Hyper-Spectral Data and Techniques for Land-use Land-Cover Analysis using Two Time Data for Lonar Town, Buldhana District of Maharashtra State

Neelam Rawat; Arvind Pandey

Hyper-Spectral Data and Techniques for Land-use Land-Cover Analysis using Two Time Data for Lonar Town, Buldhana District of Maharashtra State

Neelam Rawat *

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Arvind Pandey

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Hyper-Spectral Data and Techniques for Land-use Land-Cover Analysis using Two Time Data for Lonar Town, Buldhana District of Maharashtra State

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Abstract

Hyper-spectral optical data has been the key for accurate mapping in various field of scientific research to get results in different dimension. Based on this the present study involves two different images classify by different technique to improve the spectral resolution classification for the LULC areas using their unique spectral reflectance. The Optimum bands for the urban, vegetation, agriculture and water features are found using the spectral library is created for different invariant LULC features. The performance evaluation of the Hyperion image is carried out in terms of spatial, spectral and feature based and the results shows Spectral Angle Mapper with n-D visualizer produces a better classification output compared to the Spectral Angle Mapper and Support Vector Machine method for a heterogeneous LULC area. Accuracy assessment also revealed choosing reference pixels for classification using MNF scatterplots and then refining them use n-D visualizer increases classification accuracy.

References

7 Cites in Article

Reference Format

Somdatta Chakravortty (2011). QUALITY ENHANCEMENT OF HYPERSPECTRAL IMAGE DATA THROUGH ATMOSPHERIC CORRECTION: A CASE STUDY OF HENRY AND LOTHIAN ISLANDS OF SUNDERBAN BIOSPHERE RESERVE, WEST BENGAL.
A Farooq,F Qurat-Ul-Ain (2012). Pixel Purity Index Algorithm and n-Dimensional Visualization for ETM+ Image Analysis: A Case of District Vehari.
K Khurshid,Karl Staenz,Lixin Sun,Robert Neville,H White,Abdou Bannari,Catherine Champagne,Robert Hitchcock (2006). Preprocessing of EO-1 Hyperion data.
George Petropoulos,Kostas Arvanitis,Nick Sigrimis (2012). Hyperion hyperspectral imagery analysis combined with machine learning classifiers for land use/cover mapping.
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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Neelam Rawat, Arvind Pandey. 2017. "Hyper-Spectral Data and Techniques for Land-use Land-Cover Analysis using Two Time Data for Lonar Town, Buldhana District of Maharashtra State". Global Journal of Science Frontier Research - H: Environment & Environmental geology GJSFR-H Volume 17 (GJSFR Volume 17 Issue H2).

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GJSFR Volume 17 Issue H2

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

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Classification

GJSFR-H Classification FOR Code: 120599

Submission ReceivedMay 1, 2017
Peer Review Double Blind
Handling Editor
Accepted May 30, 2017
Published June 11, 2017

Version of record

v1.2

Issue date

July 4, 2017

Language

English

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Article Matrices

Total Score: 147

Country: India

Subject: Global Journal of Science Frontier Research

Authors: Arvind Pandey, Smrti Rawat , Neelam Rawat (PhD/Dr. count: 0)

View Count (all-time): 382

Total Views (Real + Logic): 1315

Total Downloads (simulated): 112

Publish Date: 2017 06, Sun

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Total Views: 1.3K

Total Downloads: 112

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