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This study was carried out in preparation for the conservation of the oil painted dome of Archangel Gabriel church located at Haret El Saqqayeen in Abdeen (Cairo). Stratigraphic, chemical and environmental studies were conducted to examine the painting technique and to assess the conservation state of the dome. The dome was imaged using Multi-spectral imaging and samples were collected from representative areas. Cross-sections were investigated by the means of scanning electron microscopy coupled with dispersive energy of X-ray spectrometer (SEM-EDS) and stereo microscopy. Fourier transformed infrared spectroscopy (FTIR) and gas chromatography-mass spectroscopy (GC/MS) was employed for the identification of the paint medium. X-ray diffraction (XRD) and the colorimetric measurements were conducted for characterization the differences of hues between the original and non-original pigments. As a part of the study, the environment within the dome was measured with data loggers and gas sampling. The results showed that the painted dome dates back to two different periods. The older paintings were applied before 1907 and were covered by ground layers to be repainted in 1907. Non-professional over-painting and the uncontrolled indoor climate have a significant role in the deterioration phenomena of the dome.

Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the data.