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

Remote Sensing

Maurizio Santoro⁴  Oliver Cartus⁵  Johan E.S. Fransson²  Anatoly Shvidenko¹  Ian McCallum¹  Ronald J. Hall³  André Beaudoin⁷  Christian Beer⁶ 

[1]International Institute of Applied Systems Analysis, A-2361 Laxenburg, Austria

[2] E-Mails:

[3]Department of Forest Resource Management, Swedish University of Agricultural Sciences, SE-901 83 Umeå, Sweden

[4] E-Mail:

[5]Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, Edmonton, AB T6H 3S5, Canada

[6] E-Mail:

[7]Gamma Remote Sensing, Worbstrasse 225, 3073 Gümligen, Switzerland

[8] E-Mail:

[9]Woods Hole Research Center, Falmouth, MA 02540, USA

[10] E-Mail:

[11]Department of Applied Environmental Science (ITM) and Bert Bolin Centre for Climate Research, Stockholm University, SE-106 91 Stockholm, Sweden

[12] E-Mail:

[13]Laurentian Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sainte-Foy, QC G1V 4C7, Canada

[14] E-Mail:

关键词: SAR backscatter;    Envisat ASAR;    growing stock volume;    boreal forest;    Sweden;    Siberia;    Québec;    BIOMASAR algorithm;   

DOI  :  10.3390/rs5094503

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland