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Rock unit discrimination on Landsat TM, SIR-C and Radarsat images using spectral and textural information

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Abstract:

The paper presents results for spectral and textural analysis of the rock units in Landsat Thematic Mapper (TM) images, dual-band (L and C) and dual-polarization (HH and HV) Shuttle Imaging Radar (SIR)-C images, and C-band HH polarization Standard Beam 4 and Extended High Incidence Beam 3 Radarsat images from a study area between California and Arizona, USA. Fractal dimension, lacunarity and grey-level co-occurrence matrix (GLCM) textural feature images were created from the SIR-C and Radarsat images. Fractal dimensions were calculated using a differential box counting method and lacunarity measures were obtained using a new grey-scale lacunarity estimation method for 36 sample images extracted from the SIR-C and Radarsat images. The fractal dimension and lacunarity curves and class signature separability analysis show that, for rock unit discrimination using image textural features in the study area, the SIR-C L-HH image is more suitable than other SIR-C images and Radarsat images, and that co-polarization (HH) generally provides more textural information than cross-polarization (HV) in the study area. The study also shows that lacunarity measures can reveal the scaling properties of radar image textures for rock units. The combination of spectral information from Landsat TM images and textural information from radar images improves the image classification accuracy of rock units in the study area.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160310001632675

Affiliations: 1: Department of Geology University of New Brunswick Fredericton New Brunswick E3B 5A3 Canada, Email: bleblon@unb.ca 2: Faculty of Forestry and Environmental Management University of New Brunswick Fredericton New Brunswick E3B 6C2 Canada (506) 453-4924 (506) 453-3538, Email: bleblon@unb.ca

Publication date: September 1, 2004

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