Above-ground biomass prediction by Sentinel-1 multitemporal data in central 
Italy with integration of ALOS2 and Sentinel-2 data

Vaglio Laurin, Gaia; Balling, Johannes; Corona, Piermaria; Mattioli, Walter; Papale, Dario; Puletti, Nicola; Rizzo, Maria; Truckenbrodt, John; Urban, Marcel

doi:10.1117/1.JRS.12.016008

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Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data

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http://dx.doi.org/10.1117/1.JRS.12.016008
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Citation

Vaglio Laurin, G., Balling, J., Corona, P., Mattioli, W., Papale, D., Puletti, N., et al. (2018). Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data. Journal of Applied Remote Sensing, 12(1): 016008. doi:10.1117/1.JRS.12.016008.

Cite as: https://hdl.handle.net/21.11116/0000-0000-3AAF-B

Abstract

The objective of this research is to test Sentinel-1 SAR multitemporal data, supported by multispectral and SAR data at other wavelengths, for fine-scale mapping of above-ground
biomass (AGB) at the provincial level in a Mediterranean forested landscape. The regression
results indicate good accuracy of prediction (R2 ¼ 0.7) using integrated sensors when an
upper bound of 400 Mgha−1 is used in modeling. Multitemporal SAR information was relevant,
allowing the selection of optimal Sentinel-1 data, as broadleaf forests showed a different
response in backscatter throughout the year. Similar accuracy in predictions was obtained
when using SAR multifrequency data or joint SAR and optical data. Predictions based on
SAR data were more conservative, and in line with those from an independent sample from
the National Forest Inventory, than those based on joint data types. The potential of S1 data
in predicting AGB can possibly be improved if models are developed per specific groups
(deciduous or evergreen species) or forest types and using a larger range of ground data.
Overall, this research shows the usefulness of Sentinel-1 data to map biomass at very high resolution for local study and at considerable carbon density.