A New European Settlement Map from Optical Remotely Sensed Data. Florczyk, A. J., Ferri, S., Syrris, V., Kemper, T., Halkia, M., Soille, P., & Pesaresi, M. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(5):1978–1992, May, 2016.
doi  abstract   bibtex   
An application of a general methodology for processing very high-resolution imagery to produce a European Settlement Map (ESM) in support of policy-makers is presented. The process mapped around 10 million km2 of the European continent. The input image data are satellite SPOT-5/6 pan-sharpened multispectral images of 2.5- and 1.5-m spatial resolution, respectively. This is the first time that remote sensing technology demonstrates capability to produce a continental information layer using 2.5-m input images. Moreover, it is the highest resolution continental map produced so far. The presented workflow is data-driven and consists in fully automatic image information extraction based on textural and morphological image analysis. The learning method allows the processing of high-resolution image data using coarse resolution thematic layers as reference. Validation shows an overall accuracy of 96\,% with omission and commission errors less than 4\,% and 1\,%, respectively.
@article{florczykNewEuropeanSettlement2016,
  title = {A New {{European}} Settlement Map from Optical Remotely Sensed Data},
  author = {Florczyk, Aneta J. and Ferri, Stefano and Syrris, Vasileios and Kemper, Thomas and Halkia, Matina and Soille, Pierre and Pesaresi, Martino},
  year = {2016},
  month = may,
  volume = {9},
  pages = {1978--1992},
  issn = {1939-1404},
  doi = {10.1109/jstars.2015.2485662},
  abstract = {An application of a general methodology for processing very high-resolution imagery to produce a European Settlement Map (ESM) in support of policy-makers is presented. The process mapped around 10 million km2 of the European continent. The input image data are satellite SPOT-5/6 pan-sharpened multispectral images of 2.5- and 1.5-m spatial resolution, respectively. This is the first time that remote sensing technology demonstrates capability to produce a continental information layer using 2.5-m input images. Moreover, it is the highest resolution continental map produced so far. The presented workflow is data-driven and consists in fully automatic image information extraction based on textural and morphological image analysis. The learning method allows the processing of high-resolution image data using coarse resolution thematic layers as reference. Validation shows an overall accuracy of 96\,\% with omission and commission errors less than 4\,\% and 1\,\%, respectively.},
  journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14610704,~to-add-doi-URL,data-transformation-modelling,europe,human-settlement,mapping,modelling,open-data,remote-sensing},
  lccn = {INRMM-MiD:c-14610704},
  number = {5}
}
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