Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, 193-200, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-5-W4/193/2015/
doi:10.5194/isprsarchives-XL-5-W4-193-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
18 Feb 2015
MULTI-SENSOR RADIOMETRIC STUDY TO DETECT PATHOLOGIES IN HISTORICAL BUILDINGS
S. Del Pozo1, J. Herrero-Pascual1, B. Felipe-García2, D. Hernández-López2, P. Rodríguez-Gonzálvez1, and D. González-Aguilera1 1Dept. of Cartographic and Land Engineering, High School of Ávila, University of Salamanca, Ávila, 05003, Spain
2Regional Development Institute-IDR, University of Castilla-La Mancha, Albacete, 02071, Spain
Keywords: Architecture, Cultural Heritage, Camera, Multispectral, Laser Scanning, Remote Sensing, Close Range, Classification Abstract. This paper presents a comparative study with different remote sensing technologies to recognize pathologies in façades of historical buildings. Building materials deteriorate over the years due to different extrinsic and intrinsic agents, so assessing these diseases in a non-invasive way is crucial to help preserve them. Most of these buildings are extremely valuable and some of them have been declared monuments of cultural interest. In this way through close range remote sensing techniques, it is possible to study material pathologies in a rigorous way and in a short duration field campaign.

For the investigation two different acquisition systems were applied, active and passive methods. The terrestrial laser scanner FARO Focus 3D was used as active sensor, working at the wavelength of 905 nm. For the case of passive sensors, a Nikon D-5000 and a 6- bands Mini-MCA multispectral camera (530-801 nm) were applied covering visible and near infrared spectral range. This analysis allows assessing the sensor, or sensors combination, suitability for pathologies detection, addressing the limitations according to the spatial and spectral resolution. Moreover, the pathology detection by unsupervised classification methods is addressed in order to evaluate the automation capability of this process.

Conference paper (PDF, 2954 KB)


Citation: Del Pozo, S., Herrero-Pascual, J., Felipe-García, B., Hernández-López, D., Rodríguez-Gonzálvez, P., and González-Aguilera, D.: MULTI-SENSOR RADIOMETRIC STUDY TO DETECT PATHOLOGIES IN HISTORICAL BUILDINGS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W4, 193-200, doi:10.5194/isprsarchives-XL-5-W4-193-2015, 2015.

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