INVESTIGATING MATERIAL DECAY OF HISTORIC BUILDINGS USING VISUAL ANALYTICS WITH MULTI‐TEMPORAL INFRARED THERMOGRAPHIC DATA

This paper shows how visual analytics methodology can be used to facilitate interpretation of multi-temporal thermographic imagery for the purpose of restoration of cultural heritage. We explore thermographic data in a visual environment from the unifying spatio-temporal per- spective in an attempt to identify spatial and spatio-temporal patterns that could provide information about the structure and the level of decay of the material, and the presence of other physical phenomena in the wall. The approach is tested on a thermographic dataset captured on the facade of a Romanesque building from the 13th century—the Cathedral in Matera (Italy).

[1]  Mark Gahegan,et al.  Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach , 2005, Cartography and geographic information science.

[2]  Ermanno G. Grinzato,et al.  Quantitative infrared thermography in buildings , 1998 .

[3]  Mark Gahegan,et al.  Introducing geovista studio: an integrated suite of visualization and computational methods for expl , 2002 .

[4]  Robert M. Edsall.  The parallel coordinate plot in action: design and use for geographic visualization , 2003, Comput. Stat. Data Anal..

[5]  Martin Charlton,et al.  Combining Geovisual Analytics with Spatial Statistics: the Example of Geographically Weighted Regression , 2008 .

[6]  André Skupin,et al.  Visualizing Demographic Trajectories with Self-Organizing Maps , 2005, GeoInformatica.

[7]  Ermanno G. Grinzato,et al.  Monitoring of ancient buildings by the thermal method , 2002 .

[8]  Ermanno G. Grinzato,et al.  Nondestructive evaluation of delaminations in fresco plaster using transient infrared thermography , 1994 .

[9]  Nik Rajic,et al.  Principal component thermography for flaw contrast enhancement and flaw depth characterisation in composite structures , 2002 .

[10]  Alfred Inselberg.  Visualization and data mining of high-dimensional data , 2002 .

[11]  Ermanno G. Grinzato,et al.  Statistical analysis of IR thermographic sequences by PCA , 2004 .

[12]  Antonia Moropoulou,et al.  Emissivity considerations in building thermography , 2003 .

[13]  Menno-Jan Kraak,et al.  Alternative Visualization of Large Geospatial Datasets , 2004 .

[14]  Martin Charlton,et al.  Exploring the spatio-temporal dynamics of geographical processes with geographically weighted regression and geovisual analytics , 2008 .

[15]  Juha Vesanto,et al.  SOM-based data visualization methods , 1999, Intell. Data Anal..

[16]  Elisabetta Rosina,et al.  Moisture detection in wood and plaster by IR thermography , 2004 .

[17]  Ermanno G. Grinzato,et al.  Thermal Characterization of Defects in Building Envelopes Using Long Square Pulse and Slow Thermal Wave Techniques , 1997 .

[18]  Diansheng Guo,et al.  Coordinating Computational and Visual Approaches for Interactive Feature Selection and Multivariate Clustering , 2003, Inf. Vis..

[19]  Urska Demsar,et al.  Knowledge Discovery in the Environmental Sciences: Visual and Automatic Data Mining for Radon Problems in Groundwater , 2007, Trans. GIS.

[20]  Daniel A. Keim,et al.  Geovisual analytics for spatial decision support: Setting the research agenda , 2007, Int. J. Geogr. Inf. Sci..

[21]  Fernando Bação,et al.  The self-organizing map, the Geo-SOM, and relevant variants for geosciences , 2005, Comput. Geosci..

[22]  Nicola Walsh,et al.  The effects of wetting and drying, and marine salt crystallization on calcarenite rocks used as building material in historic monuments , 2007, Geological Society, London, Special Publications.

[23]  Antonia Moropoulou,et al.  Applications of infrared thermography for the investigation of historic structures , 2004 .

[24]  Giovanni Maria Carlomagno,et al.  REVIEW ARICLE: Recent advances in the use of infrared thermography , 2004 .

[25]  Elisabetta Rosina,et al.  Applying Infrared Thermography to Historic Wood-Framed Buildings in North America , 2002 .