Projecting deforestation trends on Espiritu Santo island, Vanuatu, using a spatial modeling approach : a case study to develop a spatially explicit forest reference emission level for REDD+
As agreed under United Nations Framework Convention on Climate Change, activities reducing emissions from deforestation, forest degradation, sustainable management of forests, enhancement and conservation of forest carbon stocks (REDD+) provide financial incentives to countries mitigating climate ch...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2015 |
| País: | Ecuador |
| Institución: | Universidad San Francisco de Quito |
| Repositorio: | Repositorio Universidad San Francisco de Quito |
| OAI Identifier: | oai:repositorio.usfq.edu.ec:23000/4093 |
| Acceso en línea: | http://repositorio.usfq.edu.ec/handle/23000/4093 |
| Access Level: | acceso abierto |
| Palabra clave: | Centros culturales - Diseño y construcción - Otavalo (Ecuador) Centros culturales - Arquitectura Arquitectura Bellas artes |
| Sumario: | As agreed under United Nations Framework Convention on Climate Change, activities reducing emissions from deforestation, forest degradation, sustainable management of forests, enhancement and conservation of forest carbon stocks (REDD+) provide financial incentives to countries mitigating climate change. Countries are requested to develop so-called national forest reference levels (FRLs) as a benchmark to measure performance of land-use policy adjustments. FRLs are constructed combining information on the magnitude of anthropogenic interventions causing greenhouse gas (GHG) emissions (e.g. historic deforestation) with information capturing the changes in different forest carbon pools. Small-island countries face the particular challenge that their FRLs have to be developed in a sparse data environment. Poor satellite coverage in the past hampers the reconstruction of deforestation patterns. This thesis combines existing national deforestation data with global deforestation data and SAR-based deforestation detection to reconstruct evolving deforestation patterns across a twenty years period (1990-2010) in Espiritu Santo Island, Vanuatu, a country located in the South Pacific. The deforestation pattern is used as an input to Dinamica EGO, a spatial modeling environment projecting future trajectories based on spatial proxies capturing driver and underlying causes of deforestation. To estimate corresponding GHG emissions, an aboveground biomass map was derived from ALOS Palsar SAR data. Overall, a total of 3,296,823 tCO2e will be released under the business-as-usual scenario (BAU) over a period of 10 years (2011-2020). Uncertainties remain high due to the heterogeneity of optical and SAR data as well as suitable historical VHR data for verification purposes. |
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