Urbanisation is undoubtedly one of the most fundamental trends of the past two centuries. Between 1950 and 2014, the share of the global population living in urban areas increased from 30% to 54%, and by 2050 it is projected to expand by an additional 2.5 billion urban dwellers. Urbanisation yields many benefits for society, including enhanced opportunities for education, improved job prospects, better access to healthcare and cleaner water. Yet it is also associated with immense societal and environmental challenges. Inefficient planning and management practices lead to unsustainable settlements that do not enable people to advance personally, socially or economically. This article explores how smart and innovative technologies, including artificial intelligence, are revolutionising the way cities address the challenges associated with urban growth.
Such technologies help cities to utilise existing assets more effectively, allocate resources more efficiently and improve how data and information are managed and shared across systems. According to the International Data Corporation (IDC), worldwide spending on smart city technologies is forecast to reach US$80 billion in 2018, of which US$22 billion will be spent in the US alone. Investment in smart city technologies can potentially improve the sustainability of cities. The McKinsey Global Institute (MGI) suggests that such technologies could cut emissions by 10-15%, reduce water consumption by 20-30% and decrease the average commute time by 15-20%. Whether these are mobile apps that provide real-time information on public transportation delays, intelligent GIS systems that propose the shortest route to a destination or systems that track the sources of air pollution or determine electricity pricing dynamically according to demand peaks, smart city technologies have the potential to not only foster economic growth, but also to improve people’s quality of life.
Increasingly, satellite data is becoming a fundamental component of smart cities and an essential tool for city management and governance. From understanding connectivity between cities to measuring economic growth, detecting power outages or identifying where resources should be allocated after disasters, the increasing availability of satellite data is transforming how cities are managed and helping to improve their functionality.
From the point of view of urban governance, machine learning and artificial intelligence (AI) provide near-real-time information on how cities change in practice, e.g. through the conversion of green spaces into built-up structures. By ‘teaching’ computers what to look for in satellite images, rapidly expanding sources of satellite data are leveraged in combination with machine learning algorithms to quickly reveal how actual city development aligns with planning and zoning or which communities are most prone to flooding. Machine learning techniques help to automatically detect and map different types of land cover and land use across space and time, and generate important insights, analytics and visualisations.
In the past, expensive satellite imagery and limited computational power only allowed analysis of small geographical areas. This model is being replaced thanks to the wealth of publicly available and free satellite data about every location on Earth, captured every few days and in a spatial resolution of a few metres. This data is brought to the cloud and, using machine learning algorithms, analysed on various cloud-based platforms without the need to download and upload large volumes of data. This new model provides cities and governments with accessible solutions for satellite data analysis, decision-making and data sharing.
Today, AI is almost a buzzword, a kind of magic formula, based on some ‘intelligent agents’ and sophisticated algorithms that make decisions and take action for humans. But AI will never replace human validation or effective governance on the ground. ‘Smart’ technologies that collect data on the ground or from space must be leveraged to monitor and manage urban systems and to provide guidance and recommendations for better decision-making, which will in turn make cities more sustainable.
http://www.GIM-INTERNATIONAL.com Miércoles 17 de Octubre del 2018
Outside of our community, and arguably even within our wider community, the term ‘geomatics’ is unfamiliar and ill defined, writes Ian Brown, senior lecturer at Stockholm University. More common in North America than in many parts of Europe, geomatics can be said to refer to the measurement and analysis of the properties of the Earth. Planetary scientists might argue that geomatics could equally refer to the measurement of other planetary surfaces. Some may argue in favour of a more comprehensive definition, while many in the community may reject the term entirely. If we as a community can’t adopt a common terminology with common definitions and communicate that effectively, then how can we expect to engage with the public, decision-makers and future students? How can we attract new talent?
