Share Email Print
cover

Journal of Applied Remote Sensing

Object-oriented and pixel-based classification approach for land cover using airborne long-wave infrared hyperspectral data
Author(s): Richa Marwaha; Anil Kumar; Arumugam Senthil Kumar
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Our primary objective was to explore a classification algorithm for thermal hyperspectral data. Minimum noise fraction is applied to thermal hyperspectral data and eight pixel-based classifiers, i.e., constrained energy minimization, matched filter, spectral angle mapper (SAM), adaptive coherence estimator, orthogonal subspace projection, mixture-tuned matched filter, target-constrained interference-minimized filter, and mixture-tuned target-constrained interference minimized filter are tested. The long-wave infrared (LWIR) has not yet been exploited for classification purposes. The LWIR data contain emissivity and temperature information about an object. A highest overall accuracy of 90.99% was obtained using the SAM algorithm for the combination of thermal data with a colored digital photograph. Similarly, an object-oriented approach is applied to thermal data. The image is segmented into meaningful objects based on properties such as geometry, length, etc., which are grouped into pixels using a watershed algorithm and an applied supervised classification algorithm, i.e., support vector machine (SVM). The best algorithm in the pixel-based category is the SAM technique. SVM is useful for thermal data, providing a high accuracy of 80.00% at a scale value of 83 and a merge value of 90, whereas for the combination of thermal data with a colored digital photograph, SVM gives the highest accuracy of 85.71% at a scale value of 82 and a merge value of 90.

Paper Details

Date Published: 17 December 2015
PDF: 20 pages
J. Appl. Rem. Sens. 9(1) 095040 doi: 10.1117/1.JRS.9.095040
Published in: Journal of Applied Remote Sensing Volume 9, Issue 1
Show Author Affiliations
Richa Marwaha, Indian Institute of Remote Sensing (India)
Anil Kumar, Indian Institute of Remote Sensing (India)
Arumugam Senthil Kumar, Indian Institute of Remote Sensing (India)


© SPIE. Terms of Use
Back to Top