eight emerging geospatial technologies

Eight emerging geospatial technologies

Future Technologies Review Geospatial ReportAccording to the ‘Geospatial Readiness Index’, the UK’s geospatial technology sector is recognised as the second most developed in the world, behind the US.

A report funded by the Geospatial Commission highlights eight emerging technologies in the geospatial sector, including Artificial Intelligence, 3D scanners, and immersive technologies. The report analyses commercial opportunities, the maturity of each technology in the UK, and provides case studies.

Here’s an edited extract

1. Cameras, images and sensing

There’s been development and widespread adoption of new platforms for collecting Earth Observation, EO, data, including satellites and drones. This has resulted in greater coverage across satellite constellations, more accurate targeting, and significant improvements in the resolution and accuracy of cameras and sensors. Improved EO capabilities is crucial for sectors such as infrastructure, asset management and agriculture. The combination of aerial imagery with other map data and land use data, will allow a deeper and more nuanced understanding of urban environments, enabling highly accurate 3D models.

  • Getmapping and Bluesky International have both developed products that combine multiple datasets with aerial imagery to gain better understanding of a given locations. Bluesky recently invested in the Leica CityMapper, the world’s first hybrid airborne sensor combining vertical and oblique imagery together with 3D laser scanning, in order to capture major cities throughout the UK
  • Vehicle sensors are becoming increasingly common, with multiple public and private sector organisations undertaking vehicle drive-by imaging and mapping surveys. These projects are being used for a wide range of applications, including asset management, 3D city modelling, and utility surveys

Satellite Image 1

2. Unmanned vehicle systems and drones

There are three areas of major geospatial interest relating to drones. Drones are being used as an aerial platform for EO and mapping projects, as well as delivery systems for lightweight packages, postal services and medicines. Most recently, they  are being developed to carry and transport passengers within urban areas.

  • Drones are also increasingly being used to support the monitoring and inspection of the condition of energy distribution assets and networks across the UK. Many of these inspections are beginning to leverage Computer Vision to recognise images of infrastructural assets, to identify different types of faults and anomalies. Since 2018, EY has been running a number of pilots in Paris relating to the use of autonomous drones to inspect faults in solar panels
  • Significant research is also underway to develop future swarm capabilities in command and control systems. Drone swarms are groups of drones that capable of being programmed to perform a set mission or action. Swarms will become increasingly applied to the monitoring of urban infrastructure, to rapidly monitor and assess the progress of construction and development projects
  • Over the next ten years, we should expect to see the use of drones to extend from EO, mapping and monitoring into the domains of parcel and passenger delivery. For the geospatial community, the primary goal will be to provide first and last mile geospatial reference and navigation data to support these systems


3. Security, measurement and scanning

The geospatial community will continue to see the introduction of efficiencies to the existing surveying and measurement processes, which will have a positive impact on cost, time and on-site health and safety. More accurate and precise positioning systems are central for the operation of complex sensors systems at scale, such as IoT systems, where connected devices collect and communicate location intelligence by transmitting signals in real-time.

  • Geospatial technologies are harnessing multiple Global Navigation Satellite Systems, GNSS, sources to support navigation and tracking, including for intelligent transport systems
  • Simultaneous Location and Mapping, or SLAM, enables a user or autonomous device to create a dynamic map to navigate complex environments in real-time. SLAM makes the remote creation of data possible in situations where the environment is too dangerous, or small, for humans to map themselves. In many factories and fulfilment centres, autonomous devices are using this technology to recognise features such as shelving units and the travel paths of other robots
  • LiDAR is a well-established geospatial technology that involves using pulses of light to capture and model a feature or an area environment in three dimensions. LiDAR can be applied across multiple sectors and requirements, including mapping an industrial site in granular detail, providing ground model data for flood modelling, and providing the spatial context for developing immersive environments


4. Artificial Intelligence

AI techniques have largely been used by the geospatial community to analyse ‘structured’ geospatial datasets. These datasets tend to be quantitative, easily grouped and stored in spreadsheets or other kinds of traditional databases. ‘Unstructured’ data, can be more qualitative and potentially difficult to store and analyse. Examples include video footage, such as satellite video imagery and CCTV footage, as well as speech and natural language data.