We can start by reminding ourselves that geomatics, or ‘geographic information science’ (GIS) if you prefer, exists within the Science, Technology, Engineering and Mathematics (STEM) framework. STEM is acknowledged to be fundamental to a knowledge economy. Everything from disruptive technologies (e.g. self-driving cars and e-payments) to sustainable living (e.g. fossil-free fuels and Blue Growth) requires a dynamic and STEM-educated workforce. The above-mentioned examples also require geomatics-related capabilities to greater or lesser degrees. Geomatics is a STEM subject, and students are increasingly aware that STEM-related jobs have a bright future with good prospects for career development and decent remuneration. We need to promote geomatics as STEM; we can then leverage the resources promoting STEM learning to encourage the uptake of geomatics education.
There is also much we can do ourselves, of course. We can encourage students at undergraduate level to develop skill sets that include numerical skills and technological skills. GIS is central to how we teach geography and related sciences in both the Science and Social Science faculties. Many students will have had a taste of GIS prior to university. We can emphasise that spatial analysis requires particular methods and tools. We can highlight the role geomatics plays in everything from planning fieldwork to producing maps, and modelling patterns in the landscape or populations. Big data and artificial intelligence (AI) have become popular buzzwords that border on clichés, but they are two technologies that will be deployed to address some of the pressing problems facing society and industry. Weather forecasting has used big data, quietly, for decades. Everything from agri-business/precision-farming and flood forecasting to global freight planning may reasonably be using big geodata in the near future, if not already. Generating data, analysis and services will require a mix of skill sets that includes geomatics expertise.
At our institution in Stockholm, we manage class sizes to maintain good staff-student ratios and to enable us to utilise well-equipped computer labs with professional software from leading vendors. We offer courses that deliver different levels of specialisation to enable students to meet their various needs, and we offer these across educational programmes rather than just to our specialists. Other programmes deploy their own geomatics teaching, tailored to meet their particular goals and reflecting how a mix of skills, including geomatics, can meet a broad range of user and employer needs. We emphasise that our students will develop a skill set that will allow them to perform well in the workplace after graduation, and we assign considerable time to working in the computer lab. We also give them ample opportunities to hone their capabilities for group work and individual project work.
Today’s students are unequivocally aware of the competitive labour market and they want skills that employers are demanding. Addressing this is key to successful recruitment and to providing employers with a workforce that meets their needs and tackles the challenges society faces. That in turn requires the development of geomatics skills at all levels of education and the provision of life-long learning opportunities.
http://www.GIM-INTERNATIONAL.com Miércoles 17 de Octubre del 2018
In 2017, 11 European public mapping agencies (PMAs) financed a EuroSDR project to explore the economic value of 3D geoinformation. They benefited from being able to share knowledge with one another about the findings and their concerns. For the investigated cases, the cost-benefit ratio was found to be about 1:3. Since the calculated financial benefits were rather circumstantial, however, the academics involved in the project complemented the study with a scientific article in which they attempt to provide more nuance by focusing on the broader public value. They conclude that, in general, the use of 3D geoinformation is increasingly profitable. For PMAs, future research will be not so much about whether to make the transition to 3D, but more about how to do so.
Public mapping agencies (PMAs) are in a difficult position. After 25 years the production processes for 2D mapping and GIS have finally reached a status of high efficiency, but now the market increasingly needs 3D data and information. New but here-to-stay applications like BIM, smart cities, augmented reality and climate change studies ‘demand’ it. Plus high-tech innovations and pretty 3D visualisations are more effective means of communicating data about the physical and built environments. But most PMAs are reluctant to invest in anything more than large pilots or individual projects. One of the problems is that the public authority that has to bear the costs is not usually the one that enjoys the most benefits. The core competence of PMAs is to produce all the highly reliable geographical data of the territory needed and distribute it in as client-friendly a way as possible within their imposed business model. If the clients’ needs evolve to 3D, the PMAs have to follow, otherwise they risk losing their authoritative position – or do they? That is the key question for many European PMAs, which is why they participated in the EuroSDR project to investigate the economic value of 3D.
