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Open AccessArticle

Estimation of Above-Ground Biomass over Boreal Forests in Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data

1
Department for Earth Observation, Friedrich-Schiller-University Jena, Loebdergraben 32, 07743 Jena, Germany
2
International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Hans-Knoell-Str. 10, 07745 Jena, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(10), 1550; https://doi.org/10.3390/rs10101550
Received: 12 August 2018 / Revised: 17 September 2018 / Accepted: 19 September 2018 / Published: 26 September 2018
The estimation of above-ground biomass (AGB) in boreal forests is of special concern as it constitutes the highest carbon pool in the northern hemisphere. Particularly, monitoring of the forests in the Russian Federation is important as some regions have not been inventoried for many years. This study explores the combination of multi-frequency, multi-polarization, and multi-temporal radar data as one key approach to provide an accurate estimate of forest biomass. The data from L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-Band Synthetic Aperture Radar 2 (PALSAR-2), together with C-band RADARSAT-2 data, were applied for AGB estimation. Backscatter coefficients from L- and C-band radar were used independently and in combination with a non-parametric model to retrieve AGB data for a boreal forest in Siberia (Krasnoyarskiy Kray). AGB estimation was performed using the random forests machine learning algorithm. The results demonstrated that high estimation accuracies can be achieved at a spatial resolution of 0.25 ha. When the L-band data alone were used for the retrieval, a corrected root-mean-square error (RMSEcor) of 29.4 t ha−1 was calculated. A marginal decrease in RMSEcor was observed when only the filtered L-band backscatter data, without ratio and texture, were used (29.1 t ha−1). The inclusion of the C-band data reduced the over and underestimation; the bias was reduced from 5.5 t ha−1 to 4.7 t ha−1; and a RMSEcor of 30.2 t ha−1 was calculated. View Full-Text
Keywords: SAR; boreal forest; above-ground biomass; backscatter; ALOS-2 PALSAR-2; RADARSAT-2 SAR; boreal forest; above-ground biomass; backscatter; ALOS-2 PALSAR-2; RADARSAT-2
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MDPI and ACS Style

Stelmaszczuk-Górska, M.A.; Urbazaev, M.; Schmullius, C.; Thiel, C. Estimation of Above-Ground Biomass over Boreal Forests in Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data. Remote Sens. 2018, 10, 1550. https://doi.org/10.3390/rs10101550

AMA Style

Stelmaszczuk-Górska MA, Urbazaev M, Schmullius C, Thiel C. Estimation of Above-Ground Biomass over Boreal Forests in Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data. Remote Sensing. 2018; 10(10):1550. https://doi.org/10.3390/rs10101550

Chicago/Turabian Style

Stelmaszczuk-Górska, Martyna A.; Urbazaev, Mikhail; Schmullius, Christiane; Thiel, Christian. 2018. "Estimation of Above-Ground Biomass over Boreal Forests in Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data" Remote Sens. 10, no. 10: 1550. https://doi.org/10.3390/rs10101550

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