Monitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD+

dc.contributor.authorSolberg, Svein
dc.contributor.authorGizachew, Belachew
dc.contributor.authorNæsset, Erik
dc.contributor.authorGobakken, Terje
dc.contributor.authorBollandsås, Ole Martin
dc.contributor.authorMauya, Ernest William
dc.contributor.authorOlsson, Håkan
dc.contributor.authorMalimbwi, Rogers
dc.contributor.authorZahabu, Eliakimu
dc.date.accessioned2017-01-19T12:36:51Z
dc.date.available2017-01-19T12:36:51Z
dc.date.issued2015
dc.description© 2015 Solberg et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.en_US
dc.description.abstractBackground: REDD+ implementation requires establishment of a system for measuring, reporting and verification (MRV) of forest carbon changes. A challenge for MRV is the lack of satellite based methods that can track not only deforestation, but also degradation and forest growth, as well as a lack of historical data that can serve as a basis for a reference emission level. Working in a miombo woodland in Tanzania, we here aim at demonstrating a novel 3D satellite approach based on interferometric processing of radar imagery (InSAR). Results: Forest carbon changes are derived from changes in the forest canopy height obtained from InSAR, i.e. decreases represent carbon loss from logging and increases represent carbon sequestration through forest growth. We fitted a model of above-ground biomass (AGB) against InSAR height, and used this to convert height changes to biomass and carbon changes. The relationship between AGB and InSAR height was weak, as the individual plots were widely scattered around the model fit. However, we consider the approach to be unique and feasible for large-scale MRV efforts in REDD+ because the low accuracy was attributable partly to small plots and other limitations in the data set, and partly to a random pixel-to-pixel variation in trunk forms. Further processing of the InSAR data provides data on the categories of forest change. The combination of InSAR data from the Shuttle RADAR Topography Mission (SRTM) and the TanDEM-X satellite mission provided both historic baseline of change for the period 2000–2011, as well as annual change 2011–2012. Conclusions: A 3D data set from InSAR is a promising tool for MRV in REDD+. The temporal changes seen by InSAR data corresponded well with, but largely supplemented, the changes derived from Landsat data.en_US
dc.identifier.urihttps://www.suaire.sua.ac.tz/handle/123456789/1176
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectForest monitoringen_US
dc.subjectBiomassen_US
dc.subjectCarbonen_US
dc.subjectInSARen_US
dc.titleMonitoring forest carbon in a Tanzanian woodland using interferometric SAR: a novel methodology for REDD+en_US
dc.typeArticleen_US
dc.urlhttp://download.springer.comen_US

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