BENCHMARK OF MACHINE LEARNING METHODS FOR CLASSIFICATION OF A SENTINEL-2 IMAGE

Pirotti F., Sunar F., Piragnolo M.

23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS), Prague, Czech Republic, 12 - 19 July 2016, vol.41, pp.335-340 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 41
  • Doi Number: 10.5194/isprsarchives-xli-b7-335-2016
  • City: Prague
  • Country: Czech Republic
  • Page Numbers: pp.335-340
  • Istanbul Technical University Affiliated: Yes

Abstract

Thanks to mainly ESA and USGS, a large bulk of free images of the Earth is readily available nowadays. One of the main goals of remote sensing is to label images according to a set of semantic categories, i.e. image classification. This is a very challenging issue since land cover of a specific class may present a large spatial and spectral variability and objects may appear at different scales and orientations.