Determining optimal new generation satellite derived metrics for accurate C3 and C4 grass species aboveground biomass estimation in South Africa

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dc.contributor.authorShoko, Cletah
dc.contributor.authorMutanga, Onisimo
dc.contributor.authorDube, Timothy
dc.date.accessioned2019-10-29T14:36:18Z
dc.date.available2019-10-29T14:36:18Z
dc.date.issued2018
dc.description.abstractWhile satellite data has proved to be a powerful tool in estimating C3 and C4 grass species Aboveground Biomass (AGB), finding an appropriate sensor that can accurately characterize the inherent variations remains a challenge. This limitation has hampered the remote sensing community from continuously and precisely monitoring their productivity. This study assessed the potential of a Sentinel 2 MultiSpectral Instrument, Landsat 8 Operational Land Imager, and WorldView-2 sensors, with improved earth imaging characteristics, in estimating C3 and C4 grasses AGB in the Cathedral Peak, South Africa. Overall, all sensors have shown considerable potential in estimating species AGB; with the use of different combinations of the derived spectral bands and vegetation indices producing better accuracies. However,WorldView-2 derived variables yielded better predictive accuracies (R2 ranging between 0.71 and 0.83; RMSEs between 6.92% and 9.84%), followed by Sentinel 2, with R2 between 0.60 and 0.79; and an RMSE 7.66% and 14.66%. Comparatively, Landsat 8 yielded weaker estimates, with R2 ranging between 0.52 and 0.71 and high RMSEs ranging between 9.07% and 19.88%. In addition, spectral bands located within the red edge (e.g., centered at 0.705 and 0.745 m for Sentinel 2), SWIR, and NIR, as well as the derived indices, were found to be very important in predicting C3 and C4 AGB from the three sensors. The competence of these bands, especially of the free-available Landsat 8 and Sentinel 2 dataset, was also confirmed from the fusion of the datasets. Most importantly, the three sensors managed to capture and show the spatial variations in AGB for the target C3 and C4 grassland area. This work therefore provides a new horizon and a fundamental step towards C3 and C4 grass productivity monitoring for carbon accounting, forage mapping, and modelling the influence of environmental changes on their productivity.en_US
dc.identifier.citationShoko, C., Mutanga, O., & Dube, T. (2018). Determining Optimal New Generation Satellite Derived Metrics for Accurate C3 and C4 Grass Species Aboveground Biomass Estimation in South Africa. Remote Sensing, 10(4), 564. MDPI AG. Retrieved from http://dx.doi.org/10.3390/rs10040564en_US
dc.identifier.issn2072-4292
dc.identifier.urihttp://dx.doi.org/10.3390/rs10040564
dc.identifier.urihttp://hdl.handle.net/10566/5079
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectWorldView-2en_US
dc.subjectLandsat 8en_US
dc.subjectSentinel 2en_US
dc.subjectFestuca costataen_US
dc.subjectThemeda triandraen_US
dc.titleDetermining optimal new generation satellite derived metrics for accurate C3 and C4 grass species aboveground biomass estimation in South Africaen_US
dc.typeArticleen_US

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