Identification of Continental Wetlands Using Different Orbital Remote Sensors

This paper evaluates the potential of false-color composite images, from 3 different remote sensing satellites, for the identification of continental wetlands. Landsat 8, Sentinel-2 and CBERS-4 scenes from three different Ramsar sites (i.e., sites designated to be of international importance) two sites located within the Mato-Grossense Pantanal and one within the Sul-mato-grossense were used for analyses. For each site, images from both the dry and rainy seasons were analyzed using Near-Infrared (NIR), Shortwave Infrared (SWIR), and visible (VIS) bands. The results show that false-color composite images from both the Landsat 8 and the Sentinel-2 satellites, with both SWIR 2-NIR-BLUE and NIR-SWIR-RED spectral band combinations, allow the identification of wetlands.

Recognition of a porphyry system using ASTER data in Bideghan – Qom province (central of Iran)

The Bideghan area is located south of the Qom province (central of Iran). The most impressive geological features in the studied area are the Eocene sequences which are intruded by volcanic rocks with basic compositions. Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) image processing have been used for hydrothermal alteration mapping and lineaments identification in the investigated area. In this research false color composite, band ratio, Principal Component Analysis (PCA), Least Square Fit (LS-Fit) and Spectral Angel Mapping (SAM) techniques were applied on ASTER data and argillic, phyllic, Iron oxide and propylitic alteration zones were separated. Lineaments were identified by aid of false color composite, high pass filters and hill-shade DEM techniques. The results of this study demonstrate the usefulness of remote sensing method and ASTER multi-spectral data for alteration and lineament mapping. Finally, the results were confirmed by field investigation.

Classification of COSMO SkyMed SAR Data Based on Coherence and Backscattering Coefficient

A novel supervised classification approach is proposed for high-resolution dual-polarization (dual-pol) amplitude COSMO SkyMed images. Coherence, mean backscattering coefficient and backscatter difference images are generated, from which the False Color Composite (FCC) image is formed. A classification scheme based on maximum likelihood algorithm land cover classification is implemented on the false color composite image to classify the river, vegetation and the urban areas of Jharia, located in the state of Jharkhand in India using MATLAB 7.6 and ENVI 4.7.

False Color Composite System of Multi-Spectral RS Images Based on IDL

Several methods of the choice in assembled spectral and color composite in the false color composite of multi-spectral RS images are discussed. The research indicates that using the OIF method to carry on the band choice, unifying the easy and feasible RGB false colored synthesis and carrying on the method of image linear extension can realize the false color composite of multi-spectral RS images effectively, and the obtaining false color image has rich information and distinctive visual effects.