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Can the global modeling technique be used for crop classification?

Author

Listed:
  • Mangiarotti, S.
  • Sharma, A.K.
  • Corgne, S.
  • Hubert-Moy, L.
  • Ruiz, L.
  • Sekhar, M.
  • Kerr, Y.

Abstract

Crop detection from remote sensed images is of major interest for land use and land cover mapping. Classification techniques often require multi-temporal images. However, most of these techniques assume that the cultural cycle occurs at the same dates across plots or for a given crop and do not take into account the sensitivity to initial conditions of the dynamical behaviors. Such hypotheses are not well adapted when a wide diversity of practices is observed for the same crops from one crop field to another, which is often the case in tropical context. To cope with these difficulties, a new classification technique based on the global modeling technique is introduced in this paper. It is first applied to a case study based on chaotic oscillators. It is then tested on crop classification observed from satellite data.

Suggested Citation

  • Mangiarotti, S. & Sharma, A.K. & Corgne, S. & Hubert-Moy, L. & Ruiz, L. & Sekhar, M. & Kerr, Y., 2018. "Can the global modeling technique be used for crop classification?," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 363-378.
    • Handle: RePEc:eee:chsofr:v:106:y:2018:i:c:p:363-378
    DOI: 10.1016/j.chaos.2017.12.003
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    References listed on IDEAS

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    1. Mangiarotti, Sylvain & Le Jean, Flavie & Huc, Mireille & Letellier, Christophe, 2016. "Global modeling of aggregated and associated chaotic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 82-96.
    2. Antonio Aguirre & Luis Antonio Aguirre, 2000. "Time series analysis of monthly beef cattle prices with nonlinear autoregressive models," Applied Economics, Taylor & Francis Journals, vol. 32(3), pages 265-275.
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