Assessing Technologies to Accelerate the Process of Monitoring, Reporting, and Verifying Emission Reductions Programs
This study explored the use of a state-of-the-art collection of high-quality in situ datasets, following best practices13 to inform biomass estimates derived through remote sensing. The intention was to circumvent (1) the challenge of extrapolating data coverage from plot-level to satellite-level (for example, for the entire ERP area) and (2) the limitations of using allometric equations to estimate biomass from national forest inventories. The ASA also explored a novel method of creating data synergies within a 50,000-hectare (ha) region of interest. It was expected that these processes would improve the accuracy and bias of estimates so they could be extrapolated to the larger ERP area with the support of colleagues from Sylvera
Year of publication: |
2025-02-11
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Authors: | Aguilar-Amuchastegui, Naikoa ; Becerra Leal, Catalina ; Belenky, Lucas Gregory ; Botero, Maria Fernanda Jaramillo ; Burt, Andrew ; Espejo, Andres B. ; Galindo, Gustavo ; Kiesslich, Norman ; Matteson, Ryan ; Michel Fuentes, Jose Maria ; Odorico, Hercilo ; Osterbur, Nicholas ; Peneva-Reed, Ellie ; Perez Lara, Martin ; Sanchez, Natalie ; Soares, Muri ; Turriago, Juan ; Vilca, Beisit Luz Puma |
Publisher: |
Washington, DC : World Bank |
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