Using publicly available remote sensing products to evaluate REDD + projects in Brazil

Gabriela Demarchi (), Julie Subervie, Thibault Catry () and Isabelle Tritsch
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Gabriela Demarchi: CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier, CIFOR - Center for International Forestry Research - CGIAR - Consultative Group on International Agricultural Research [CGIAR]
Thibault Catry: UMR 228 Espace-Dev, Espace pour le développement - IRD - Institut de Recherche pour le Développement - UPVD - Université de Perpignan Via Domitia - AU - Avignon Université - UR - Université de La Réunion - UNC - Université de la Nouvelle-Calédonie - UG - Université de Guyane - UA - Université des Antilles - UM - Université de Montpellier
Isabelle Tritsch: UPR Forêts et Sociétés - Forêts et Sociétés - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Cirad-ES - Département Environnements et Sociétés - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement

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Abstract: Ensuring the perpetuity and improvement of REDD initiatives requires rigorous impact evaluation of their effectiveness in curbing deforestation. Today, a number of global and regional remote sensing (RS) products that detect changes in forest cover are publicly available. In this study, we assess the suitability of using these datasets to evaluate the impact of local REDD projects targeting smallholders in the Brazilian Amazonb] Firstly, we reconstruct the forest loss of 21,492 farms located in the Transamazonian region for the period 2008 to 2018, using data from two RS products: Global Forest Change (GFC) and the Amazon Deforestation Monitoring Project (PRODES). Secondly, we evaluate the consistency between these two data sources and find that the deforestation estimates at the farm level vary considerably between datasets. Despite this difference, using microeconometric techniques that use pre-treatment outcomes to construct counter-factual patterns of REDD program participants, we estimate that about two hectares, or about four percent of the forest area, were saved on average on each of the 350 participating farms during the first years of the program, regardless of the data-source used. Moreover, we find that deforestation decreased on plots surrounding participating farms during the very first years of the program, suggesting that the program may have had a positive effect on neighboring farms as well. Finally, we show that participants returned to their business-as-usual pattern of clearing one to three hectares per year at the end of the program. The environmental gain generated by the program, however, was not offset by any catch-up behavior, as the two hectares saved on each farm before 2017 were not cleared in 2018. By calculating the monetary gain of the delayed carbon dioxide emissions, we find that the program's benefits were ultimately greater than its costs.

Date: 2023-05
New Economics Papers: this item is included in nep-agr, nep-big, nep-env and nep-ppm
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-04037153v1
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Published in Global Environmental Change, 2023, 80, pp.102653. ⟨10.1016/j.gloenvcha.2023.102653⟩

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Working Paper: Using publicly available remote sensing products to evaluate REDD+ projects in Brazil (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04037153

DOI: 10.1016/j.gloenvcha.2023.102653

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