/ M. Santoro, O. Cartus, N. Carvalhais [et al.]> // Earth Syst. Sci. Data. - 2021. -
Vol. 13,
Is. 8. - P3927-3950,
DOI 10.5194/essd-13-3927-2021. - Cited References:68. - This research has been supported by the European Space Agency (ESRIN contract no. 4000113100/14/I-NB) and the Russian Science Foundation (grant no. 19-77-30015).
. - ISSN 1866-3508. - ISSN 1866-3516
РУБ Geosciences, Multidisciplinary + Meteorology & Atmospheric Sciences
Аннотация: The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a spatial resolution of 1 ha. Using an extensive database of 110 897 AGB measurements from field inventory plots, we show that the spatial patterns and magnitude of AGB are well captured in our map with the exception of regional uncertainties in high-carbon-stock forests with AGB 250 Mg ha(-1), where the retrieval was effectively based on a single radar observation. With a total global AGB of 522 Pg, our estimate of the terrestrial biomass pool in forests is lower than most estimates published in the literature (426-571 Pg). Nonetheless, our dataset increases knowledge on the spatial distribution of AGB compared to the Global Forest Resources Assessment (FRA) by the Food and Agriculture Organization (FAO) and highlights the impact of a country's national inventory capacity on the accuracy of the biomass statistics reported to the FRA. We also reassessed previous remote sensing AGB maps and identified major biases compared to inventory data, up to 120% of the inventory value in dry tropical forests, in the subtropics and temperate zone. Because of the high level of detail and the overall reliability of the AGB spatial patterns, our global dataset of AGB is likely to have significant impacts on climate, carbon, and socio-economic modelling schemes and provides a crucial baseline in future carbon stock change estimates.
WOS Держатели документа: Gamma Remote Sensing, CH-3073 Gumlingen, Switzerland.
Max Planck Inst Biogeochem, Hans Knoll Str 10, D-07745 Jena, Germany.
Univ Nova Lisboa, Fac Ciencias & Tecnol, Dept Ciencias & Engn Ambiente, FCT,DCEA, P-2829516 Caparica, Portugal.
Wageningen Univ & Res, Lab Geoinformat Sci & Remote Sensing, Droevendaalsesteeg 3, NL-6708 PB Wageningen, Netherlands.
Wageningen Univ & Res, Plant Prod Syst Grp, POB 430, NL-6700 AK Wageningen, Netherlands.
Wageningen Univ & Res, Ctr Crop Syst Anal, POB 430, NL-6700 AK Wageningen, Netherlands.
European Commiss, Joint Res Ctr, Ispra, Italy.
Univ Sheffield, Natl Ctr Earth Observat NCEO, Sheffield S3 7RH, S Yorkshire, England.
Univ Leicester, Ctr Landscape & Climate Res, Sch Geog Geol & Environm, Leicester LE1 7RH, Leics, England.
Natl Ctr Earth Observat NCEO, Leicester LE1 7RH, Leics, England.
Int Inst Appl Syst Anal, Schlosspl 1, A-2361 Laxenburg, Austria.
Russian Acad Sci, Ctr Forest Ecol & Prod, Profsoyuznaya 84-32-14, Moscow 117997, Russia.
Siberian Fed Univ, Inst Ecol & Geog, 79 Svobodny Prospect, Krasnoyarsk 660041, Russia.
Russian Acad Sci, Lab Ecophysiol Permafrost Syst, VN Sukachev Inst Forest, Siberian Branch,Separated Dept KSC SB RAS, Krasnoyarsk 660036, Russia.
Tokyo Denki Univ, Div Architectural Civil & Environm Engn, Sch Sci & Engn, Hiki, Saitama 3500394, Japan.
Remote Sensing Technol Ctr Japan, Minato Ku, Tokyu Reit Toranomon Bldg,3f,3-17-1 Toranomon, Tokyo 1050001, Japan.
Univ Valencia, Image Proc Lab IPL, Valencia, Spain.
Univ Montana, Numer Terradynam Simulat Grp NTSG, Missoula, MT 59812 USA.
Univ Zagreb, Fac Forestry & Wood Technol, Dept Forest Inventory & Management, Zagreb 10000, Croatia.
Tomsk State Univ, Biol Inst, Tomsk 634050, Russia.
Univ Manchester, Sch Environm Educ & Dev, Dept Geog, Oxford Rd, Manchester M13 9PL, Lancs, England.
Guyana Forestry Commiss, 1 Water St, Georgetown, Guyana.
UMR 5174 CNRS IRD UPS, Lab Evolut & Diversit Biol, F-31062 Toulouse 9, France.
Purdue Univ, Dept Forestry & Nat Resources, 715 State St, W Lafayette, IN 47907 USA.
Rocha Int, Cambridge, England.
RSPB Ctr Conservat Sci, Sandy, Beds, England.
Univ Edinburgh, Sch GeoSci, Crew Bldg,Kings Bldg, Edinburgh EH9 3FF, Midlothian, Scotland.
Univ Dundee, Dept Geog & Environm Sci, Dundee, Scotland.
Univ Brunei Darussalam, Fac Sci, Jln Tungku Link, BE-1410 Gadong, Brunei.
Amma Remote Sensing, CH-3073 Gumlingen, Switzerland.
Univ Tuscia, Dept Innovat Biol Agrofood & Forest Syst DIBAF, I-01100 Viterbo, Italy.
Univ Ghent, Dept Environm, CAVElab Computat & Appl Vegetat Ecol, Coupure Links 653, B-9000 Ghent, Belgium.
World Resources Inst Indonesia WRI Indonesia, Dept Res Data & Innovat, Wisma PMI, 3rd Floor,Jl Wijaya I-63, Kebayoran Baru, South Jakarta, Indonesia.
Bangor Univ, Sch Nat Sci, Bangor, Gwynedd, Wales.
Доп.точки доступа: Santoro, Maurizio; Cartus, Oliver; Carvalhais, Nuno; Rozendaal, Danae M. A.; Avitabile, Valerio; Araza, Arnan; de Bruin, Sytze; Herold, Martin; Quegan, Shaun; Rodriguez-Veiga, Pedro; Balzter, Heiko; Carreiras, Joao; Schepaschenko, Dmitry; Korets, Mikhail; Shimada, Masanobu; Itoh, Takuya; Martinez, J.; Cavlovic, Jura; Gatti, Roberto Cazzolla; Bispo, Polyanna da Conceicao; Dewnath, Nasheta; Labriere, Nicolas; Liang, Jingjing; Lindsell, Jeremy; Mitchard, Edward T. A.; Morel, Alexandra; Pascagaza, Ana Maria Pacheco; Ryan, Casey M.; Slik, Ferry; Laurin, Gaia Vaglio; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon; A., Arnan; European Space Agency (ESRIN) [4000113100/14/I-NB]; Russian Science FoundationRussian Science Foundation (RSF) [19-77-30015]