For the study – with involvement of the company ConsultingWhere – six application fields were selected: forest management, flood management, 3D cadastre and valuation, civil contingency, asset management, and urban planning. Over the course of six different EuroSDR workshops, attended by representatives of the PMAs and the stakeholders of the application fields, value chain analysis was applied. Improved planning processes were a clear theme in all of the fields. Two application fields were selected for quantification using cost-benefit analysis: flood management, due to the ubiquity of the problem and its high political profile, and urban planning because 3D geoinformation has a significant potential to contribute to the problems of managing urban growth.
In urban planning, the costs and benefits were evaluated in detail by scaling up and comparing real-world cost estimates from Denmark, a country that uses 3D geoinformation in this field, with the Republic of Ireland (using the comparative land areas), which does not. The benefits are based on the financial impacts that are related to processes in the urban planning value chain:
- Local area planning (LAP) revision and the impact on the planning authority
- Visual impact assessment and the lower costs for developers
- Reduced time for citizens to make LAP submissions and major scheme objections
- General improvements to public-sector efficiency.
After the application of some correction factors, the net value of the cost-benefit analysis for a ten-year period was calculated as 1:2.1 and a net present value (NPV) of €22 million.
In flood management, the same financial model was applied but three approaches were taken to ‘triangulate’ the assessment. Firstly, a cost avoidance method used data from Switzerland, one of the few countries in Europe where the PMA has made a complete switch to 3D several years ago. Estimating the damage avoided since then thanks to the use of 3D geoinformation resulted in a cost-benefit ratio of 1:3.3 and an NPV after ten years of €8.9 million. Secondly, a case study was performed looking at an impact study in The Netherlands where high-resolution height data was published as open data some years back. The results of the Dutch study were compared with the cost-benefit potential of a similar high-resolution 3D digital terrain model in Denmark. The third method applied an adapted business case transfer from the USA’s National Enhanced Elevation Assessment to Belgium. The results of the latter two methods were similar to the Swiss one.
The EuroSDR study concludes: “The cost-benefit analysis in both urban planning and flood management demonstrated that benefits outstrip costs by a multiple of two to three times, even when considering each case in isolation. As further applications of 3D geoinformation are added, additional costs should rise more slowly, whilst benefits should accrue at a similar rate, thereby enhancing the overall rate of return.” The PMAs were very content, both with the study outcome and also with the opportunity to share knowledge about the challenges they face in convincing decision-makers to invest in this innovation.
Public value perspective
3D production and processing costs are approaching the same level as for 2D, but 3D innovations also require time and money to invest in technical infrastructure and in transforming business and operating models. In a climate of budgetary constraints, the economic feasibility of 3D innovation is “a point of consideration”, states the report. Accordingly, to further assist public-sector managers making the case for change, two academics involved in the EuroSDR study – Professor Jantien Stoter (TU Delft, The Netherlands, specialised in 3D and 4D geoinformation) and Professor Joep Crompvoets (KU Leuven, Belgium, specialised in national spatial data infrastructures), both of whom have intimate knowledge of PMAs – sought other means to complement the findings. They collaborated with Dr Serene Ho (KU Leuven, specialised in institutional aspects of geospatial innovation) to explore 3D geoinformation innovation from a public value perspective. Such a perspective on innovation explores the value of it from the users’ point of view. While acknowledging that traditional innovation ideals of effectiveness and efficiency matter, it draws attention to civic objectives like responsiveness to needs, liberty and participation, citizenship and transparency. Re-examining the data collected for the EuroSDR study, a qualitative analysis has been published as a scientific article (in Land, May 2018). It reveals that, in the authors’ experience, proving economic value is vital, but the creation of public value is equally or more significantly a driving factor for transformative innovation “as this conveys social and political currency”.
