History is replete with disruptions, some catastrophic, others beneficial in the long run. Will geospatial DNA of digital transformation ensure a better world?
The digital transformation of the world is moving apace as digital devices become ubiquitous. Today, every object from the car you drive to the smartphone in your pocket has an element of digitization inbuilt. While a self-driving car is the ultimate in digitization, even the humble family jalopy has digital electronics monitoring various engine parameters and even your driving. Similarly, that smartphone in your pocket is not just a telephone but does more than your average desktop. A spinoff of this is the growth of electronic networks, particularly the Internet. Combined with the smartphone this enables an experience, which was in yesteryears, was available only on Dan Dare comics. Smart devices and the internet connect humans and machines together in a dynamic fabric.
The dynamic nature depends to a large extent on location. Take the example of the self-driving cars. This is an excellent example of a machine interacting with other machines, and humans in a dynamic environment in which location plays a crucial role. In smart farms we have an example of interaction between machines, human and other living objects which cover precision farming and animal tracking using RFID to name a few. The success of the Internet of Things is closely dependent on location. Thus the larger field of ICT needs geospatial systems to provide the all-important location information. Unique digital solutions for dynamic solutions need unique applications of geospatial systems.
In life, the uniqueness of living systems is decided by their DNA. Like the DNA double helix strands, which have four connectors, cytosine, guanine, adenine and thymine in millions of combinations, we may consider the geospatial DNA to have four ‘connectors’ namely Platform, Data, Storage and Software, which can be combined in many ways to deliver unique solutions.
Platform and data
Data acquisition systems have grown rapidly thanks to innovative use of miniaturized hardware. Today EOS small satellite swarms provide hourly global coverage. With resolution in the range of a few meters, these satellites provide detailed imagery and video of each and every part of the globe. For example, recently a Chinese video satellite Jilin-1 orbiting at around 535 km above Earth live recorded the launch of the OS-X1 rocket as it lifted off from Jiuquan at 12:10 local time live, demonstrating the power of remote sensing far beyond what we have been used to. Such power is being used for many dynamic applications like tracking of ships and vehicles and monitoring of Earth events like storms, accidents and unusually large gathering of people which have a direct impact on safety and security.
Closer to Earth, remotely piloted aircraft systems, familiarly referred to as drones, are gaining acceptance as country after country are issuing regulations for their use. Drones can carry payloads ranging from digital precision still cameras to video cameras to SAR and LiDAR, all thanks to miniaturized electronics. Such drones are being used to provide 3D scans of buildings and other structures that can be integrated with BIM and GIS to provide near real-time data on dynamic activities. Drones provide that extra service, which is needed when cloud cover obstructs satellite imaging sensors or when high-resolution data is needed or when real-time data is needed.
Another advance in sensor technology are in situ sensors and implantable sensors. In situ sensors, for example, we monitor the Earth’s crustal movements and automatically feed the data to a central computer for further analysis and possibly, earthquake early warning. GPS-enabled sensors with transmitters are used to monitor wildlife and research on their activity. Richard Attenborough’s Blue Planet II used this technology to unravel many secrets like the spawning ground of Blue whales. A National Geographic investigation used this technology to track illegal trade routes of ivory using GPS tracker and transmitter implanted in a fake tusk. RFID sensor implants are used to track livestock, certify the authenticity of medicines, detect stolen cars. Self-driven cars use an array of sensors, which help to navigate public roads and highways. Finally, the Internet of Things is driven by sensors of various types which enable smart homes, smart cities, smart manufacturing and smart healthcare to name a few.
The users are spoilt for data. Considering the number of national and commercial satellite systems producing terabytes of data, the rising popularity of drones and the
proliferation of sensors, enough and more data is now available not only for traditional use in monitoring and management of natural resources but for many commercial applications. Though the use is presently dominated by national governments, by 2025 it is expected that the demand from commercial users will equal and then perhaps exceed the governmental demand.
Other moves that have accelerated data use are GEO initiative, Radiant.Earth, government institutions and some commercial initiatives. The Group on Earth Observations champions the move to Open Data. Its Founder-Chair, Barbara Ryan had earlier made Landsat data freely downloadable when she was with the US Government. GEO encourages satellite operators to make their data available for free to stimulate data usage, particularly for humanitarian activities. ESA has made Sentinel data freely downloadable right from the start of the program thus encouraging, both academic, government and commercial users.
