ARCTIS — A MATLAB® Toolbox for Archaeological Imaging Spectroscopy

Abstract

Imaging spectroscopy acquires imagery in hundreds or more narrow contiguous spectral bands. This offers unprecedented information for archaeological research. To extract the maximum of useful archaeological information from it, however, a number of problems have to be solved. Major problems relate to data redundancy and the visualization of the large amount of data. This makes data mining approaches necessary, as well as efficient data visualization tools. Additional problems relate to data quality. Indeed, the upwelling electromagnetic radiation is recorded in small spectral bands that are only about ten nanometers wide. The signal received by the sensor is, thus quite low compared to sensor noise and possible atmospheric perturbations. The often small, instantaneous field of view (IFOV)-essential for archaeologically relevant imaging spectrometer datasets-further limits the useful signal stemming from the ground. The combination of both effects makes radiometric smoothing techniques mandatory. The present study details the functionality of a MATLAB ® -based toolbox, called ARCTIS (ARChaeological Toolbox for Imaging Spectroscopy), for filtering, enhancing, analyzing, and visualizing imaging spectrometer datasets. The toolbox addresses the above-mentioned problems. Its 8618Graphical User Interface (GUI) is designed to allow non-experts in remote sensing to extract a wealth of information from imaging spectroscopy for archaeological research. ARCTIS will be released under creative commons license, free of charge, via website (http://luftbildarchiv.univie.ac.at).

The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation

“…The potential of airborne and spaceborne imaging spectrometers has long been exploited to monitor the Earth's surface and atmosphere and to provide valuable information for the better understanding of a large number of environmental processes (e.g., [3,4]). Those applications include, for example, vegetation monitoring and ecology (e.g., [5][6][7][8][9][10][11]), geology and soils (e.g., [12][13][14][15][16][17]), coastal and inland waters (e.g., [18][19][20][21]), mapping of snow properties [22,23] and archaeological prospection [24,25].…”

Automated Extraction of the Archaeological Tops of Qanat Shafts from VHR Imagery in Google Earth

“…Soil marks can appear on bare soil changing in color, shape, or texture [1,2]. In order to identify these buried archaeological features, different types of remote sensing imagery have been used including aerial photographs [1,3,4], spaceborne and airborne RADAR images [5][6][7], airborne LIDAR images [8,9], as well as imaging spectroscopy [10][11][12][13]. Recently, archaeologists interested in detecting archaeological features are increasingly employing very high resolution (VHR) commercial satellite imagery [14][15][16][17][18][19][20].…”

Detection of Archaeological Residues in Vegetated Areas Using Satellite Synthetic Aperture Radar

“…Combining various measurements in the range of Photosynthetically Active Radiation (PAR) (400 to 700 nm) that photosynthetic plants absorb [13], with measurements in the NIR, can be used to further enhance subtle differences in vegetation stress [14]. Much research has been carried out on the use of multispectral [8,15,16] and hyperspectral [17][18][19] data for the enhancement of crop marks, exploiting multiple image bands from the visible to the NIR parts of the electromagnetic (EM) spectrum. The thermal infrared (TIR) part of the EM spectrum has also been used to detect buried structures due to their heat signature [20], which can be enhanced through calculations of the day-night thermal inertia [21].…”