The article points out that moving towards a model where 3D geoinformation is the dominant data environment for PMAs will undoubtedly yield public value. 3D geoinformation enhances a government’s ability to protect its citizens’ quality of life by providing advanced analytical abilities that result in better living environments and avoiding damage to property. It improves the safety of emergency responders. It helps in planning and securing vital infrastructure. Also, it engenders greater trust in public organisations by fostering greater transparency, confidence and the ability to communicate decisions. The paper describes many examples from the 11 European countries.
Authoritative geodata custodians
Classification of the feedback from stakeholders demonstrates clear potential in financial and strategic aspects, mainly generated through mechanisms of improving the effectiveness of technical products (and, subsequently, various workflows and applications) and enhancing the data environment in which stakeholders operate. The potential for public value creation for PMAs could be even more significant, given the fundamental nature of cadastral data for all other development-related decision-making and the growing importance of sound urban planning. The authors conclude: “Innovation in 3D geoinformation would therefore likely consolidate and advance the PMAs’ position as authoritative geodata custodians and emphasise the role PMAs play in fostering secure and sustainable development. The move to 3D is a better way to meet the evolving nature and scale of their public mandate”.
“I have no doubt that 3D mapping is the near future in a fast-growing amount of applications,” says Jantien Stoter. Joep Crompvoets agrees – albeit a little reluctantly, because he also believes that many so-called new applications function fine, and more simply, with 2D data: “A decision-maker’s heart beats faster when they look at 3D visualisations, and this innovation is a logical evolution. So I agree that we will not get this genie back into the bottle again, although it comes at a price.” In their scientific article they refer to the economic value outcome of the EuroSDR study by stating: “The study found that such innovation was potentially a viable return on investment, perhaps even profitable.” This downplays the cost-benefit ratio of 1:3 actually presented in the study. Both professors explain: “We don’t want to give the impression that the financial benefits for the national or regional mapping organisation are always that manifest, let alone achieve a certain cost-benefit ratio. And it makes a big difference whether the investors’ perspective is aimed at obtaining benefits for the country as a whole, or whether the PMA has to sell the data to be profitable on its own. It certainly seems profitable, but the amount of scientific studies is too limited to be very specific. It is easier to prove that 3D geoinformation brings larger effectiveness of policies, processes and operating environments within and between governments and businesses.”
Back to the future
This has echoes of an earlier time, when digital mapping and GIS found their way from the American defence industry to the national mapping authorities worldwide. There were not many convincing cost-benefit studies proving GIS was profitable, yet the PMAs still had to make the switch because everybody could see that it made so many processes more effective and the technology was here to stay. Stoter and Crompvoets recognise many similarities. They add: “An important difference is that back then the transition was made easy because the initial costs of the national large-scale digital mapping and GIS revolution had largely been paid by the utilities sector. Now the demand is so fragmented that there is no focus for a shared business model.” Also, compared to the analogue way of working until then, GIS was a really disruptive technology; the market understood that serious investments and national coordination were needed. “But we passed the point of no return for the transition to 3D about five years ago,” states Jantien Stoter. “Since we can’t calculate the profit of new technology for new and currently unknown possibilities, we have to stop concentrating on the doubts. Look at examples such as Singapore and large cities in China or the PMA of Switzerland – they made the complete switch to 3D geoinformation and no longer want to be without it.” Joep Crompvoets outlines the plans for future research: “Our investigations will concentrate on how – and not whether – to make the change. We think that mapping of base data in 3D is the most efficient for a country when it is centralised, harmonised and quality controlled by the national mapping agencies. Which steps can be taken? Which priorities work best? And how should it be financed?”. His colleague concludes: “It is about the production of correct, up-to-date 3D data at different levels of detail for different applications, without every user group producing and paying for its own snapshot of reality. We’d better get going – back to the future!”
