Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data

REMOTE SENSING OF ENVIRONMENT

卷:252

Article

Aguirre-Gutierrez, Jesus^1,2  Rifal, Sami¹  Shenkin, Alexander¹  Oliveras, Imma¹  Bentley, Lisa Patrick³  Svatek, Martin⁴  Girardin, Cecile A. J.¹  Both, Sabine⁵  Riutta, Terhi^1,27  Berenguer, Erika¹  Kissling, W. Daniel^1,6  Bauman, David⁷  Raab, Nicolas¹  Moore, Sam¹  Farfan-Rios, William^8,9,10  Simoes Figueiredo, Axa Emanuelle¹¹  Reis, Simone Matias^1,12  Ndong, Josue Edzang¹³  Ondo, Fidele Evouna¹³  Bengone, Natacha N'ssi¹⁴  Mihindou, Vianet¹⁴  Moraes de Seixas, Marina Maria¹⁵  Adu-Bredu, Stephen¹⁶  Abemethy, Katharine^17,18  Asner, Gregory P.¹⁹  Barlow, Jos^20,21  Burstem, David F. R. P.²²  Coomes, David A.²³  Cernusak, Lucas A.²⁴  Dargle, Greta C.²⁵  Enquist, Brian J.²⁶  Ewers, Robert M.²⁷  Ferreira, Joice²¹  Jeffery, Kathryn J.¹⁸  Joly, Carlos A.^28,30  Lewis, Simon L.^25,29  Marimon-Junior, Ben Hur⁹  Martin, Roberta E.¹⁹  Morandi, Paulo S.¹²  Phillips, Oliver L.²⁵  Quesada, Carlos A.³⁰  Salinas, Norma³¹  Marimon, Beatriz Schwantes⁹  Silman, Miles³²  Teh, Yit Arn³³  White, Lee J. T.¹⁸  Malhi, Yadvinder¹ 

[1] Univ Oxford, Environm Change Inst, Sch Geog & Environm, Oxford, England

[2] Naturalis Biodivers Ctr, Biodivers Dynam, 1801 East Cotati Ave, Leiden, Netherlands

[3] Sonoma State Univ, Dept Biol, 1801 East Cotati Ave, Rohnert Pk, CA 94928 USA

[4] Mendel Univ Brno, Fac Forestry & Wood Technol, Dept Forest Bot Dendrol & Geobiocoenol, Brno, Czech Republic

[5] Univ New England, Environm & Rural Sci, Armidale, NSW 2351, Australia

[6] Univ Amsterdam, Inst Biodivers & Ecosyst Dynam IBED, Amsterdam, Netherlands

[7] Univ Libre Bruxelles, Lab Ecol Vegetale & Biogeochim, CP 244, Brussels, Belgium

[8] Washington Univ St Louis, Living Earth Collaborat, St Louis, MO USA

[9] Missouri Bot Garden, Ctr Conservat & Sustainable Dev, St Louis, MO USA

[10] Univ Nacl San Antonio Abad Cusco, Herbario Vargas CUZ, Escuela Profes Biol, Cuzco, Peru

[11] Natl Inst Amazonian Res INPA, CP 2223, BR-69080971 Manaus, Amazonas, Brazil

[12] Univ Estado Mato Grosso, Lab Ecol Vegetal LABEV, Nova Xavantina, Brazil

[13] Agence Natl Parcs Nationaux, BP20379, Libreville, Gabon

[14] Minist Eaux Forets Mer & Environm, Libreville, Gabon

[15] Embrapa Amazonia Oriental, Trav Dr Eneas Pinheiro, BR-66095100 Belem, PA, Brazil

[16] CSIR Forestry Res Inst Ghana, POB 63, Kumasi, Ghana

[17] Inst Rech Ecol Trop, Libreville, Gabon

[18] Univ Stirling, Biol & Environm Sci, Stirling, Scotland

[19] Arizona State Univ, Ctr Global Discovery & Conservat Sci, Tempe, AZ USA

[20] Univ Lancaster, Lancaster Environm Ctr, Lancaster LA1 4YQ, England

[21] MCT Museu Paraense Emilio Goeldi, Magalhaes Barata 376, BR-66040170 Belem, PA, Brazil

[22] Univ Aberdeen, Sch Biol Sci, Aberdeen, Scotland

[23] Univ Cambridge, Conservat Res Inst, Dept Plant Sci, Cambridge CB2 3QZ, England

[24] James Cook Univ, Coll Sci & Engn, Cairns, Qld 4878, Australia

[25] Univ Leeds, Sch Geog Ecol & Global Change, Leeds, W Yorkshire, England

[26] Univ Arizona, Dept Ecol & Evolutionary Biol, Tucson, AZ USA

[27] Imperial Coll London, Dept Life Sci, Ascot, Berks, England

[28] Univ Estadual Campinas, Inst Biol, Dept Biol Vegetal, Campinas, Brazil

[29] UCL, Dept Geog, London, England

[30] Inst Nacl de Pesquisas da Amazonia, Coordenacao Dinam Ambiental, Manaus, Amazonas, Brazil

[31] Pontificia Univ Catol Peru, Ave Univ 1801, Lima 32, Peru

[32] Wake Forest Univ, Dept Biol, Winston Salem, NC 27109 USA

[33] Newcastle Univ, Sch Nat & Environm Sci, Newcastle Upon Tyne, Tyne & Wear, England

关键词: Plant traits;    Sentinel-2;    Tropical forests;    Random Forest;    Pixel-level predictions;    Image texture;   

DOI  :  10.1016/j.rse.2020.112122

来源: Elsevier

【 摘 要 】

Tropical forest ecosystems are undergoing rapid transformation as a result of changing environmental conditions and direct human impacts. However, we cannot adequately understand, monitor or simulate tropical ecosystem responses to environmental changes without capturing the high diversity of plant functional characteristics in the species-rich tropics. Failure to do so can oversimplify our understanding of ecosystems responses to environmental disturbances. Innovative methods and data products are needed to track changes in functional trait composition in tropical forest ecosystems through time and space. This study aimed to track key functional traits by coupling Sentinel-2 derived variables with a unique data set of precisely located in-situ measurements of canopy functional traits collected from 2434 individual trees across the tropics using a standardised methodology. The functional traits and vegetation censuses were collected from 47 field plots in the countries of Australia, Brazil, Peru, Gabon, Ghana, and Malaysia, which span the four tropical continents. The spatial positions of individual trees above 10 cm diameter at breast height (DBH) were mapped and their canopy size and shape recorded. Using geo-located tree canopy size and shape data, community-level trait values were estimated at the same spatial resolution as Sentinel-2 imagery (i.e. 10 m pixels). We then used the Geographic Random Forest (GRF) to model and predict functional traits across our plots. We demonstrate that key plant functional traits can be accurately predicted across the tropicsusing the high spatial and spectral resolution of Sentinel-2 imagery in conjunction with climatic and soil information. Image textural parameters were found to be key components of remote sensing information for predicting functional traits across tropical forests and woody savannas. Leaf thickness ((R)2 = 0.52) obtained the highest prediction accuracy among the morphological and structural traits and leaf carbon content (R-2 = 0.70) and maximum rates of photosynthesis (R-2 = 0.67) obtained the highest prediction accuracy for leaf chemistry and photosynthesis related traits, respectively. Overall, the highest prediction accuracy was obtained for leaf chemistry and photosynthetic traits in comparison to morphological and structural traits. Our approach offers new opportunities for mapping, monitoring and understanding biodiversity and ecosystem change in the most species-rich ecosystems on Earth.

【 授权许可】

Free