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Vol 199
Pages:
269
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RUS

Automatic interpretation technology of aerial and satellite images according to different methods of land cover for protected areas

Authors:
A. A. Bogolyubova
About authors
  • National Mineral Resources University (Mining University)
Date submitted:
2011-11-26
Date accepted:
2012-01-06
Date published:
2012-05-01

Abstract

This paper focused on remote sensing,  digital  acquisition  and digital  processing methods for the purpose of land cover automatic classification of Yuntolovsky reserve. It presents the technique of automatic identification of land cover according to different methods. Comparisons the results of maximum likelihood method and neural networks approach are presented in the paper.

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References

  1. Боголюбова А.А. Классификация почвенно- растительного покрова особо охраняемых природных территорий Санкт-Петербурга // Актуальные проблемы лесного комплекса: Сб. научн. трудов по итогам международной научно-технической конференции. Брянск, 2011. Вып.26. С.168-172.
  2. Волкова Е.А. Юнтоловский региональный комплексный заказник / Е.А.Волкова, Г.А.Исаченко, В.Н.Храмов. СПб, 2005. 202 с.
  3. Назаров Л.Е. Нейросетевые алгоритмы совместной обработки совокупности разнородных космических изображений Земли / Л.Е.Назаров, А.А.Чухланцев, А.М.Шутко // Цифровая обработка данных и ее применение: Сб. докл. по итогам 6-й международной конференции DSPA-2004. СПб, 2004. Т.1. С.195.
  4. О государственном природном комплексном заказнике регионального значения «Юнтоловский»: Распоряжение губернатора Санкт-Петербурга от 30.11.99 г.
  5. № 1275-р // Вестник администрации Санкт-Петербурга
  6. № 12. 1999. 27 декабря.
  7. Iwaniak A. Feature extraction in high-resolution raster images using neural networks / A.Iwaniak, T.Kubik, P.Tymków // Reports on Geodesy. Warszawa, Poland. 2006. Vol.2. N 77. P.263-271.
  8. Tymków Przemysław. Application of photogram-metric and remote sensing methods for identification of resistance coefficients of hight water flow in river valleys. Wroclaw, 2009. 101 p.

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