Ram Avtar (EDT) Tropical Forest, Geospatial Data and REDD+

Annotation

With an increasing role of tropical forests supporting a range of ecosystem services, biodiversity conservation, water regulation, soil conservation, timber, non-timber forest products, carbon sequestration, and climate change mitigation, the importance of forest resources management has become very crucial. The tropical forests of Indochina countries are rich in biodiversity and carbon density, and thus are significant from social, ecological, political and economic aspects. These forests provide essential livelihoods to the local and indigenous people. Rapid economic growth, agriculture expansion, illegal logging, population growth, and urbanization have been reported as major contributors to almost all cases of deforestation. Due to rapid development, forest resources are at a great risk. The FRA 2010 report shows that deforestation caused a loss of about 13 million hectares of tropical forests per year from the year 2000 to 2010. Therefore, there is an urgent need for better management of these resources. This book partially contributes towards climate change mitigation by implementing the Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanism. To mitigate climate change, most present studies are now concentrated on afforestation, reforestation and reducing deforestation and degradation. This book is focused on the application of multi-sensor remote sensing techniques to manage Cambodian forests for the effective implementation of the REDD+ mechanism. In this context, it is important to obtain reliable and consistent information of (a) forest cover, (b) deforestation, and (c) forest biomass to estimate CO2 emissions for the improvement of national carbon accounting. Additionally, this information will also be used for the development of the measurement, reporting and verification (MRV) system and for the management of forest resources to support sustainable forest management. Current knowledge is very limited with regard to the MRV system for REDD+ mechanism implementation. This book demonstrates the use of multi-sensor remote sensing techniques to manage the forest resources more sustainably. Further, it includes a concept on how precisely we can measure various forest parameters to minimize the uncertainty and to validate the results based on field data. The study is very much interdisciplinary in nature. It integrates core remote sensing techniques with the socio-economic angle of the REDD+ mechanism. It emphasizes on remote sensing as a technique for ensuring the MRV of REDD+ initiatives, taking into consideration its cost effectiveness in implementation.