Forest monitoring: issues and good practices in sample-based area estimation
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REDD+ and greenhouse gas reporting for the agriculture, forestry and other land use (AFOLU) sector requires land use changes to be characterized to estimate the associated greenhouse gas emissions or absorptions. It is becoming increasingly common for countries to track these changes using visually interpreted, sample-based approaches. Known as sample-based area estimation, the technique has been widely used in recent years in the generation of activity data for REDD+ Monitoring Reporting and Verification (MRV). However, implementing countries and agencies have repeatedly highlighted the lack of guidance on certain frequently encountered issues with this approach. This paper responds to this need for guidance by trying to address the most urgent technical issues faced by countries relating to sample based area estimation. Among others, it tackles issues such as how to best monitor beyond deforestation or for multiple purposes, how to account for variability between interpreters looking at the same satellite image, what type of sample unit to use and how many measurements are needed per sample unit. Existing good practices are consolidated, and new good practices are proposed as solutions where appropriate. The paper also indicates areas of future research, which should be pursued to answer the remaining questions surrounding area estimation. This paper will enable donors, academia, and countries that currently use or that want to use sample based area estimation for generating activity data for REDD+ or for other purposes. This paper is conceived to gain an overview of the most pressing research needs in the area and to delve into current good practice and existing literature. It will give non-experts an overview of area estimation, its applications and limitations.
Keywords: area estimation, REDD+, statistics, remote sensing, forest monitoring
ID: 3481211