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Admired and despised, created and destroyed, legal and illegal: Contemporary graffiti are polarising, and not everybody agrees to label them as cultural heritage. However, if one is among the steadily increasing number of heritage professionals and academics that value these short-lived creations, their digital documentation can be considered a part of our legacy to future generations. To document the geometric and spectral properties of a graffito, digital photographs seem to be appropriate. This also holds true when documenting an entire graffiti-scape consisting of 1000s of individual creations. However, proper photo-based digital documentation of such an entire scene comes with logistical and technical challenges, certainly if the documentation is considered the basis for further analysis of the heritage assets. One main technical challenge relates to the photographs themselves. Conventional photographs suffer from multiple image distortions and usually lack a uniform scale, which hinders the derivation of dimensions and proportions. In addition, a single graffito photograph often does not reflect the meaning and setting intended by the graffitist, as the creation is frequently shown as an isolated entity without its surrounding environment. In other words, single photographs lack the spatio-temporal context, which is often of major importance in cultural heritage studies. Here, we present AUTOGRAF, an automated and freely-available orthorectification tool which converts conventional graffiti photos into high-resolution, distortion-free, and georeferenced graffiti orthophotomaps, a metric yet visual product. AUTOGRAF was developed in the framework of INDIGO, a graffiti-centred research project. Not only do these georeferenced photos support proper analysis, but they also set the basis for placing the graffiti in their native, albeit virtual, 3D environment. An experiment showed that 95 out of 100 tested graffiti photo sets were successfully orthorectified, highlighting the proposed methodology’s potential to improve and automate one part of contemporary graffiti’s digital preservation.

Climate change and the associated glacier retreat lead to considerable enlargement and alterations of the proglacial systems. The colonisation of plants in this ecosystem was found to be highly dependent on terrain age, initial site conditions and geomorphic disturbances. Although the explanatory variables are generally well understood, there is little knowledge on their collinearities and resulting influence on proglacial primary succession. To develop a sphere-spanning understanding of vegetation development, a more interdisciplinary approach was adopted. In the proglacial areas of Fürkeleferner, Zufallferner and Langenferner (Martell Valley, Eastern Italian Alps), in total 65 plots of 5×2 m were installed to perform the vegetation analysis on vegetation cover, species number and species composition. For each of those, 39 potential explanatory variables were collected, selected through an extensive literature review. To analyse and further avoid multicollinearities, 33 of the explanatory variables were clustered via principal component analysis (PCA) to five components. Subsequently, generalised additive models (GAMs) were used to analyse the potential explanatory factors of primary succession. The results showed that primary succession patterns were highly related to the first component (elevation and time), the second component (solar radiation), the third component (soil chemistry), the fifth component (soil physics) and landforms. In summary, the analysis of all explanatory variables together provides an overview of the most important influencing variables and their interactions; thus it provides a basis for the debate on future vegetation development in a changing climate.

Graffiti are polarising. Some consider them vandalism, others part of our cultural heritage. If we consider graffiti to be part of our cultural heritage, we should also treat them as such. However, long-term and detailed graffiti documentation initiatives are sparse, so many of the existing archives with graffiti records are biased and incomplete. In addition, graffiti records usually suffer from decontextualisation, that is the lack of environmental information (be it spatially, temporally, but also smell and weather conditions). This means that graffiti documentation might not reflect the intended setting or meaning by the creator. INDIGO, a graffiti-centred academic project, largely overcomes the issue of decontextualisation by designing and implementing photogrammetric engineering approaches that support the ongoing documentation of an extensive graffiti-scape. The latter is situated along the Donaukanal, Vienna’s central waterway and one of the most prominent graffiti hotspots worldwide. One innovation developed in the framework of INDIGO is a freely available Metashape add-on called AUTOGRAF. AUTOGRAF employs photogrammetric computer vision techniques to automatically create ortophotographs from all photographed graffiti. Orthophotographs or orthophotomaps are distortion-free images, combining photographs’ visual qualities with characteristics of maps. They allow embedding the graffiti in their native, albeit virtual, 3D environment and can thus largely overcome decontextualisation. In this contribution, we showcase the significant advantages of orthophotomaps over conventional photographs and introduce the AUTOGRAF-based workflow that allows the automated derivation of graffiti orthophotos. INDIGO will use this tailor-made tool to enable graffiti analysis in unprecedented detail by mapping and displaying graffiti in their original setting along the Donaukanal.

