High Dimensional Kullback-Leibler Divergence for grassland object-oriented classification from high resolution satellite image time series

Maïlys Lopes; Mathieu Fauvel; Stéphane Girard; David Sheeren

Poster communications

High Dimensional Kullback-Leibler Divergence for grassland object-oriented classification from high resolution satellite image time series

Maïlys Lopes ^{1, *} Mathieu Fauvel ^{1, 2} Stéphane Girard ³ David Sheeren ^{1, 2}

* Corresponding author

1 DYNAFOR - Dynamiques Forestières dans l'Espace Rural

2 DYNAFOR - Dynamiques et écologie des paysages agriforestiers

3 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems

Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann

Abstract : The aim of this study is to classify grassland management practices using satellite image time series with high spatial resolution. The study area is located in southern France where 52 parcels with 3 management types were selected. The spectral variability inside the grasslands was taken into account considering that the pixels signal can be modeled by a Gaussian distribution. A parsimonious model is discussed to deal with the high dimension of the data and the small sample size. A high dimensional symmetrized Kullback-Leibler divergence (KLD) is introduced to compute the similarity between each pair of grasslands. The model is positively compared to the conventional KLD to construct a positive definite kernel used in SVM for supervised classification.

Keywords : high dimension grassland management practices classification satellite image time series

Document type :

Poster communications

Domain :

Environmental Sciences / Biodiversity and Ecology

Engineering Sciences [physics] / Signal and Image processing

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https://hal.inrae.fr/hal-02798633
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Submitted on : Friday, June 5, 2020 - 4:17:09 PM
Last modification on : Thursday, May 13, 2021 - 3:46:55 AM

High Dimensional Kullback-Leibler Divergence for grassland object-oriented classification from high resolution satellite image time series

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High Dimensional Kullback-Leibler Divergence for grassland object-oriented classification from high resolution satellite image time series

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