Making a city resilient in the face of natural disasters is a decade’s work. Geospatial Intelligence is here to help.
As we are preparing for our first in a series of Geospatial Innovation Cycles, where we bring geospatial insights within key industry verticals, Luca Budello reflects on how Geospatial Intelligence can help with building long-term resilience in cities.
For a little while, urban resilience has been an important yet complex topic.
Resilience involves not only prepping cities to better respond to natural disasters, but also taking steps to prevent them. Some catastrophes caused by seemingly natural disasters are only partially the result of natural causes; they are also the result of failed urban planning and lack of maintenance. This situation places the responsibility of minimising the risk of natural catastrophes in the hands of city planners, lawmakers and the local population.
Acknowledging the ageing infrastructure and repurposing it to face the challenges of creating cities that are smart, sustainable and future-proofed is a primary challenge of resilience. This concern has become an even more pressing issue in the era of climate change, when much of that infrastructure is endangered by extreme weather conditions or the need to become fit for a sustainable low carbon future.
Making a city resilient is a decade’s work. While cities do not have the luxury of fixing major urban challenges in a short span of time, there is certainly a need for increased investment in single infrastructure initiatives that address multiple challenges in one go.
Whether we pursue physical resilience in the face of natural hazards, or economic resilience in the face of uncertain times, urban resilience requires an unprecedented level of coordination and collaboration between different levels of government, industries and humanitarian organisations.
Ushering in Geospatial Technologies
In the digital era, geospatial technologies are revolutionising the economy. From navigating public transport to monitoring supply chains and designing efficient distribution paths, location-based digital services, Earth Observation data and the insights that can be derived from the ‘where’ dimension in a digital space has seen an exponential growth in the volume of spatial information.
From smartphones to satellite sensors, from ground penetrating radars to immersive and 3D technologies, from LiDAR to Building Information Modelling (BIM) and machine learning, the level of ubiquity at which geospatial data is being incorporated into building & maintaining infrastructure practices is growing rapidly.
Geospatial data working in synergy with machine learning and other emerging technologies is becoming the enabling factor that helps to build better, smarter, more sustainable and efficient cities. Let’s have a look at some these technologies and their impact on society.
Drones for Infrastructure
Operating at height is not the only threat for officials. They can also come into contact with toxic substances and pollutants, running vehicles, or traffic speeding and high-voltage machinery. When an asset is in poor condition these risks intensify. High-resolution images, thermal imaging, landscape maps, 3D models, LiDAR cloud points, volumetrics — unmanned aerial vehicles (UAVs) can collect this broad range of data, often in (almost) real-time and make it available for analysis.
In the US, drones are now used for bridge, pavement, and light-pole inspections, as well as for gathering aerial views of highway constructions in progress. Drones deliver much better data about what’s going on, without requiring inspectors to climb to heights, go up in a bucket truck or be in close proximity to speeding traffic. One study found drones could detect cracks in concrete bridges as low as 0.02 inches, even in low-light conditions.
AI-powered UAV mapping provides devices with revolutionary ways of observing and understanding the world. Efficient capabilities for geographic and location-based data collection, evaluation and estimation result in great benefits for the infrastructure sector.
Furthermore, Geospatial AI (GeoAI) has the potential to:
- increase the efficiency of the supply chains
- maximize customer service
- improve land survey and infrastructure evaluation strategies
- make a significant contribution to disaster aid and mitigation.
All of this contributes to cost reduction, productivity increases, and the achievement of targets related to decarbonising the construction and infrastructure industry, making it more sustainable.
Building Information Modelling (BIM) for the Win
Through improved mapping tools and photos of Earth, the plethora of information that is easily accessible for the maintenance of infrastructure has increased tremendously. Today, when a new project is launched it often involves acquiring geospatial data -from point clouds to digital elevation – effectively documenting reality while simplifying procedures.
BIM can help with building complete 3D representations of real infrastructures, which in turn can help capture vital information about subsidence and risk of damage; this may be, for example, the cause of work stoppages. Monitoring infrastructure through the use of BIM can ensure that work doesn’t stop unnecessarily.
Digital Twins, the New Buzzword
A digital twin is a digital representation of a physical asset, process or system that enables users to visualise it, check its status, perform analysis and generate insights in order to predict and optimize asset performance. Digital twins are continuously updated with data from multiple sources – which is what makes them different from static, 3D models – making it the next major thing in the infrastructure industries.
Bentley Systems for example, has helped the city of Lisbon shift from a reactive to a proactive mindset, by implementing a digital twin framework to monitor and mitigate the flood risks expected due to climate change.
The rising ocean and repeated heavy rain have elevated the risk of flooding; due to the heavily built urban environment, flood occurrences have increased and became more damaging. As the current city infrastructure does not allow the monitoring of optimal drainage systems, , the city of Lisbon generated a virtual twin that helps them simulate alternative scenarios extensively, drawing up plans to mitigate the risks associated with flooding. This virtual twin enables Lisbon to build infrastructure resilience within the city mesh, saving millions on potential damage costs and possibly lives.
An Eye in the Sky
In the aftermath of the Morandi Bridge collapse in Genova in August 2018, which killed 43 people and left 600 homeless, a consortia of scientists in the USA, Italy and the UK (Milillo et al. 2019) has shown that it is possible to assess potential pre-failure clues of critical infrastructures based on Interferometric Synthetic Aperture Radar (InSAR) observations.
Asset managers require liable and long-term monitoring of the performance and condition of their assets, in order to maximize their operation and utilisation, while preventing potential catastrophic collapses.
InSAR can measure deformation in near real-time, which can help engineers to spot structural issues and prevent failures before it is too late. As pointed in this post by Thomas Beaton, Senior Earth Observation Engineer at Telespazio Vega UK, by combining 3D Building Information Modelling (BIM) with satellite-derived Interferometric Synthetic Aperture Radar (InSAR) survey measurements, it is possible to visualise structural movement dynamics for preventative maintenance purposes.
Accurate geospatial information is helping immensely and will continue to help policymakers, international agencies and civil society have greater insight into the allocation of needs and ways of optimising construction planning, maintenance, expenditure and the development of better initiatives. A deeper understanding and management of location-based data and facilities integrated with infrastructure planning and other sources of information– such as population data, smartphone data, surveys, and organizational data – can enable more optimal distribution of resources for smarter service delivery, and also make the infrastructure we already have more resilient for the future.