbon stocks (REDD+) in non-Annex I (mostly developing) countries.
Within the REDD+ framework, participating countries are given incentives to develop national strategies and implementation plans that reduce emissions and enhance sinks from forests and to invest in low carbon development pathways. For REDD+ activities to be effective, accurate and robust methodologies to estimate emissions from deforestation and forest degradation are crucial. Remote sensing is an essential REDD+ observation tool, and in combination with ground measurements it provides an objective, practical and cost-e ective solution for developing and maintaining REDD+ monitoring systems.The remote sensing monitoring objective for REDD+ is not only to map deforestation but also to support policy formulation and implementation. Identifying and addressing drivers and activities causing forest carbon change is crucial in this respect. Despite the importance of identifying and addressing drivers, quantitative information on these drivers, and the related carbon emissions, is scarce at the national level.
Most tropical developing countries have a limited capacity for monitoring forest area change and carbon stocks. There is progress being made regarding several gaps (e.g. data, remote sensing methodologies, capacity building) and approaches are being put forward to manage the challenges associated with monitoring tropical forests for REDD+. However, many gaps still remain and knowledge about and experience with various remote sensing data sources and methods for forest monitoring for REDD+ is scattered among researchers and practitioners.
This thesis explores the role of remote sensing for monitoring tropical forests for REDD+ in general, and for assessing land use and related carbon emissions linked to drivers of tropical deforestation in particular.
My PhD thesis can be downloaded here.
The project ran from 2011 until 2016.