KangYanZhangEtAl2018

Référence

Kang, X., Yan, L., Zhang, X., Li, Y., Tian, D., Peng, C., Wu, H., Wang, J. and Zhong, L. (2018) Modeling gross primary production of a typical Coastal Wetland in China using MODIS time series and CO2 Eddy Flux Tower Data. Remote Sensing, 10(5). (Scopus )

Résumé

How to effectively combine remote sensing data with the eddy covariance (EC) technique to accurately quantify gross primary production (GPP) in coastal wetlands has been a challenge and is also important and necessary for carbon (C) budgets assessment and climate change studies at larger scales. In this study, a satellite-based Vegetation Photosynthesis Model (VPM) combined with EC measurement and Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to evaluate the phenological characteristics and the biophysical performance of MODIS-based vegetation indices (VIs) and the feasibility of the model for simulating GPP of coastal wetland ecosystems. The results showed that greenness-related and water-related VIs can better identify the green-up and the senescence phases of coastal wetland vegetation, corresponds well with the C uptake period and the phenological patterns that were delineated by GPP from EC tower (GPPEC). Temperature can explain most of the seasonal variation in VIs and GPPEC fluxes. Both enhanced vegetation index (EVI) and water-sensitive land surface water index (LSWI) have a higher predictive power for simulating GPP in this coastal wetland. The comparisons between modeled GPP (GPPVPM) and GPPEC indicated that VPM model can commendably simulate the trajectories of the seasonal dynamics of GPPEC fluxes in terms of patterns and magnitudes, explaining about 85% of GPPEC changes over the study years (p < 0.0001). The results also demonstrate the potential of satellite-driven VPM model for modeling C uptake at large spatial and temporal scales in coastal wetlands, which can provide valuable production data for the assessment of global wetland C sink/source. © 2018 by the authors.

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@ARTICLE { KangYanZhangEtAl2018,
    AUTHOR = { Kang, X. and Yan, L. and Zhang, X. and Li, Y. and Tian, D. and Peng, C. and Wu, H. and Wang, J. and Zhong, L. },
    TITLE = { Modeling gross primary production of a typical Coastal Wetland in China using MODIS time series and CO2 Eddy Flux Tower Data },
    JOURNAL = { Remote Sensing },
    YEAR = { 2018 },
    VOLUME = { 10 },
    NUMBER = { 5 },
    NOTE = { cited By 0 },
    ABSTRACT = { How to effectively combine remote sensing data with the eddy covariance (EC) technique to accurately quantify gross primary production (GPP) in coastal wetlands has been a challenge and is also important and necessary for carbon (C) budgets assessment and climate change studies at larger scales. In this study, a satellite-based Vegetation Photosynthesis Model (VPM) combined with EC measurement and Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to evaluate the phenological characteristics and the biophysical performance of MODIS-based vegetation indices (VIs) and the feasibility of the model for simulating GPP of coastal wetland ecosystems. The results showed that greenness-related and water-related VIs can better identify the green-up and the senescence phases of coastal wetland vegetation, corresponds well with the C uptake period and the phenological patterns that were delineated by GPP from EC tower (GPPEC). Temperature can explain most of the seasonal variation in VIs and GPPEC fluxes. Both enhanced vegetation index (EVI) and water-sensitive land surface water index (LSWI) have a higher predictive power for simulating GPP in this coastal wetland. The comparisons between modeled GPP (GPPVPM) and GPPEC indicated that VPM model can commendably simulate the trajectories of the seasonal dynamics of GPPEC fluxes in terms of patterns and magnitudes, explaining about 85% of GPPEC changes over the study years (p < 0.0001). The results also demonstrate the potential of satellite-driven VPM model for modeling C uptake at large spatial and temporal scales in coastal wetlands, which can provide valuable production data for the assessment of global wetland C sink/source. © 2018 by the authors. },
    AFFILIATION = { Beijing Key Laboratory ofWetland Services and Restoration, Institute ofWetland Research, Chinese Academy of Forestry, Beijing, China; Sichuan Zoige Wetland Ecosystem Research Station, Tibetan Autonomous Prefecture of Aba, China; Department of Biology Science, Institute of Environment Sciences, University of Quebec at Montreal, Montreal, QC, Canada; Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; Center for Ecological Forecasting and Global Change, College of Forestry, Northwest Agriculture and Forest University, Yangling, China; School of Environmental Science and Engineering, Tianjin University, China-Australia Centre for Sustainable Urban Development, Tianjin, China },
    ART_NUMBER = { 708 },
    AUTHOR_KEYWORDS = { Coastal wetland; Eddy covariance; Gross primary production; MODIS; Vegetation indices; VPM },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.3390/rs10050708 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047546395&doi=10.3390%2frs10050708&partnerID=40&md5=bfffcbfa3ae1ea6081bb65de06a28076 },
}

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