12 research outputs found

    Monitoring the Water Bodies of the Mackenzie Delta by Remote Sensing Methods

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    In the Mackenzie Delta, Northwest Territories, the thousands of lakes, ponds, channels and waterways, connected in an apparently chaotic manner, present a major logistical problem for collecting information regarding the nature of this complex hydrologic system. The use of satellite images gives an economical and synoptic view of this isolated region, while special analysis techniques simplify the environmental appraisal. The use of (mathematical) morphological analysis of the surface waters imaged by the satellite allowed the authors to distinguish all water bodies, even when they were at the limit of the spatial resolution of the sensor. The technique further permitted the classification of these water bodies by their inter- and intra-connectivity. Another technique, termed chromaticity analysis, allows for the removal of atmospheric differences among images, which in turn enables the use of surface calibration data from one date to be used on images of other dates. This method was also used to generate quantitative maps of suspended sediment concentration levels. Together, these techniques permit the assessment of the hydrologic flow (or its hindrance) of sediment and nutrients for the sustenance of aquatic flora and fauna. They further supply a method for the mapping of access routes by water craft to all parts of the Delta.Key words: mathematical morphology, chromaticity analysis, remote sensing, Landsat, Mackenzie Delta, suspensdeeddi ment, hydrologic networkMots clés: morphologie mathématique, analyse par chromaticité, télédétection, Landsat, Delta du Mackenzie, sediments en suspension, réseau hydrologiqu

    Multispectral remotely sensed images interpretation using fuzzy neural networks

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    International audienceMultispectral remotely sensed images interpretation using fuzzy neural network

    An information fusion method for mutispectral image classification postprocessing

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    An automatic road extraction method using a map-guided approachcombined with neural networks for cartographic database validation purposes

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    International audienceA method is proposed to extract road intersections from a SPOT panchromatic image, using a map-guided approach combined with the application of a neural network. The results show an average increase of 36% of planimetric accuracy after applying the method instead of simply superimposing the roads on the geocoded image. Also, only 8 out 42 samples were previously correctly traced, compared to 27 after application of the algorithm

    Segmentation of airborne hyperspectral images by integrating multi-level data fusion

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    International audienceThis paper deals with the extraction of the hedgerow and copse network from hyperspectral images acquired with the Compact Airborne Spectrographic Imager (CASI). The strategy of segmentation integrates several levels of data fusion allowing a decision to be taken concerning the membership of each pixel to the hedgerow and copse network from the large set of original data. The first level leads to quantifying the membership of each pixel to specific features of the network. It includes data fusion based on physical properties, geometric context-dependent fuzzy fusion with an original consistency measure and the geometric fusion of decisions. The second level is a fuzzy fusion of methods allowing the membership of each pixel to the network to be quantified. Finally, the third level involves post-processing the data with a context-dependent fusion of decisions to obtain the final map of the hedgerow and copse network
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