Open Innovation, Soft Branding and Green Influencers: Critiquing 'Fast Fashion' and 'Overtourism'

This paper explores digital reality replication for cultural consumption and green-digital open-system innovation, along with responsible, sustainable practices fashioned in a post-COVID-19 era. We address these after the dystopian effects of lockdown on global tourism and, in particular, the looming crisis of unsustainable 'overtourism'. The aim of this paper is to disclose problems and policies related to moderating consumption to more sustainable levels. The scope of the article tackles three fields: urban re-branding, fast fashion, and overtourism. Each problem area is analysed against the background of digital surveillance in the attention economy with the aid of a conceptual model. Accordingly, the principal objectives of this paper are to analyse key sustainability problem sources, evolutionary processes, and policy responses. The paper's originality and value lie in its recognition of tractable problem engagement through conceptual and practicable methods. This contribution also explores other consumption modes that tourists appreciate, namely, retail activity and its unsustainable "fast fashion" obsession. Finally, the paper analyses urban soft branding, the third tourism attractor within the niche touristic activity of the creative-cultural and gastronomic kind, which also features impulses that affect the perpetuation of unsustainable touristic practices. Thus, this contribution also assesses various studies on tourism futures that exploit digital media to assist in conserving both natural and cultural environments. Accordingly, we first narrate the soft re-branding of an "Art City" as a "Fashion City" and consider the example of green-digital innovation in the cultural milieu of Florence, Italy, in light of criticism of the unsustainability of "fast fashion". We consider which actions are envisioned or advised in the similarly "over-touristed" city of Venice. In a different vein, we consider whether the mobilisation of 'pop celebrity' performers such as audience engagers or influencers works for sustainable intervention through an assessment of the cultural interventions of Madonna in Lisbon. Finally, we anatomise "green" politics and policies for creative-cultural cities with the support of digital media to influence sustainable actions to moderate or, alternatively, revitalise polluted, congested, or otherwise over-touristed city centres. The greening of central Paris, Barcelona, Milan, and London offer a a series of examples of this type of moderation and revitalisation. Keywords: digital reproduction; open innovation; lockdown; overtourism; soft branding; influencer

Discrete Representation of Urban Areas through Simplification of Digital Elevation Data

In recent years there has been large increase in the amount of digital mapping data of landscapes and urban environments available through satellite imaging. This digital information can be used to develop wind flow simulators over large cities or regions for various purposes such as pollutant transport control, weather forecasts, cartography and other topographical analysis. It can also be used by architects for city planning or by game programmers for virtual reality and similar applications. But this data is massive and contains a lot of redundant information such as trees, cars, bushes, etc. For many applications, it is beneficial to reduce these huge amounts of data through elimination of unwanted information and provide a good approximate model of the original dataset. The resultant dataset can then be utilized to generate surface grids suitable for CFD purposes or can be used directly for real-time rendering or other graphics applications. Digital Elevation Model, DEM, is the most basic data type in which this digital data is available. It consists of a sampled array of elevations for ground positions that are regularly spaced in a Cartesian coordinate system. The purpose of this research is to construct and test a simple and economical prototype which caters to image procesing and data reduction of DEM images through noise elimination and compact representations of complex objects in the dataset. The model is aimed at providing a synergy between resultant image quality and its size through the generation of various levels of detail. An alternate approach using the concepts of standard deviation helps in achieving the desired goal and the results obtained by testing the model on Salt Lake City dataset verify the claims. Thus, this thesis is aimed at DEM image processing to provide a simple and compact representation of complex objects encountered in large scale urban environment datasets and reduce the size of the dataset to accommodate efficient storage, computation, fast transmission across networks and interactive visualization