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The population for assessing biomass estimates (left) and an example of the sampling units, 4×4 map pixels enclosing the NFI field plots (right). (Málaga et al. 2022)

Using a global biomass map to assess the precision of Above Ground Biomass (AGB) estimates within the Peruvian Amazonia

Author: Natalia Málaga

Country case studies linking the information from a national network of forest inventories and satellite data are needed to gain experience and build confidence on how forest-related greenhouse gas (GHG) monitoring and reporting can benefit from evolving space-based biomass products. Given the limited coverage and periodicity of National Forest Inventories (NFIs) in tropical countries, it is timely to explore whether global biomass maps can improve sample-based inventory estimates.

In the Forest Carbon Monitoring project, we had the opportunity to investigate this topic in Peru with our user partner the Peruvian National Forest and Wildlife Service (SERFOR). SERFOR is responsible for the country’s national forest inventory system and the forest-related emission factor information that supports the national REDD+ MRV and GHG accountability system. Peru started implementing their National Forest & Wildlife Inventory (NF&WI) in 2013, and by 2020 it had completed approximately 32% of the target sample. Peru relies on this probabilistic sample of plots to estimate national forest-related emission factors.

The objective of the study was to assess whether the 2017 CCI Biomass map, used as auxiliary data, could produce a gain in precision to the country field-based forest AGB estimates within the Peruvian Amazonia. Model-assisted estimators were used with data from the country’s NFI and we also explored hybrid inferential techniques to account for the sources of uncertainty associated with the integration of remote sensing-based products and NFI plot data. The analysis has been fully reported in a recently published paper entitled ‘Precision of subnational forest AGB estimates within the Peruvian Amazonia using a global biomass map’.

The study found that without calibrating the map to correct for the systematic map error, the CCI Biomass map tended to overestimate forest-related AGB values across Peruvian Amazonia. After calibration, the map slightly increased the precision of the AGB estimates, which was constrained by the small map-plot correlations. However, when propagating the sources of uncertainty, the map no longer contributed much to increasing the precision. Further improvement of space-based biomass products should enhance their usefulness for enhancing (sub)national AGB estimates.

Overall, the results of the study can support SERFOR to develop a more comprehensive and sustainable biomass monitoring system resulting from the integration of space-based and in-situ plot data.


Full citation: Málaga N, de Bruin S, McRoberts RE, Arana Olivos A, de la Cruz Paiva R, Durán Montesinos P, Requena Suarez D, Herold M. 2022. Precision of subnational forest AGB estimates within the Peruvian Amazonia using a global biomass map. Int J Appl Earth Obs Geoinformation 115:103102. doi: 10.1016/j.jag.2022.103102