Graffiti are polarising. Some consider them vandalism, others part of our cultural heritage. If we consider graffiti to be part of our cultural heritage, we should also treat them as such. However, long-term and detailed graffiti documentation initiatives are sparse, so many of the existing archives with graffiti records are biased and incomplete. In addition, graffiti records usually suffer from decontextualisation, that is the lack of environmental information (be it spatially, temporally, but also smell and weather conditions). This means that graffiti documentation might not reflect the intended setting or meaning by the creator. INDIGO, a graffiti-centred academic project, largely overcomes the issue of decontextualisation by designing and implementing photogrammetric engineering approaches that support the ongoing documentation of an extensive graffiti-scape. The latter is situated along the Donaukanal, Vienna’s central waterway and one of the most prominent graffiti hotspots worldwide. One innovation developed in the framework of INDIGO is a freely available Metashape add-on called AUTOGRAF. AUTOGRAF employs photogrammetric computer vision techniques to automatically create ortophotographs from all photographed graffiti. Orthophotographs or orthophotomaps are distortion-free images, combining photographs’ visual qualities with characteristics of maps. They allow embedding the graffiti in their native, albeit virtual, 3D environment and can thus largely overcome decontextualisation. In this contribution, we showcase the significant advantages of orthophotomaps over conventional photographs and introduce the AUTOGRAF-based workflow that allows the automated derivation of graffiti orthophotos. INDIGO will use this tailor-made tool to enable graffiti analysis in unprecedented detail by mapping and displaying graffiti in their original setting along the Donaukanal., document | archive | disseminate graffiti-scapes, 2022: document | archive | disseminate graffiti-scapes

This presentation was given by Benjamin Wild during Session E of the goINDIGO 2022 international graffiti symposium. Graffiti and street art are unique forms of cultural heritage which have not yet received the scientific attention they deserve. The potential of graffiti research to answer a variety of social and cultural research questions is underexploited. One reason for this lack of academic rigor lies within the very sparse availability of well-curated and publicly accessible graffiti data. One obvious foundation for a graffiti dataset is images depicting the various pieces, tags or throw-ups. The few existing graffiti image databases do not allow the study of the graffiti’s exact shapes and dimensions as the photographs suffer from various distortions which are introduced by topography, perspective, or the camera itself. Orthophotos have the great advantage of removing above-mentioned image distortions. The creation of orthophotos, however, is time-consuming and requires considerable manual interaction, which poses a significant obstacle considering that comprehensive and up-to-date graffiti databases often deal with hundreds of images per week. Here, we present a novel methodology which overcomes the above-mentioned limitations in present-day graffiti documentation by deriving graffiti orthophotos in a highly automated way. In contrast to conventional photographs, orthophotos are adjusted for the graffiti surface topography and had all perspective and lens distortions removed. As a result, orthophotos allow the measurement of coordinates, distances, and areas of the depicted graffiti, enabling the derivation of exact proportions and relating the object to a real-world geographic coordinate reference system. Orthophotos in this context are therefore accurate maps of graffiti. The derivation of orthophotos, however, is complex and requires not only exact knowledge about the three-dimensional surface geometry of the object but also about the camera’s internal geometry and its exact location and orientation in space. We are developing a photogrammetric methodology and associated tool that derives the required information based on graffiti photos and outputs the desired orthophotos without any manual intervention during the process. In this talk, we present this bespoke photogrammetric approach which is currently investigated in the framework of the graffiti documentation and dissemination project INDIGO and is built as a Python add-on to the commercial package Agisoft Metashape Professional. First tests were conducted at the Donaukanal (Eng. Danube Canal), a central waterway through Vienna and a famous graffiti hotspot. The results indicate a reliable performance of our approach: the majority (ca. 85%) of the tested graffiti images were successfully and automatically turned into orthophotos. We will present those results and discuss where further finetuning is needed and demonstrate why the presented tool has the potential to largely automize the way graffiti are being documented. This approach will enable the building of a solid and extensive database for advanced graffiti research., The INDIGO graffiti project is funded by the Heritage Science Austria programme of the Austrian Academy of Sciences (ÖAW)

This is the book of abstracts created for the goINDIGO 2022 international graffiti symposium organised in the framework of the academic project INDIGO.

This presentation was given by Benjamin Wild at the 3D-ARCH 2022 conference in Mantova, Italy. The presentation won the best paper award., The INDIGO graffiti project is funded by the Heritage Science Austria programme of the Austrian Academy of Sciences (��AW)

Graffiti is a short-lived form of heritage balancing between tangible and intangible, offensive and pleasant. Graffiti makes people laugh, wonder, angry, think. These conflicting traits are all present along Vienna's Donaukanal (Eng. Danube Canal), a recreational hotspot – located in the city's heart – famous for its endless display of graffiti. The graffiti-focused heritage science project INDIGO aims to build the basis to systematically document, monitor, and analyse circa 13 km of Donaukanal graffiti in the next decade. The first part of this paper details INDIGO's goals and overarching methodological framework, simultaneously placing it into the broader landscape of graffiti research. The second part of the text concentrates on INDIGO's graffiti documentation activities. Given the project's aim to create a spatially, spectrally, and temporally accurate record of all possible mark-makings attached in (il)legal ways to the public urban surfaces of the Donaukanal, it seems appropriate to provide insights on the photographic plus image-based modelling activities that form the foundation of INDIGO's graffiti recording strategy. The text ends with some envisioned strategies to streamline image acquisition and process the anticipated hundreds of thousands of images.