  • Earth Observation technologies routinely apply image processing and classification techniques to interpret and map landscapes and features of interest. More recently, the industry has been able to apply change detection algorithms to automatically identify areas of change, including urban development or to support damage assessment mapping following a disaster event
  • Ryelore Ai, is developing Deep Learning algorithms capable of detecting patterns in satellite imagery, to support financial institutions to make better investment decisions.
  • Urban Intelligence has a built an AI system which aims to provide a ‘credit score’ for plots of land, based on their suitability for development
  • In the field of location intelligence, by processing millions of GPS points in real-time, systems are able to forecast changing road and traffic conditions for truckers and hauliers
Ryelore Ai

Ryelore Ai detects patterns in satellite imagery, to support financial institutions in making better investment decisions

5. Smart sensors and IoT

Perhaps the most highly anticipated use of geospatial technologies and sensors is in the ‘smart city’ domain. Smart City applications rely on an integrated IoT network of devices across a set of different services and businesses.

  • CityPulse has been running trial projects in Aarhus, Denmark to deliver a route planning system that is capable of providing drivers with real-time analytics of road conditions. These advances are attempting to tackle issues of congestion, pollution and energy consumption by using location-enabled technologies
  • Urban Hawk collates and consolidates data collected from multiple geolocated and timestamped sensors and public sector datasets to monitor the security and resilience of assets in urban areas
  • TravelAI analyses crowdsourced data to provide cities with data and insights about how its residents use transportation infrastructure. It has worked with cities such as Leeds, Newcastle and Oxford
  • One geospatial startup, Energeo, is working to support the roll-out of smart grids, utilising geospatial technologies to assist the management of geolocated charging stations for electric cars
  • Smart dust is a new sensor type that offers the potential for blanket monitoring and surveillance of an area. These sensors can be as small as a grain of sand and can remain suspended in an environment like a particle of dust. They can be equipped with GPS in order to provide a locational aspect to their measurements

EV Charging

6. Immersive technologies

Any level of geospatial detail can be presented within an immersive reality, from a skeleton geometry in 3D, through to an Intelligent Point Cloud which updates as a real-time digital representation of a building. Some GIS technologies are also becoming integrated with immersive systems, and we are starting to see the early adoption of these solutions in certain niche sectors.

  • Trimble is an example of a well-established geospatial technology company that has recently broken into the field of immersive technologies. Trimble’s solution presents a Mixed Reality for site workers, providing precise alignment of visual data from the planning process and the actual physical environment that construction teams are working in. This enables workers to review their models while overlaying them in the context of the real world, leading to significant time and cost savings as well as on site health and safety benefits

7. Simulation

3D Modelling is now a commonplace service offered by geospatial companies. We expect these 3D requirements will continue to grow as the emerging technologies in this area mature, and as user communities begin to increasingly apply 3D systems to support their business operations and decision making.

  • With advances in AI and Machine Learning, multidimensional modelling and simulation will improve maintenance and decision-making processes for organisations. The UK has ongoing programmes involving these techniques for flood-risk modelling and simulation, air pollution modelling and environmental noise mapping
  • GIS technologies also offer a number of benefits for modelling facility management scenarios, including space management, visualisation and planning. Facility operating systems, which manage large operations such as airports, industrial and power plants will be the main beneficiaries of such developments. Increasingly, Smart Cities will coordinate these systems with smart sensor capabilities which will model and simulate urban planning. Fields such as construction and development are also increasingly adopting continual sensor monitoring and reporting on assets

8. Connectivity

In addition to the ongoing investments to achieve full fibre wide and local area networks, going forward, the single largest game-changer in geospatial connectivity is likely to be 5G. 5G technologies use existing and high-frequency spectrums, enabling rapid data transfer speeds, making it easier to download and upload on mobile devices. Where 5G networks are deployed, they will build on and add to the foundation created by previous mobile generations, as part of a wider ecosystem of mobile connectivity.

  • Small and miniaturised satellite constellations, such as those operated by OneWeb, will present new global network and communications opportunities. These emerging high-capacity and fast communications channels will enable geospatial data to be transferred at volume, at speed and securely
  • Considering all UK network investments collectively, we should anticipate that our motorways and main rail routes will have enhanced connectivity by 2025 along with our major towns and cities
  • The reduced latency, the time it takes to transfer data, of 5G technology will be crucial to the future adoption of autonomous vehicles and drones. This is because autonomous vehicles require extremely fast networks with no delay or lag to operate without fault. This reduced latency will also better support the effective streaming of real-time imaging data on the move, as well as continuous sensor availability to support spatial analysis at scale in real-time
  • Constant and secure connectivity will also be crucial for drones and other unmanned vehicles when performing missions covering large land areas, including surveying, mapping and the monitoring of energy grids

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Still early days with most of this, so much potential

By Anonymous

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