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@inproceedings{bb208001,
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@inproceedings{bb208002,
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@inproceedings{bb208003,
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@inproceedings{bb208004,
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@inproceedings{bb208005,
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@inproceedings{bb208006,
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generalized gamma distribution",
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@inproceedings{bb208007,
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For Land Cover Classification Using Integration of SAR and Optical
Satellite Imagery",
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@inproceedings{bb208008,
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an Object-Based Approach",
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@inproceedings{bb208009,
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@inproceedings{bb208010,
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@inproceedings{bb208011,
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@inproceedings{bb208012,
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land cover classes using both optical and SAR data",
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@article{bb208013,
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        TITLE = "Change detection for thematic mapping by means of airborne
multitemporal polarimetric SAR imagery",
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        TITLE = "Nonparametric Change Detection in Multitemporal SAR Images Based on
Mean-Shift Clustering",
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analysis of SAR and PolSAR image time series",
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@inproceedings{bb208016,
        AUTHOR = "Le, T.T. and Atto, A.M. and Trouve, E.",
        TITLE = "Change analysis of dual polarimetric Sentinel-1 SAR image time series
using stationary wavelet transform and change detection matrix",
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        YEAR = "2015",
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@article{bb208017,
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using polarimetric SAR images",
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@article{bb208018,
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        TITLE = "An Integrated Surface Parameter Inversion Scheme Over Agricultural
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RADARSAT-2 Imagery",
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Classification and Change Detection in Dynamic Tropical Landscapes",
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@article{bb208021,
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@inproceedings{bb208022,
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@inproceedings{bb208023,
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        AUTHOR = "Zhu, Q. and Zhong, Y.F. and Zhang, L.P.",
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@article{bb208039,
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Resolution Image Scene Classification",
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@article{bb208040,
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        TITLE = "Dirichlet-Derived Multiple Topic Scene Classification Model for High
Spatial Resolution Remote Sensing Imagery",
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@article{bb208043,
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Topic Model for High Spatial Resolution Remote Sensing Imagery",
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@article{bb208044,
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        TITLE = "Multi-class geospatial object detection based on a position-sensitive
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@article{bb208049,
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@article{bb208053,
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@article{bb208054,
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@article{bb208055,
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@article{bb208057,
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@article{bb208058,
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@article{bb208059,
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@article{bb208060,
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EO-1 Data",
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@article{bb208061,
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Comparing the Getis and Geary Indices",
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@article{bb208062,
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@article{bb208063,
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Comparing Cubist, Random Forests, and Support Vector Regression",
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@article{bb208064,
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structures acquired by mathematical morphology",
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@article{bb208065,
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Mapping from a Gazetteer",
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@article{bb208066,
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the Mega-Urban Area of the Pearl River Delta (China)",
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@article{bb208067,
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High-Resolution Remotely Sensed Datasets Using Classification Trees and
Test Field Points",
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@article{bb208068,
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Public Domain Remotely Sensed Data",
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@article{bb208069,
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        TITLE = "Machine Learning Comparison between WorldView-2 and
QuickBird-2-Simulated Imagery Regarding Object-Based Urban Land Cover
Classification",
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@article{bb208070,
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Land Cover in the Context of Urban Mosquito Habitat",
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@article{bb208071,
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@article{bb208072,
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@article{bb208073,
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Points Ancillary Data",
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@article{bb208074,
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SAR Images in Urban Areas",
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@inproceedings{bb208075,
        AUTHOR = "Soheili Majd, M. and Simonetto, E. and Polidori, L.",
        TITLE = "Maximum Likelihood Classification of High-Resolution Polarimetric SAR
Images in Urban Area",
        BOOKTITLE = HighRes11,
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        BIBSOURCE = "http://www.visionbib.com/bibliography/cartog927.html#TT203260"}

@article{bb208076,
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Heat Islands and Land Cover",
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Multispectral Data for Urban Land-Cover Mapping",
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super-object information",
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Using Multidimensional Fractal Dimension Indices",
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of land cover in urban neighbourhoods using WorldView-2 imagery",
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@article{bb208085,
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Urban Land Classification with Landsat Thematic Mapper Imagery",
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A SOM approach to Italian industrial districts",
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@article{bb208088,
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remotely sensed images over urban areas",
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@article{bb208089,
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Pattern Recognition from Multi-spectral Satellite Images",
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@article{bb208090,
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Integrating Visual Interpretation and Object-Based Classification",
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@article{bb208091,
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@article{bb208092,
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@article{bb208093,
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@article{bb208094,
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@article{bb208096,
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to Mitigate Urban Microclimatic Variability within H-Res Thermal
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@article{bb208097,
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@article{bb208098,
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Classification in an Urban Environment",
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@article{bb208099,
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Last update:Feb 7, 2020 at 17:28:46