Scientific publications

Литинский П.Ю.

Классификация сканерных снимков методом моделирования спектрального пространства

// Труды КарНЦ РАН. No 5. Сер. Математическое моделирование и информационные технологии, вып. 2. 2011. C. 45-54

Litinsky P.Yu. Multispectral imagery classification method based on spectral space modeling // Transactions of Karelian Research Centre of Russian Academy of Science. No 5. Mathematical Modeling and Information Technologies. 2011. Pp. 45-54

Keywords: remote sensing, multispectral imagery classification, geoinformation modeling.

A method for satellite imagery (Landsat TM/ETM+, IRS, etc.) classification based on spectral space modeling is described. The 3D model is built in xyz-axes, where x and y are the first two principal components of the image matrix in logarithmic form (bands G, R, NIR, SWIR2), and z is the moisture stress index MSI (SWIR1/NIR). Ambiguous spectral classes are decomposed using the geomorphometric model and time series imagery. The method is optimal for taiga ecosystem structure and dynamics modeling.

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Last modified: September 26, 2016