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Forests 2014, 5(10), 2464-2489; doi:10.3390/f5102464

Combining Satellite Data and Community-Based Observations for Forest Monitoring

1
Laboratory of Geo-information Science and Remote Sensing, Wageningen University, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands
2
The Nature and Biodiversity Conservation Union (NABU), Bonga, Southern Nations Nationalities and People's Region (SNNPR), Ethiopia
*
Author to whom correspondence should be addressed.
Received: 5 May 2014 / Revised: 20 September 2014 / Accepted: 6 October 2014 / Published: 14 October 2014
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Abstract

Within the Reducing Emissions from Deforestation and Degradation (REDD+) framework, the involvement of local communities in national forest monitoring activities has the potential to enhance monitoring efficiency at lower costs while simultaneously promoting transparency and better forest management. We assessed the consistency of forest monitoring data (mostly activity data related to forest change) collected by local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. Professional ground measurements and high resolution satellite images were used as validation data to assess over 700 forest change observations collected by the local experts. Furthermore, we examined the complementary use of local datasets and remote sensing by assessing spatial, temporal and thematic data quality factors. Based on this complementarity, we propose a framework to integrate local expert monitoring data with satellite-based monitoring data into a National Forest Monitoring System (NFMS) in support of REDD+ Measuring, Reporting and Verifying (MRV) and near real-time forest change monitoring. View Full-Text
Keywords: REDD+; MRV; national forest monitoring system; community-based monitoring; citizen science; remote sensing; accuracy assessment; Kafa; Ethiopia REDD+; MRV; national forest monitoring system; community-based monitoring; citizen science; remote sensing; accuracy assessment; Kafa; Ethiopia
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pratihast, A.K.; DeVries, B.; Avitabile, V.; de Bruin, S.; Kooistra, L.; Tekle, M.; Herold, M. Combining Satellite Data and Community-Based Observations for Forest Monitoring. Forests 2014, 5, 2464-2489.

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