Combining Satellite Data and Community-Based Observations for Forest Monitoring

Forests

Arun Kumar Pratihast²  Ben DeVries²  Valerio Avitabile²  Sytze de Bruin²  Lammert Kooistra²  Mesfin Tekle³  Martin Herold²  Arturo Balderas Torres¹ 

[1] Laboratory of Geo-information Science and Remote Sensing, Wageningen University, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands;;Laboratory of Geo-information Science and Remote Sensing, Wageningen University, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands; E-Mails:;The Nature and Biodiversity Conservation Union (NABU), Bonga, Southern Nations Nationalities and People’s Region (SNNPR), Ethiopia; E-Mail:

关键词: REDD+;    MRV;    national forest monitoring system;    community-based monitoring;    citizen science;    remote sensing;    accuracy assessment;    Kafa;    Ethiopia;   

DOI  :  10.3390/f5102464

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.