EuroSDR EuroSDR is a not-for-profit organisation linking national mapping and cadastral agencies with research institutes and universities in Europe for the purpose of applied research in spatial data provision, management and delivery. Joep Crompvoets is EuroSDR’s secretary-general and chairs the Business Models and Operation Commission. He is a professor of information management in the public sector, senior researcher/consultant and project manager at the Public Governance Institute of KU Leuven, Belgium. Jantien Stoter leads the EuroSDR 3D Special Interest Group. She is a professor of 3D geoinformation at The Netherlands’ TU Delft, Faculty of the Built Environment & Architecture. Prof Stoter also works as an innovation researcher at both Kadaster and Geonovum.
http://www.GIM-INTERNATIONAL.com Miércoles 10 de Octubre del 2018
3D city models have become common geospatial data assets for cities, and can be utilised for tasks including planning, visualisation and decision-making. The field of 3D city modelling is diverse, with a multitude of technical solutions. Even the definition of what constitutes a 3D city model still remains ambiguous. Yet, surprisingly few studies have focused on reviewing the existing activities and assembling the big picture. This article presents some of the key findings from a recent study reviewing major 3D city modelling activities in Finland.
3D city models can be seen as an enabler in the smart city paradigm, operating as a user interface to the modern urban environment and acting as a platform for cooperation and services. Therefore, a high degree of interoperability is expected from city models and from the information systems that host them. Also, 3D city models are expected to support a multitude of applications. This remains a challenging task, still hindered by many issues, such as ambiguities and differences in modelling, differences in perspectives, missing guidelines, challenges in data conversion and georeferencing, and problems in data quality.
Quest for data integration
Data integration is an inherent component in city modelling. 3D city models are commonly built through 3D reconstruction and data integration, by merging photogrammetry or laser scanning data with GIS data such as building footprints and IDs. Also, the use of highly detailed building information models (BIM) as a source of as-planned data remains a significant development topic. Another development direction is the integration of time series and sensor data to the objects in a city model. Rather than being static representations of the environment, inclusion of live data is turning city models into increasingly dynamic artefacts and towards the concept of a ‘digital twin’ of the city.
Expanding field of applications
The application space of 3D city models has expanded hand in hand with the technical development. In addition to the ‘traditional’ use cases in urban planning and zoning, 3D city models are expected to facilitate energy analysis, detailed architectural visualisation, interactive and immersive applications development, and participatory GIS. All this places challenging requirements on the platforms of the 3D city models.
The discussion on 3D city models is further complicated by the amount of different platforms used for 3D city model applications. In addition to the professional GIS/CAD tools, 3D city models are used on game engines and various web-based 3D viewers, such as virtual globes.
Reviewing the major 3D city modelling projects in Finland
In a recent study, the authors took a closer look at some of the 3D city modelling projects in the six largest cities in Finland, using project descriptions maintained by the cities to obtain an overview of the current activities. To support further understanding, local city representatives in the studied cities were interviewed. A summary of the analysed projects is presented in Table 1.
Excess of platforms
Firstly, the studied 3D city models utilised a great variety of platforms. In the 19 studied projects, a total of 13 different platforms were discovered for hosting the models. These included GIS/CAD software (e.g. Trimble Locus and Bentley Microstation), virtual globes (e.g. Cesium, CityPlanner, Sova3D, MAPGETS) and game engines (e.g. Unity, Unreal Engine). Some of the software solutions applied in Finland were more or less unique and have not seen wide adoption globally.
Secondly, the authors noted that in each studied city the maintenance and upkeep of the 3D city models was tied to the statutory base mapping process that heavily relies on the chosen GIS/CAD software. In many cases, the 3D model data maintained by the city itself was used as an input or reference data for virtual globes and 3D game engine-based projects, which focused on specific applications often aimed at broader audiences.
Data quality and accessibility
The studied 3D city modelling projects contained a variety of different levels of detail, ranging from simple block models to highly photorealistic models containing facades modelled in great detail. Fewer than half of the models utilised as-planned information such as BIM or architectural plans. More than half of the city models covered the full regional area of the city.
