Asosiy kontentga oʻtish
AkademIndex

Mahsulotlar

Ishlab chiquvchilar uchun

AkademBaseEkotizim uchun ochiq API
Maqola

The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations

Maurizio SantoroGamma Remote Sensing, 3073 Gümligen, SwitzerlandOliver CartusGamma Remote Sensing, 3073 Gümligen, SwitzerlandNuno CarvalhaisDepartamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, PortugalDanaë M. A. RozendaalCentre for Crop Systems Analysis, Wageningen University and Research, P.O. Box 430, 6700 AK Wageningen, the NetherlandsValerio AvitabileJoint Research Centre, European Commission, Ispra, ItalyArnan ArazaLaboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Droevendaalsesteeg 3, 6708 PB Wageningen, the NetherlandsSytze de BruinLaboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Droevendaalsesteeg 3, 6708 PB Wageningen, the NetherlandsMartin HeroldLaboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Droevendaalsesteeg 3, 6708 PB Wageningen, the NetherlandsS. QueganNational Centre for Earth Observation (NCEO), University of Sheffield, Sheffield, S3 7RH, UKPedro Rodríguez‐VeigaCentre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, LE1 7RH, UKHeiko BalzterCentre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, LE1 7RH, UKJoão M. B. CarreirasNational Centre for Earth Observation (NCEO), University of Sheffield, Sheffield, S3 7RH, UKDmitry SchepaschenkoCenter of Forest Ecology and Productivity, Russian Academy of Sciences, Profsoyuznaya 84/32/14, 117997 Moscow, RussiaMikhail KoretsLaboratory of Ecophysiology of Permafrost Systems, V.N. Sukachev Institute of Forest of the Siberian Branch of the Russian Academy of Sciences – separated department of the KSC SB RAS, 660036 Krasnoyarsk, RussiaMasanobu ShimadaTokyo Denki University, School of Science and Engineering, Division of Architectural, Civil and Environmental Engineering, Ishizaka, Hatoyama, Hiki, Saitama, 350-0394, JapanTakuya ItohRemote Sensing Technology Center of Japan, Tokyu Reit Toranomon Bldg, 3f, 3-17-1 Toranomon, Minato-Ku, Tokyo, 105-0001, JapanÁlvaro Moreno‐MartínezNumerical Terradynamic Simulation Group (NTSG), University of Montana, Missoula, MT, USAJura ČavlovićDepartment of Forest Inventory and Management, Faculty of Forestry and Wood Technology, University of Zagreb, Svetosimunska cesta 23, 10000 Zagreb, CroatiaRoberto Cazzolla GattiBiological Institute, Tomsk State University, 634050 Tomsk, RussiaPolyanna da Conceição BispoDepartment of Geography, School of Environment, Education and Development, University of Manchester, Oxford Road, M13 9PL Manchester, UKNasheta DewnathGuyana Forestry Commission, 1 Water Street, Kingston, Georgetown, GuyanaNicolas LabrièreLaboratoire Évolution et Diversité Biologique, UMR 5174 (CNRS/IRD/UPS), 31062 Toulouse CEDEX 9, FranceJingjing LiangDepartment of Forestry and Natural Resources, Purdue University, 715 W State St, West Lafayette, IN 47907, USAJeremy LindsellA Rocha International, Cambridge, UKEdward T. A. MitchardSchool of GeoSciences, University of Edinburgh, Crew Building, The King's Buildings, Edinburgh, EH9 3FF, UKA. MorelDepartment of Geography and Environmental Sciences, University of Dundee, Dundee, UKAna Maria Pacheco PascagazaCentre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, LE1 7RH, UKCasey M. RyanSchool of GeoSciences, University of Edinburgh, Crew Building, The King's Buildings, Edinburgh, EH9 3FF, UKFerry SlikFaculty of Science, University Brunei Darussalam, Jln Tungku Link, Gadong, BE1410, Brunei Darussalam amma Remote Sensing, 3073 Gümligen, SwitzerlandGaia Vaglio LaurinDepartment for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, 01100 Viterbo, ItalyHans VerbeeckCAVElab – Computational and Applied Vegetation Ecology, Department of Environment, Ghent University, Coupure Links 653, 9000 Gent, BelgiumArief WijayaSimon WillcockSchool of Natural Sciences, Bangor University, Bangor, Gwynedd, UK
2021en
ABI

Annotatsiya

Abstract. 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. The dataset is available at https://doi.org/10.1594/PANGAEA.894711 (Santoro, 2018).

Hali tarjima qilinmagan

Identifikatorlar

Iqtiboslar va manbalar

2 ta iqtibos0 ta foydalanilgan manba