DALMINE
Overview
Date/time interval
Syllabus
Course Objectives
By the end of the course, students will be able to analyse architectural artefacts, urban aggregates and territorial contexts from both a qualitative and quantitative perspective, understanding the relationship between built form, environment, acquisition techniques and systems of representation.
The course provides the theoretical and operational tools needed to carry out architectural survey through integrated procedures for data acquisition, processing, interpretation and restitution. Students will acquire knowledge of the main methods of direct, instrumental and digital survey, of metric and morphological documentation techniques, and of the processes used to produce graphic and three-dimensional models for the knowledge, representation and communication of the built heritage.
Special attention will be paid to new technologies for survey and digital documentation, with reference to photogrammetric processes, three-dimensional reconstruction, point clouds, meshes and textures, surface mapping and the controlled use of artificial-intelligence-based tools. These tools will not be considered as substitutes for the survey method, but as operational supports to be critically evaluated in relation to data quality, process traceability and the metric and geometric consistency of the final outputs.
Students will also be expected to distinguish between image-enhancement operations that are compatible with the survey process and transformations that are not acceptable because they may alter the metric, morphological or material content of the data. Particular attention will therefore be given to the cautious use of AI tools for noise reduction, exposure balancing, colour correction, controlled improvement of image readability and image optimisation, avoiding changes that may introduce undocumented elements or modify the geometric structure of the scene.
Course Prerequisites
Students are expected to have basic knowledge of architectural and territorial drawing, three-dimensional modelling and geomatics. A preliminary familiarity with the principles of architectural representation, measurement, digital photography and the geometric reading of the built environment is also useful.
Restoration Module
Students are expected to have a general knowledge of the restoration theories developed over the last two centuries, alongside a basic understanding of the history of architecture.
Teaching Methods
Laboratory work plays a central role in the learning process. Through real cases of architectural and urban survey, students experiment with different methods of data acquisition, processing and representation, developing operational skills and critical awareness of the methodological choices adopted.
Activities may include the use of software and digital tools for image management, photogrammetry, three-dimensional reconstruction, digital modelling, processing of point clouds and meshes, surface mapping, graphic restitution and communication of results. AI-based tools or advanced computational procedures may also be presented, with particular reference to controlled image enhancement, preparation of photographic datasets, 3D reconstruction, segmentation or classification of surfaces and optimisation of survey workflows.
The use of these tools will always be linked to a critical evaluation of the data produced. Students will be guided to verify whether the operations carried out preserve the metric, geometric and documentary consistency of the survey, avoiding automatic procedures that may generate uncontrolled alterations or introduce unverifiable information.
Since software, digital platforms, AI tools and 3D reconstruction workflows are subject to rapid updates, the operational procedures may be adapted each year according to the evolution of available technologies and the teaching objectives of the course.
Restoration module
Lectures and practical exercises, including on-site observations focusing on the material characteristics, stratigraphic aspects, and conservation conditions of a building of historical and architectural interest.
The works produced during the course will be the subject of the final examination.
Assessment Methods
Assessment is based on the evaluation of the outputs produced during the course and on their discussion during the examination. These outputs may include a methodological report, survey drawings, graphic restitutions, digital models, point clouds, meshes, textures, three-dimensional elaborations, surface mappings, videos or other products agreed upon during the exercises. The assessment takes into account the correctness of the survey method, the consistency between data acquisition, processing and restitution, the technical and graphic quality of the outputs, the student’s ability to describe operational choices and the degree of autonomy achieved. During the course, students may use software and digital tools for survey, photogrammetry, 3D reconstruction, image processing, modelling and surface mapping. Artificial-intelligence-based tools may also be introduced, particularly for controlled image enhancement, management of photographic datasets, support for three-dimensional reconstruction, surface classification and optimisation of some operational phases. The use of AI tools is allowed only if it is documented and critically controlled. Students must specify which tools have been used, for what purpose and with what effects on the survey process. Changes that alter the geometry of the artefact, introduce details that were not surveyed or transform the data in a non-verifiable way are not allowed. Image-processing operations must be limited to improving the readability, sharpness, exposure or technical quality of the dataset, without changing the metric, morphological and documentary content needed for reconstruction. The theoretical programme of reference is the one of the academic year in which the student attended the course. The applied component, however, may be updated according to the academic year in which the examination is actually taken. This distinction is necessary because the technologies, software, digital workflows and AI tools used in architectural survey and restitution change rapidly. The outputs developed during the year of attendance are considered fully consistent with the teaching pathway up to the February examination session of the following academic year. For students attending the course in academic year 2026/2027, the reference deadline is therefore the February 2028 examination session. After that deadline, the theoretical component remains linked to the year of attendance, but the lecturer may require the exercises to be updated, integrated or reworked according to the methods, software and operational procedures adopted in the academic year in which the examination is taken. The final mark, expressed out of thirty, considers the completeness of the outputs, the quality of the restitution, the correctness of the method followed, the ability to critically read the case study, the awareness shown in the use of survey and representation tools, and the correct and documented use of AI technologies where applicable.
