Open AccessEffect of Spectral Bandwidths on Linear Feature Extraction: An Evaluation of Landsat ETM+ and OLI Sensors
Author(s) -
Ali Imanian,
Adel Asadi,
Majid H. Tangestani,
Saeid Homayouni,
Ali Faghih
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/767/1/012046
Subject(s) - panchromatic film , principal component analysis , remote sensing , standard deviation , feature extraction , pattern recognition (psychology) , computer science , environmental science , geology , mathematics , artificial intelligence , multispectral image , statistics
Hitherto there have been many studies comparing the usefulness of OLI and ETM+ sensors for linear feature extraction. However, not too much attention has been paid to the differences in the bandwidth of the two sensors. In this study, the suitability of Landsat ETM+ and OLI sensors for automatic detection of linear features by LINE algorithm was compared. In this study, eight regions in northern, central and southern parts of Iran were selected based on the diversity of lithology, the pristine status, and lack of human activities for the comparison of the two datasets. Results revealed that LINE algorithm performed better on the images with higher standard deviation. The ETM+ datasets are more suitable for linear feature extraction because ETM+ panchromatic band and first principal component analysis image (PC1 image) of ETM+ datasets have higher standard deviation compared to OLI datasets.