Indexes for assessing the spectral range more sensitive to the detection of the buried structures

Angelo Palombo; Rosa Maria Cavalli; Lorenzo Fusilli; Simone Pascucci; Federico Santini

doi:10.1117/12.739071

30 October 2007 Indexes for assessing the spectral range more sensitive to the detection of the buried structures

Angelo Palombo, Rosa Maria Cavalli, Lorenzo Fusilli, Simone Pascucci, Federico Santini

Author Affiliations +

Proceedings Volume 6749, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII; 67492Z (2007) https://doi.org/10.1117/12.739071
Event: SPIE Remote Sensing, 2007, Florence, Italy

Abstract

Buried man-made structures, like archaeological handiworks, altering the natural trend of the soil surface can yield tonal anomalies on remotely sensed images. These anomalies differ in size and/or intensity according to either the environmental conditions at the time of acquisition or the spectral and spatial characteristics of the images. The research challenge is to identify the best wavelength to detect these anomalies. In this paper we have set up two new parameters for identifying and assessing the potential of anomaly detection: the Detection Index (DI), which counts the pixels related to the marks, and the Separation Index (SI), which relates the difference in brightness of the marks with respect to the background. These two indexes have been tested on MIVIS (Multispectral Visible Imaging Spectrometer) airborne hyperspectral data acquired on remains not yet excavated of a few archaeological sites. Results show that such indexes are an efficient, flexible and quick tool for assessing the image potential to detect buried structures. Moreover, when they are applied to hyperspectral data, they allows for identifying the spectral range more sensitive to the detection of the buried structures.

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Angelo Palombo, Rosa Maria Cavalli, Lorenzo Fusilli, Simone Pascucci, and Federico Santini "Indexes for assessing the spectral range more sensitive to the detection of the buried structures", Proc. SPIE 6749, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, 67492Z (30 October 2007); https://doi.org/10.1117/12.739071

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