Remote Sens. 2013, 5(9), 4503-4532; doi:10.3390/rs5094503
Article

Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data

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Received: 25 June 2013; in revised form: 29 August 2013 / Accepted: 5 September 2013 / Published: 12 September 2013
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Abstract: A study was undertaken to assess Envisat Advanced Synthetic Aperture Radar (ASAR) ScanSAR data for quantifying forest growing stock volume (GSV) across three boreal regions with varying forest types, composition, and structure (Sweden, Central Siberia, and Québec). Estimates of GSV were obtained using hyper-temporal observations of the radar backscatter acquired by Envisat ASAR with the BIOMASAR algorithm. In total, 5.3×106 km2 were mapped with a 0.01° pixel size to obtain estimates representative for the year of 2005. Comparing the SAR-based estimates to spatially explicit datasets of GSV, generated from forest field inventory and/or Earth Observation data, revealed similar spatial distributions of GSV. Nonetheless, the weak sensitivity of C-band backscatter to forest structural parameters introduced significant uncertainty to the estimated GSV at full resolution. Further discrepancies were observed in the case of different scales of the ASAR and the reference GSV and in areas of fragmented landscapes. Aggregation to 0.1° and 0.5° was then undertaken to generate coarse scale estimates of GSV. The agreement between ASAR and the reference GSV datasets improved; the relative difference at 0.5° was consistently within a magnitude of 20–30%. The results indicate an improvement of the characterization of forest GSV in the boreal zone with respect to currently available information.
Keywords: SAR backscatter; Envisat ASAR; growing stock volume; boreal forest; Sweden; Siberia; Québec; BIOMASAR algorithm
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Santoro, M.; Cartus, O.; Fransson, J.E.; Shvidenko, A.; McCallum, I.; Hall, R.J.; Beaudoin, A.; Beer, C.; Schmullius, C. Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data. Remote Sens. 2013, 5, 4503-4532.

AMA Style

Santoro M, Cartus O, Fransson JE, Shvidenko A, McCallum I, Hall RJ, Beaudoin A, Beer C, Schmullius C. Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data. Remote Sensing. 2013; 5(9):4503-4532.

Chicago/Turabian Style

Santoro, Maurizio; Cartus, Oliver; Fransson, Johan E.; Shvidenko, Anatoly; McCallum, Ian; Hall, Ronald J.; Beaudoin, André; Beer, Christian; Schmullius, Christiane. 2013. "Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data." Remote Sens. 5, no. 9: 4503-4532.


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