![]() ![]() Planning appropriate and compatible conservation and restoration interventions to tackle the deterioration of historic structures requires a comprehensive knowledge of the preservation state. ![]() However, environmental pressures and anthropogenic factors cause constant alterations and impose significant risks. The historic build environment is a vital aspect of a place's culture, history, and landscape, which necessitates measures to ensure its preservation through time. Furthermore, the utilization of low-cost photographic equipment and easily operable digital image processing software adds to the practicality and agility of the presented methodology.Īrchitectural heritage possesses outstanding value while concomitantly comprises a fundamental manifestation of sociocultural identity. The automated thematic mapping facilitates the spatial and semantic description of the deterioration patterns. Several spectral band combinations and image classification techniques (regression, decision tree, and ensemble learning algorithmic implementations) are evaluated to propose an accurate approach. This work combines reflectance imaging and supervised segmentation, based on machine learning methods, to automatically segment deterioration patterns on multispectral image composites, using a weathered historic fortification as a case study. ![]() The automated mapping of deterioration is a direction not often explored, especially when the investigated architectural surfaces present a multitude of deterioration forms and consist of heterogeneous materials, which significantly complicates the generation of thematic decay maps. It is usually performed using non-destructive methods such as mapping of surface features. Documentation of deterioration makes it possible to identify risk factors and interpret weathering mechanisms. The conservation of historic structures requires detailed knowledge of their state of preservation. ![]()
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