Long term analysis of time series of satellite images

Thomas Guyet 1, 2 Hervé Nicolas 3, 2
1 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Satellite images allow the acquisition of large-scale ground vegetation. Images are available along several years with a high acquisition rate. Such data are called satellite image time series (SITS). We present a method to analyse an SITS through the characterization of the evolution of a vegetation index (NDVI) at two scales: annual and multi-annual. We evaluate our method on SITS of the Senegal from 2001 to 2008 and we compare our method to a clustering of long time series. The results show that our method better discriminates regions in the median zone of Senegal and locates fine interesting areas.
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Thomas Guyet, Hervé Nicolas. Long term analysis of time series of satellite images. Pattern Recognition Letters, Elsevier, 2015, ⟨10.1016/j.patrec.2015.11.005⟩. ⟨hal-01239504⟩

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