The Radiant Earth Foundation is a not-for-profit initiative following the GEO initiative by creating a database of Open Data. Other data resources including drone data is accessible provided the user has the relevant license. The database is made available for analysis using tools provided by Radiant.Earth or by the users. This is a classic case of Data as a Service, and Applications as a Service. Similar initiatives are ISRO’s Bhuvan and NASA’s WorldWind, which are completely free. Esri’s ArcGIS Online is an initiative in the commercial world based on a subscription model.
Storage and software
The flood of data creates new problems of data storage and analysis. NASA, Radiant.Earth, ArcGIS Online and many other spatial data providers like Pitney Bowes Software & Data Marketplace and Planet use the Cloud to store data and provide access to data and analytics through APIs. However, this presupposes that the user has a stable, reliable and ‘always on’ connectivity to the Internet. Unfortunately, this is not the case in countries where such data is required the most. Thus, Bhuvan uses a distributed server model and allows download of data as per Indian security regulations and analytics support based on OGC Web Map Services.
Apart from spatial data there are several other data sources, which have an implicit spatial content like transactions, social media and socioeconomic parameters. Solutions for real-life issues need to use a variety of data sets in an analytic environment that goes beyond just image processing and GIS. Data science is a new branch of research that has come into focus. Big Data Analytics is one of the branches of data science, which enables insights culled from the data streams. Other techniques, which have emerged are artificial intelligence, machine learning and deep learning. These are not independent modules but are interrelated. AI can be considered as the mother technology that has spawned machine learning. Deep learning is a subset of machine learning, which uses BDA insights to train a deep neural network to do predictive analysis.
Other techniques related to the visualization of the analysis and spatially oriented smart contracts. Two important elements of visualization are augmented reality and virtual reality, which can create virtual worlds which can be viewed from the outside (Augmented Reality) or in an immersive environment (Virtual Reality). The blockchain is a new technology, which can tie up spatial analytics with smart contracts to enable reliable and assured transactions in the geospatial space.
Solutions using geospatial building blocks
Real-life issues like sustainable development, environmental management, climate change, infrastructure management, city management, business management, defense and security are all potential beneficiaries of digital transformation. Extending the DNA analogy we can consider solutions as composed of unique combinations of basic geospatial connectors with image processing, GIS, location on one side and subject-specific software like Business Intelligence, Building Information Management, power distribution, land records management and process management on the other.
The continuum of digital transformation has traversed through several industrial revolutions and currently, the hype is all about Industrial Revolution 4.0 which seeks “dynamic new combinations between technology, market, and society through open Innovation” (Journal of Open Innovation, Technology, Market, and Complexity, 2018, Vol 4, page 21). The key factor is society. 4IR seeks to bring about a merger of cyber and physical worlds to serve society and individuals. Though termed as ‘Industrial’ the socio-economic impact will be felt by society, government, industry and individuals in that order (See Graph 1 and Graph 2 ).
A glance at the sustainable development goals shows that these have a significant geographical context and the requisite analysis, modeling and mapping can provide valuable inputs to the overall management and monitoring of resources (See Graph 3).
PwC in a study on “Fourth Industrial Revolution for the Earth Harnessing Artificial Intelligence for the Earth” have listed the major areas of applications as climate change, biodiversity and conservation, healthy oceans, water security, clean air and weather and disaster resilience. Each of these areas has a strong geospatial content which when combined with other data and techniques can provide meaningful solutions. The study identifies the game changers, which can impact the Earth and humanity as a whole. These are autonomous and connected electric vehicles, distributed energy grids, smart agriculture, weather forecasting and climate modeling, community disaster response data and analytics platform, decentralized water systems, AI-designed intelligent, connected and livable cities, oceans data platform and Earth Bank of Codes for traditional information.
Dangers and pitfalls
As in any system, there are dangers and risks, which must be kept in mind. Such risks may include poor performance, security breaches at individual and collective levels, ethical risks, rogue operations, widening the have and have-not gap and economic risks. In a comment in Nature, Joshua Blumenstock outlines the possibility of Big Data ignoring the people for whom the analytics is intended. He writes, “algorithmic transparency, fairness and accountability are off the radar of most companies operating in developing countries” which can lead to invasion of privacy. There is a need to validate and customize data and collaborate with local entities. In his view “the successful use of Big Data in development requires a version of data science that is considerably more humble than the one that has captured the popular imagination.”
Digital transformation is gaining momentum. The benefits of going digital are numerous, however, just like any new terrain, we need to traverse it carefully. The digital technologies have huge potential for facilitating more informed decisions, but preparedness is necessary for effective adoption.