Different processing techniques to analyze high resolution hyperspectral data of urban areas

Author(s):  
A. Galli ◽  
S. Malinverni
2020 ◽  
Vol 13 (1) ◽  
pp. 92
Author(s):  
Antonio Costanzo ◽  
Donatella Ebolese ◽  
Silvestro Antonio Ruffolo ◽  
Sergio Falcone ◽  
Carmelo la Piana ◽  
...  

Nanotechnology-based materials are currently being tested in the protection of cultural heritage: ethyl silicate or silica nanoparticles dispersed in aqueous colloidal suspensions mixed with titanium dioxide are used as a coating for stone materials. These coatings can play a key role against the degradation of stone materials, due to the deposit of organic matter and other contaminants on the substrate, a phenomenon that produces a greater risk for the monuments in urban areas because of the increasing atmospheric pollution. However, during the application phase, it is important to evaluate the amount of titanium dioxide in the coatings on the substrate, as it can produce a coverage effect on the asset. In this work, we present the hyperspectral data obtained through a field spectroradiometer on samples of different stone materials, which have been prepared in laboratory with an increasing weight percentage of titanium dioxide from 0 to 8 wt%. The data showed spectral signatures dependent on the content of titanium dioxide in the wavelength range 350–400 nm. Afterwards, blind tests were performed on other samples in order to evaluate the reliability of these measurements in detecting the unknown weight percentage of titanium dioxide. Moreover, an investigation was also performed on a test application of nanoparticle coatings on a stone statue located in a coastal town in Calabria (southern Italy). The results showed that the surveys can be useful for verifying the phase of application of the coating on cultural heritage structures; however, they could also be used to check the state of the coated stone directly exposed over time to atmospheric, biological and chemical agents.


2021 ◽  
Vol 772 ◽  
pp. 145428
Author(s):  
Haixia Feng ◽  
Jian Li ◽  
Haiying Feng ◽  
Erwei Ning ◽  
Qi Wang
Keyword(s):  

1998 ◽  
Author(s):  
Bing Zhang ◽  
Jiangui Liu ◽  
Xiangjun Wang ◽  
Changshan Wu

2021 ◽  
pp. 118591
Author(s):  
Hao Lin ◽  
Siwei Li ◽  
Jia Xing ◽  
Tao He ◽  
Jie Yang ◽  
...  

2007 ◽  
Author(s):  
Marek K. Jakubowski ◽  
David Pogorzala ◽  
Timothy J. Hattenberger ◽  
Scott D. Brown ◽  
John R. Schott

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