In addition to data quality, accessibility plays a vital role in 3D city modelling, especially when models are to be used as a basis for developing new applications. Almost two-thirds of the studied city models could be freely viewed via a web-based viewer. This was realised either via separate viewer utility or, in the case of virtual globes, natively by the platform itself. More than half of the city models studied were offered for download over the internet. However, none of the cities offered any original raw data such as Lidar point clouds. This hinders possibilities to freely edit the models or to run additional analysis.
The ideal of a general model
Producing and maintaining a 3D city model requires an interplay of several technical solutions and stakeholders, both of which vary from project to project. Many of the studied cases were likely to serve only a limited number of purposes or to pilot 3D modelling in a limited area. However, the interviews showed that this had not been the original intention in the cities. On the contrary, the common vision was close to the ideal of 3D city models serving as general platforms, including the capability to re-use the gathered data and models.
Further, an increased degree of realism in visualisations, attained with 3D models, was seen as a key element in enhancing the interaction and trust between different stakeholders. This includes the notion of demonstrating impact as well as including all relevant stakeholders in the co-design and decision-making processes.
Stakeholders inside and outside city organisations are a heterogeneous group of users that have varying needs, expectations and views of 3D city modelling. The city interviewees stated that up-to-date guidelines and policies were missing or that the existing guidelines were not followed. Ambiguous terminology, lack of coordination and leadership, and the slow adaptation of standards frequently crippled communication and collaboration. Additionally, the lack of expertise was said to result in an incapacity to recognise the need for 3D city modelling and hence to define the requirements for the modelling projects.
Understanding the big picture
By looking at the characteristics of the studied 3D city modelling projects and literature, it was possible to identify three partially overlapping operational cultures in the 3D city modelling scene: 3D GIS, BIM, and computer graphics. Each of these operational cultures (Figure 2) has a unique perspective on 3D city modelling and they often lead to differing realisations (Table 2).
In the 3D GIS category, the modelling projects typically have a large regional coverage but a limited level of detail in 3D reconstruction. Further, the role of semantic data and connection to the existing city GIS data is emphasised over mere geometric reconstruction. Most of the applications focus on professional uses like city planning, mapping and various geospatial analysis. Projects in the BIM category focus on integrating as-planned data from individual buildings to models of limited regions. Understandably, aspects like model conversion and inclusion of interiors are pronounced. Typical applications in this category include urban planning, building permit processes and architectural visualisation. The projects in the computer graphics category are based on game engines, offering the highest level of photorealism facilitated by advanced real-time rendering. At the same time, models are typically limited to local coordinate systems and they rarely utilise semantic information. Also, the 3D game engine-based models have a clear emphasis on game-like interaction and immersion, with the goal of engaging users to collaborate in and explore the models, even on a pedestrian level.
In the big picture, 3D city modelling is revealed to be a diverse and multidisciplinary field with steadily increasing interest and demand. It is often accompanied with visions of a high degree of interoperability and platform-like characteristics. However, when reviewing the modelling activities more closely, they appear fragmented and fail to reach the broad applicability envisioned.
This is, to some extent, explained by the complexity of the situation. Modelling projects are carried out by people from different fields, using varying tools and aiming for different outcomes. Further, the future uses for 3D city models can be hard to predict – and not only because the user group is heterogeneous with different levels and types of expertise. As an outcome, the quest for a single, completely harmonised 3D city model becomes demanding and laborious. Improving the interplay and communication between people and technologies across these three operational cultures is a key element in advancing the interoperability and creating flexible, demand-driven 3D city models of the future.
Julin, A., Jaalama, K., Virtanen, J. P., Pouke, M., Ylipulli, J., Vaaja, M., Hyyppä, J., & Hyyppä, H. (2018). Characterizing 3D City Modeling Projects: Towards a Harmonized Interoperable System. ISPRS International Journal of Geo-Information, 7(2), 55. https://doi.org/10.3390/ijgi7020055
http://www.GIM-INTERNATIONAL.com Miércoles 10 de Octubre del 2018
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