Identification of Geospatial Objects Using Spectral Pattern

Identification of Geospatial Objects Using Spectral Pattern

ISBN13: 9781522570332|ISBN10: 1522570330|EISBN13: 9781522570349
DOI: 10.4018/978-1-5225-7033-2.ch038
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MLA

Barman, Subhabrata. "Identification of Geospatial Objects Using Spectral Pattern." Environmental Information Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 882-893. https://doi.org/10.4018/978-1-5225-7033-2.ch038

APA

Barman, S. (2019). Identification of Geospatial Objects Using Spectral Pattern. In I. Management Association (Ed.), Environmental Information Systems: Concepts, Methodologies, Tools, and Applications (pp. 882-893). IGI Global. https://doi.org/10.4018/978-1-5225-7033-2.ch038

Chicago

Barman, Subhabrata. "Identification of Geospatial Objects Using Spectral Pattern." In Environmental Information Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 882-893. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7033-2.ch038

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Abstract

Solar radiation on hitting a target surface may be transmitted, absorbed or reflected. Different materials reflect and absorb differently at different wavelengths. The reflectance spectrum of a material is a plot of the fraction of radiation reflected as a function of the incident wavelength and serves as a unique signature for the material. In principle, a material can be identified from its spectral reflectance signature if the sensing system has sufficient spectral resolution to distinguish its spectrum from those of other materials. This premise provides the basis for multispectral remote sensing. Nguyen Dinh Duong (1997) proposed a method for decomposition of multi-spectral image into several sub-images based on modulation (spectral pattern) of the spectral reflectance curve. The hypothesis roots from the fact that different ground objects have different spectral reflectance and absorption characteristics which are stable for a given sensor. This spectral pattern can be considered as invariant and be used as one of classification rules.

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