Use of multi-sensor, multi-scale and temporal data for segmenting vegetation

Abstract : The study of vegetation repartition and evolution is a wide research field and application task for environmental modeling. The objective of our study is to discriminate different vegetation types by their temporal evolution. For that purpose, we use two different sensors: the SPOT sensor provides monthly data with a sufficient spatial resolution, while the NOAA sensor provides daily data, but with a poor spatial resolution. Combining these two complementary sensors seems to be a promising way to lead the study. We propose here a three-step experiment showing that the simultaneous use of these two sensors allows us to obtain a fine segmentation of land cover.
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Communication dans un congrès
Jacky Desachy. Image and Signal Processing for Remote Sensing III, Sep 1996, Taormina, Italy. 2955, pp.96-105, 1996, Image and Signal Processing for Remote Sensing III. 〈10.1117/12.262878〉
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https://hal.inria.fr/inria-00532694
Contributeur : Brigitte Briot <>
Soumis le : jeudi 4 novembre 2010 - 13:39:10
Dernière modification le : vendredi 25 mai 2018 - 12:02:05

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Jean-Paul Berroir, Sonia Bouzidi, Isabelle Herlin. Use of multi-sensor, multi-scale and temporal data for segmenting vegetation. Jacky Desachy. Image and Signal Processing for Remote Sensing III, Sep 1996, Taormina, Italy. 2955, pp.96-105, 1996, Image and Signal Processing for Remote Sensing III. 〈10.1117/12.262878〉. 〈inria-00532694〉

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