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Perspective

The Importance of High–Quality Data for REDD+ Monitoring and Reporting

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Forestry Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, 00153 Rome, Italy
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Technical Unit Specialized in Monitoring Reporting and Verification, National Forestry Commission of Mexico, Periférico Poniente #5360 Col. San Juan de Ocotán Zapopan, Jalisco 45019, Mexico
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Department of Geospatial Information Services, Ministry of Environment, Morodok Techo Building No. 503, Tonlebassac, Phnom Penh 12301, Cambodia
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Independent Expert, Leadville, CO 80461, USA
*
Author to whom correspondence should be addressed.
The views expressed in this publication are those of the author(s) and do not necessarily reflect the views or policies of FAO.
Forests 2021, 12(1), 99; https://doi.org/10.3390/f12010099
Received: 9 December 2020 / Revised: 5 January 2021 / Accepted: 8 January 2021 / Published: 18 January 2021
(This article belongs to the Special Issue REDD+: Protecting Climate, Forests and Livelihoods)
This article discusses the importance of quality deforestation area estimates for reliable and credible REDD+ monitoring and reporting. It discusses how countries can make use of global spatial tree cover change assessments, but how considerable additional efforts are required to translate these into national deforestation estimates. The article illustrates the relevance of countries’ continued efforts on improving data quality for REDD+ monitoring by looking at Mexico, Cambodia, and Ghana. The experience in these countries show differences between deforestation areas assessed directly from maps and improved sample-based deforestation area estimates, highlighting significant changes in both magnitude and trend of assessed deforestation from both methods. Forests play an important role in achieving the goals of the Paris Agreement, and therefore the ability of countries to accurately measure greenhouse gases from forests is critical. Continued efforts by countries are needed to produce credible and reliable data. Supporting countries to continually increase the quality of deforestation area estimates will also support more efficient allocation of finance that rewards REDD+ results-based payments. View Full-Text
Keywords: forest monitoring; uncertainty; REDD+; reference levels; data quality; Cambodia; Ghana; Mexico forest monitoring; uncertainty; REDD+; reference levels; data quality; Cambodia; Ghana; Mexico
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MDPI and ACS Style

Sandker, M.; Carrillo, O.; Leng, C.; Lee, D.; d’Annunzio, R.; Fox, J. The Importance of High–Quality Data for REDD+ Monitoring and Reporting. Forests 2021, 12, 99. https://doi.org/10.3390/f12010099

AMA Style

Sandker M, Carrillo O, Leng C, Lee D, d’Annunzio R, Fox J. The Importance of High–Quality Data for REDD+ Monitoring and Reporting. Forests. 2021; 12(1):99. https://doi.org/10.3390/f12010099

Chicago/Turabian Style

Sandker, Marieke, Oswaldo Carrillo, Chivin Leng, Donna Lee, Rémi d’Annunzio, and Julian Fox. 2021. "The Importance of High–Quality Data for REDD+ Monitoring and Reporting" Forests 12, no. 1: 99. https://doi.org/10.3390/f12010099

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