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Tropical Forest, Geospatial Data & REDD+ (Paperback)
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Tropical Forest, Geospatial Data & REDD+ (Paperback)
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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 urbanisation 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 minimise 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
emphasises on remote sensing as a technique for ensuring the MRV of
REDD+ initiatives, taking into consideration its cost effectiveness
in implementation.
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