AUTHOR=Bourgeau-Chavez Laura L. , Grelik Sarah L. , Battaglia Michael J. , Leisman Dorthea J. , Chimner Rod A. , Hribljan John A. , Lilleskov Erik A. , Draper Freddie C. , Zutta Brian R. , Hergoualc’h Kristell , Bhomia Rupesh K. , Lähteenoja Outi TITLE=Advances in Amazonian Peatland Discrimination With Multi-Temporal PALSAR Refines Estimates of Peatland Distribution, C Stocks and Deforestation JOURNAL=Frontiers in Earth Science VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2021.676748 DOI=10.3389/feart.2021.676748 ISSN=2296-6463 ABSTRACT=
There is a data gap in our current knowledge of the geospatial distribution, type and extent of C rich peatlands across the globe. The Pastaza Marañón Foreland Basin (PMFB), within the Peruvian Amazon, is known to store large amounts of peat, but the remoteness of the region makes field data collection and mapping the distribution of peatland ecotypes challenging. Here we review methods for developing high accuracy peatland maps for the PMFB using a combination of multi-temporal synthetic aperture radar (SAR) and optical remote sensing in a machine learning classifier. The new map produced has 95% overall accuracy with low errors of commission (1–6%) and errors of omission (0–15%) for individual peatland classes. We attribute this improvement in map accuracy over previous maps of the region to the inclusion of high and low water season SAR images which provides information about seasonal hydrological dynamics. The new multi-date map showed an increase in area of more than 200% for pole forest peatland (6% error) compared to previous maps, which had high errors for that ecotype (20–36%). Likewise, estimates of C stocks were 35% greater than previously reported (3.238 Pg in