Audience:
- Remote sensing specialist in countries reporting to REDD+
- Officials working on uncertainty and data analysis for carbon accounting
- Students of remote sensing in forestry applications
Reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) is a framework under the United Nations Framework Convention on Climate Change (UNFCCC) with the goal of building international cooperation to achieve climate mitigation from forests.
A core element of REDD+ MRV is the monitoring and tracking of forest conversions to other lands due to human activities. Satellite information is the data source with enough periodicity and coverage to provide information on land use, type and intensity of land changes, deforestation and forest degradation. In order to meet REDD+ reporting criteria of unbiasedness and uncertainty quantification, sampling-based approaches for the estimation of area and map accuracy are necessary. This e-learning course will introduce participants to the concept, rationale and how-to of sampling-based estimation.
Please Note: This course is available in different languages. Please select the best one for you:
- English: Course: Sampling-Based Estimation of Area and Map Accuracy (doi.gov)
- French: Course: Sampling-based Estimation of Area and Map Accuracy--French Version (doi.gov)
- Spanish: Course: Sampling-based Estimation of Area and Map Accuracy--Spanish Version (doi.gov)
- Vietnamese: Course: Sampling-based Estimation of Area and Map Accuracy--Vietnamese Version (doi.gov)
The online version of this course runs on the latest versions of Chrome and Safari. There is no downloadable version of the course currently.
Duration: Approximately 2 hours.
- Editing Trainer: Stacey Clarke
- Editing Trainer: Theresa Lane