A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data
Joint Authors
Akhtar Khan, Naeem
Qadri, Salman
Khan, Dost Muhammad
Ahmad, Farooq
Qadri, Syed Furqan
Babar, Masroor Ellahi
Shahid, Muhammad
Ul-Rehman, Muzammil
Razzaq, Abdul
Shah Muhammad, Syed
Fahad, Muhammad
Ahmad, Sarfraz
Pervez, Muhammad Tariq
Naveed, Nasir
Aslam, Naeem
Jamil, Mutiullah
Rehmani, Ejaz Ahmad
Ahmad, Nazir
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-06-08
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land.
A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately.
Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared) while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image.
The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI).
Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data.
For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class).
By implementing a cross validation method (80-20), we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively.
American Psychological Association (APA)
Qadri, Salman& Khan, Dost Muhammad& Ahmad, Farooq& Qadri, Syed Furqan& Babar, Masroor Ellahi& Shahid, Muhammad…[et al.]. 2016. A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data. BioMed Research International،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1099145
Modern Language Association (MLA)
Qadri, Salman…[et al.]. A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data. BioMed Research International No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1099145
American Medical Association (AMA)
Qadri, Salman& Khan, Dost Muhammad& Ahmad, Farooq& Qadri, Syed Furqan& Babar, Masroor Ellahi& Shahid, Muhammad…[et al.]. A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1099145
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099145