This article proposes a framework for integrating community-collected data with remote sensing in national forest monitoring systems for REDD+ Measuring, Reporting and Verifying (MRV). It is based on an assessment of forest monitoring data (mostly related to forest change) collected by local monitors in the UNESCO Kafa Biosphere Reserve, Ethiopia. It uses professional ground measurements and satellite imagery as validation data to assess 700 locally collected forest change observations. The paper examines the complementarity of local and remote data, by assessing data quality in terms of spatial, temporal and thematic factors.
The paper finds that locally collected data can usefully complement remote sensing data, providing detailed information on forest change and its causes. Although the locally collected data were found to be sufficiently accurate, this did not systematically cover the full area (most collections were within reach of roads) and depended on weather and motivations of the collector. Changes in forest canopy cover can happen gradually, and local monitors tend to report land cover change at a later point than remote sensing analysts do. Nonetheless, the authors conclude that the system does have the potential to be scaled up to the national level. This study also found that mobile devices (with Open Data Kit forms) had advantages over paper forms, in terms of collecting photographs, data collection and transmission.