Restoration module
The examination consists of a discussion of the coursework produced during the module, alongside an oral interview to assess individual theoretical knowledge. The assessment of theoretical knowledge may be conducted via a written test, should the need arise during the course.
Contents
The course consists of theoretical lectures and applied exercises on case studies, aimed at learning the operational methods of architectural survey and survey of the built environment.
The following topics will be addressed: theoretical principles of architectural and urban survey; methods for reading, interpreting and geometrically describing the built environment; metric acquisition and graphic documentation techniques; direct, topographic, photogrammetric and digital survey; photographic acquisition for three-dimensional reconstruction; organisation and control of image datasets; management of quality parameters in Structure from Motion and Multi-View Stereo procedures; construction, cleaning and optimisation of point clouds, meshes and three-dimensional models; production and control of textures; surface mapping and restitution of the geometric, material and chromatic characteristics of surfaces; two-dimensional and three-dimensional representation of geometric, material and thematic information.
A specific part of the course will be devoted to the use of new technologies and AI tools in survey processes. In particular, the course will discuss possible applications of artificial intelligence for controlled enhancement of photographic images, noise reduction, exposure correction, management of underexposed or poorly readable images, improvement of apparent sharpness and preparation of photographic datasets for photogrammetry. These procedures will be addressed with methodological caution, distinguishing acceptable interventions, aimed at improving the readability of data already present in the image, from procedures that are not compatible with survey because they may generate artificial content or alter the geometry, texture or documentary consistency of the scene.
Experimental workflows for 3D reconstruction and advanced digital representation will also be introduced, with reference to the generation of three-dimensional models from images, the management of textured meshes, the integration of photographic and geometric data, surface mapping and the possible use of AI tools for segmentation, classification, surface recognition, support in data cleaning and optimisation of restitution processes.
The exercises will be developed on real case studies and may include data acquisition, controlled image processing, photogrammetric processing, three-dimensional reconstruction, digital modelling, surface mapping, production of graphic outputs and development of representations for the documentation, analysis and communication of the surveyed object.
Restoration module:
- Evolution of heritage protection: from Restoration Charters to the Italian Cultural Heritage Code.
- Methodological issues: prioritising mitigation or slowing of weathering and decay rather than erasure; in seismic contexts, structural improvement rather than full regulatory compliance; the use of innovative materials and techniques versus the traditional ones.
- Analytical tools for historical buildings: stratigraphic analysis, analysis of historic construction systems, decay mapping, and the survey and representation of structural damage and crack patterns.
Online Resources
More information
Students who intend to take the examination in academic years following the year of attendance must contact the lecturer before completing or resuming the outputs. This will make it possible to verify whether the exercises already carried out are still consistent with the course or whether they need to be updated according to the tools, software, digital workflows, AI tools and methods adopted in the academic year in which the examination is taken.
The use of artificial intelligence tools is permitted only as an operational and critical support, not as a replacement for the knowledge and interpretative process required of the student. Any use of AI tools for image enhancement, 3D reconstruction, texture management, surface mapping or production of outputs must be declared, described and justified in the methodological report.
Procedures that alter the geometry of the artefact, arbitrarily modify surfaces, generate undocumented details or produce representations that cannot be verified against the acquired data are not permitted. Image-processing operations must be limited to improving the readability and technical quality of the dataset, without modifying the metric, morphological and documentary content required for survey reconstruction and restitution.
For non-attending students, or for students who have not completed the laboratory activities during the year in which the course was delivered, the applied exercises must be agreed upon with the lecturer.