• DocumentCode
    1798918
  • Title

    Identification and cadastral registration of water bodies through multispectral image processing with multi-layer Perceptron Neural Network

  • Author

    Dianderas, Erwin ; Rojas, Kevin ; Kemper, Guillermo

  • Author_Institution
    Centre of Inf. Technol. & Commun., Lima, Peru
  • fYear
    2014
  • fDate
    17-19 Sept. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this article is developed a technique that allows to calculate the presence of vegetation, glaciers and water bodies through multispectral image processing employing a Multi-layer Perceptron Neural Netwok, giving the option to discriminate the presence of lakes to generate the cadastral registration of these. The supervised classification that was implemented has a high level of robustness and reliability, since the validation of the data obtained at a geolocation level have a 0% of error and the parameters of the area and perimeter an approximate error of 10%.
  • Keywords
    image classification; image registration; multilayer perceptrons; vegetation; water; cadastral registration; glaciers; identification; multilayer perceptron neural network; multispectral image processing; reliability; robustness; supervised classification; vegetation; water bodies; Earth; Indexes; Lakes; Neural networks; Remote sensing; Satellites; Software; Geolocalisation; Landsat 8; Neural Network(NN); Normal Difference Snow Index (NDSI); Normal Difference Vegetation Index (NDVI); Normal Difference Water Index (NDWI); Satellite Image Processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image, Signal Processing and Artificial Vision (STSIVA), 2014 XIX Symposium on
  • Conference_Location
    Armenia
  • Type

    conf

  • DOI
    10.1109/STSIVA.2014.7010132
  • Filename
    7010132