A non-linear Granger-causality framework to investigate climate-vegetation dynamics

被引:97
作者
Papagiannopoulou, Christina [1 ]
Miralles, Diego G. [2 ,3 ]
Decubber, Stijn [1 ]
Demuzere, Matthias [2 ]
Verhoest, Niko E. C. [2 ]
Dorigo, Wouter A. [4 ]
Waegeman, Willem [1 ]
机构
[1] Univ Ghent, Dept Math Modelling Stat & Bioinformat, Ghent, Belgium
[2] Univ Ghent, Lab Hydrol & Water Management, Ghent, Belgium
[3] Vrije Univ Amsterdam, Dept Earth Sci, Amsterdam, Netherlands
[4] Vienna Univ Technol, Dept Geodesy & Geoinformat, Vienna, Austria
基金
欧洲研究理事会;
关键词
GLOBAL TERRESTRIAL ECOSYSTEMS; SOIL-MOISTURE; SURFACE-TEMPERATURE; CARBON-DIOXIDE; RANDOM FORESTS; SAMPLE TESTS; TIME-SERIES; PRECIPITATION; SATELLITE; NDVI;
D O I
10.5194/gmd-10-1945-2017
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Satellite Earth observation has led to the creation of global climate data records of many important environmental and climatic variables. These come in the form of multivariate time series with different spatial and temporal resolutions. Data of this kind provide new means to further unravel the influence of climate on vegetation dynamics. However, as advocated in this article, commonly used statistical methods are often too simplistic to represent complex climate-vegetation relationships due to linearity assumptions. Therefore, as an extension of linear Granger-causality analysis, we present a novel non-linear framework consisting of several components, such as data collection from various databases, time series decomposition techniques, feature construction methods, and predictive modelling by means of random forests. Experimental results on global data sets indicate that, with this framework, it is possible to detect non-linear patterns that are much less visible with traditional Granger-causality methods. In addition, we discuss extensive experimental results that highlight the importance of considering non-linear aspects of climate-vegetation dynamics.
引用
收藏
页码:1945 / 1960
页数:16
相关论文
共 97 条
  • [51] The IGBP-DIS global 1 km land cover data set, DISCover: first results
    Loveland, TR
    Belward, AS
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 1997, 18 (15) : 3291 - 3295
  • [52] Lozano A, 2009, KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, P587
  • [53] Luojus K., 2010, GEOSC REM SENS S IGA
  • [54] Maddala G.S., 1992, INTRO ECONOMETRICS, V2nd
  • [55] Kernel method for nonlinear Granger causality
    Marinazzo, Daniele
    Pellicoro, Mario
    Stramaglia, Sebastiano
    [J]. PHYSICAL REVIEW LETTERS, 2008, 100 (14)
  • [56] GLEAM v3: satellite-based land evaporation and root-zone soil moisture
    Martens, Brecht
    Miralles, Diego G.
    Lievens, Hans
    van der Schalie, Robin
    de Jeu, Richard A. M.
    Fernandez-Prieto, Diego
    Beck, Hylke E.
    Dorigo, Wouter A.
    Verhoest, Niko E. C.
    [J]. GEOSCIENTIFIC MODEL DEVELOPMENT, 2017, 10 (05) : 1903 - 1925
  • [57] The future of Earth observation in hydrology
    McCabe, Matthew F.
    Rodell, Matthew
    Alsdorf, Douglas E.
    Miralles, Diego G.
    Uijlenhoet, Remko
    Wagner, Wolfgang
    Lucieer, Arko
    Houborg, Rasmus
    Verhoest, Niko E. C.
    Franz, Trenton E.
    Shi, Jiancheng
    Gao, Huilin
    Wood, Eric F.
    [J]. HYDROLOGY AND EARTH SYSTEM SCIENCES, 2017, 21 (07) : 3879 - 3914
  • [58] Asymptotics for out of sample tests of Granger causality
    McCracken, Michael W.
    [J]. JOURNAL OF ECONOMETRICS, 2007, 140 (02) : 719 - 752
  • [59] Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet
    McPherson, Renee A.
    Fiebrich, Christopher A.
    Crawford, Kenneth C.
    Elliott, Ronald L.
    Kilby, James R.
    Grimsley, David L.
    Martinez, Janet E.
    Basara, Jeffrey B.
    Illston, Bradley G.
    Morris, Dale A.
    Kloesel, Kevin A.
    Stadler, Stephen J.
    Melvin, Andrea D.
    Sutherland, Albert J.
    Shrivastava, Himanshu
    Carlson, J. D.
    Wolfinbarger, J. Michael
    Bostic, Jared P.
    Demko, David B.
    [J]. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2007, 24 (03) : 301 - 321
  • [60] MICHAELSEN J, 1987, J CLIM APPL METEOROL, V26, P1589, DOI 10.1175/1520-0450(1987)026<1589:CVISCF>2.0.CO