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Characterising the urban tree species using hyperspectral remotely sensed data

Kumar, Kiran (2014) Characterising the urban tree species using hyperspectral remotely sensed data. Masters thesis, Manipal Institute of Tecchnology, Manipal.

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Abstract

Hyperspectral imaging has become a fast growing technique in remote sensing image processing due to recent advances. It makes use of as many as hundreds contiguous spectral bands to expand the capability of multispectral sensors that use tens of discrete spectral bands. As a result, with such high spectral resolution many subtle objects and materials can now be uncovered and extracted by Hyperspectral imaging sensors with narrow diagnostic spectral bands for detection, discrimination, classification, identification, recognition, and quantification. Many of its applications are yet to be explored. The thesis has been analysis of airborne remote sensing data from a Hyperspectral scanner and analysis of implications for encroachment monitoring and plants, trees community mapping of, different parks in Bangalore. This has been in order to enlighten the issue of whether remote sensing technologies of today are capable of producing vegetation maps of such a quality and spatial resolution that they are suitable for research and monitoring interests. Thesis work included development of methods for, image analysis of vegetation and finding values for different vegetation indices. Remotely sensed spectral vegetation indices are widely used and have benefited numerous disciplines interested in the assessment of Structure, Biochemistry, and Plant physiology/stress. The successful use of these indices requires knowledge of the units of the input variables used to form the indices. Vegetation associations can be differentiated using their hyperspectral reflectance A number of image analysis techniques have been developed to process remote sensing data. The standard image processing software’s such as MATLAB, ENVI, ERDAS, GEOMATICA etc. For my thesis work I made use of ENVI, ERDAS, ARCMAP image processing software’s.

Item Type: Thesis (Masters)
Subjects: Engineering > MIT Manipal > Instrumentation and Control
Depositing User: MIT Library
Date Deposited: 13 Nov 2014 10:41
Last Modified: 13 Nov 2014 10:41
URI: http://eprints.manipal.edu/id/eprint/141062

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