Identification, Classification and Mapping of Surface Soil Types Using Hyperspectral Remote Sensing Datasets

Authors(5) :-Amol D. Vibhute, Karbhari V. Kale, Rajesh K. Dhumal, Ajay D. Nagne, Suresh C. Mehrotra

The traditional methods of soil analysis are tedious and they do not fulfill the rapid requirements of spatiotemporal variability. The present study highlights the use of hyperspectral remote sensing (HRS) datasets for soil classification. The Minimum Noise Fraction (MNF) method was implemented for dimensionality reduction of huge Hyperion data. First, ten MNFs were provided precious information. The Analytical Spectral Device (ASD) non-imaging spectroradiometer was used for recording the collected 74 soil samples. The reference spectra was analyzed and used for Hyperion image classification. The Spectral Angle Mapper (SAM) method was computed after dimensionality reduction by MNF method for soil classification. The overall accuracy of SAM classifier was 91.77 percent with Kappa Value 0.89. The black cotton soil, lateritic soil and sand dunes of surface soil types were identified, classified and mapped. The outcome of the present study is essential for digital soil analysis and its mapping of heterogeneous area.

Authors and Affiliations

Amol D. Vibhute
Geospatial Technology Research laboratory, Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
Karbhari V. Kale
Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
Rajesh K. Dhumal
Geospatial Technology Research laboratory, Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
Ajay D. Nagne
Geospatial Technology Research laboratory, Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
Suresh C. Mehrotra
Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India

Soil classification, Hyperspectral data, Minimum Noise Fraction, Spectral Angle Mapper, Dimensionality reduction, Accuracy Assessment

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 921-932
Manuscript Number : CSEIT1831151
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Amol D. Vibhute, Karbhari V. Kale, Rajesh K. Dhumal, Ajay D. Nagne, Suresh C. Mehrotra, "Identification, Classification and Mapping of Surface Soil Types Using Hyperspectral Remote Sensing Datasets ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.921-932, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831151

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