Automated detection of changes in urban development on multispectral satellite imagery of submeter resolution
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2018.2.02Keywords:
satellite monitoring, urban development, multi-time images, image processing, principal component analysis, updating mapsAbstract
The method for increasing the efficiency of automated detection of changes in urban development using multispectral satellite images of submeter spatial resolution of the visible and IR bands has been developed that employs the principal component analysis (PCA) for data of all spectral channels. By processing the multi-time images from the Pleiades-1A satellite, vector layers of detected changes in urban development were obtained thus confirming the high efficiency of the suggested method. Due to the high degree of automation of the satellite imagery processing, the developed technique allows to significantly reduce the labor intensity and, as a result, increase the efficiency of updating maps.References
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