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  Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR

Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J. E., Hall, R. J., et al. (2015). Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sensing of Environment, 168, 316-334. doi:10.1016/j.rse.2015.07.005.

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Santoro, Maurizio, Autor
Beaudoin, André, Autor
Beer, Christian, Autor
Cartus, Oliver, Autor
Fransson, Johan E.S., Autor
Hall, Ronald J., Autor
Pathe, Carsten, Autor
Schmullius, Christiane, Autor
Schepaschenko, Dmitry, Autor
Shvidenko, Anatoly, Autor
Thurner, Martin1, Autor           
Wegmüller, Urs, Autor
Affiliations:
1Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              

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 Zusammenfassung: This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10°N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01° were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest (< 30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV (> 300 m3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%).

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 Datum: 2015-07-0320152015
 Publikationsstatus: Erschienen
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 Identifikatoren: Anderer: BGC2296
DOI: 10.1016/j.rse.2015.07.005
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Titel: Remote Sensing of Environment
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: New York : Elsevier
Seiten: - Band / Heft: 168 Artikelnummer: - Start- / Endseite: 316 - 334 Identifikator: ISSN: 0034-4257
CoNE: https://pure.mpg.de/cone/journals/resource/954925437513