Quantitative Assessment of the Earth Observation Data and Methods Used to Generate Reference Emission Levels for REDD+

In Satellite Earth Observations and Their Impact on Society and Policy

REDD+, a policy framework through which developing countries can receive incentives for reducing their greenhouse gas emissions in the forest sector, heavily relies upon Earth observation (EO) data for policy implementation. Thus the quality and quantity of the EO data used can have an impact on the effectiveness of REDD+. In this chapter, we: (1) evaluated the quality and quantity of the EO data currently being used by different countries and projects for REDD+, and (2) analyzed whether the EO data quality/quantity was determining the ways in which the countries/projects utilized the data; e.g. the number of REDD+ activities that emissions were assessed for (#activities) and the level of complexity of the models used to project future emissions (model_complexity]. We found that the EO data quality (spatial resolution of the EO imagery used) was basically uniform, while the data quantity (# of maps produced from EO data, length of historical timeframe for which EO data was used) varied considerably from country to country and project to project. However, regression analysis showed that neither #activities nor model_complexity were well explained by the EO data quality/quantity. This suggests that countries/projects are deciding which activities to assess and which modeling approaches to select based on other factors. Increasing the EO data quality and/or quantity may not have a significant impact on the effectiveness of REDD+ unless there are more detailed regulations on how the data should be used to estimate future emissions.

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