Exploiting Growing Stock Volume Maps for Large Scale Forest Resource Assessment: Cross-Comparisons of ASAR- and PALSAR-Based GSV Estimates with Forest Inventory in Central Siberia

Forests

Christiane Schmullius¹  Christian Hüttich¹  Dmitry Schepaschenko²  Anatoly Shvidenko²  Sergey Bartalev³  Vasily Zharko³  Mikhail Korets⁴ 

[1] Department for Earth Observation, Friedrich-Schiller-University Jena, Löbdergraben 32,07743 Jena, Germany;International Institute for Advanced System Analyses, Laxenburg 2361, Austria;Space Research Institute of the Russian Academy of Sciences, Moscow 117997, Russia;Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Sciences, Krasnoyarsk, 660036, Russia;

关键词: forest inventory;    biomass;    ALOS PALSAR;    ENVISAT ASAR;    land cover fragmentation;    Siberia;    boreal forest management;   

DOI  :  10.3390/f5071753

来源: DOAJ

【 摘 要 】

Growing stock volume is an important biophysical parameter describing the state and dynamics of the Boreal zone. Validation of growing stock volume (GSV) maps based on satellite remote sensing is challenging due to the lack of consistent ground reference data. The monitoring and assessment of the remote Russian forest resources of Siberia can only be done by integrating remote sensing techniques and interdisciplinary collaboration. In this paper, we assess the information content of GSV estimates in Central Siberian forests obtained at 25 m from ALOS-PALSAR and 1 km from ENVISAT-ASAR backscatter data. The estimates have been cross-compared with respect to forest inventory data showing 34% relative RMSE for the ASAR-based GSV retrievals and 39.4% for the PALSAR-based estimates of GSV. Fragmentation analyses using a MODIS-based land cover dataset revealed an increase of retrieval error with increasing fragmentation of the landscape. Cross-comparisons of multiple SAR-based GSV estimates helped to detect inconsistencies in the forest inventory data and can support an update of outdated forest inventory stands.

【 授权许可】

Unknown