On 27th September 2019, Geospatial Advocacy Kenya had its inaugural meetup under the theme “Shifting Paradigms in Geospatial Technology”. This theme was coined in reference to the opportunities and challenges brought about by the Fourth Industrial Revolution (4IR).
4IR is driven by a convergence of emerging technologies like Artificial Intelligence (AI), blockchain, Virtual Reality (VR), robotics, and Internet of Things (IoT). Collectively they are transforming how we live and work in a drastic manner. Though a more connected and automated world will lead to overall gains in efficiency and productivity, it is expected to increase inequalities and disrupt labor markets. On this notion, it is important that the geospatial industry in Kenya finds out how it can leverage the opportunities and overcome the challenges.
Change starts in the mind, so the geospatial industry will have to abandon old paradigms and adopt new ones to thrive in a world transformed by 4IR. The two paradigms that need to be challenged most are the notion that (geo)spatial is special, and its obsession with mapmaking.
Geospatial = Special – Working with spatial data still has its own peculiarities, but the geospatial industry can’t isolate itself from technology convergence around. It also needs to integrate its sub-sectors to make a compelling value proposition for the use of geospatial data, analytics, and visualization.
Geospatial = Mapping – Mercator mapped the world, John Snow mapped the source of a Cholera outbreak, and Google Maps helps us not to get lost. But to stay relevant, the geospatial industry will have to provide location insights for action and decision-making rather than make pretty maps that nobody uses.
A discussion on paradigms can turn into a war of ideologies since we are influenced by our own interests, perspectives, and experiences. So let us consider the drivers behind these shifts before discussing two new paradigms towards the end of this article.
Technology drivers are technology advancements and innovations that are pushing industry growth from the supply side. The following drivers will be discussed in detail:
- Cloud Computing
- AI and Data Science
- Big Data and IoT
- AR/VR and 3D
In addition, we’ll consider the following needs and preferences from the consumers that are generating and driving the demand for geospatial services:
- Subscription payments
- Open and free software and data
- End-to-end solutions
- UI/UX design
Cloud Computing – Cloud computing was popularized when Amazon introduced Elastic Compute Cloud in 2006 and continues to experience unprecedented growth. It offers immense scalability through parallel computing and cloud services which can be accessed anytime and anywhere through an internet-enabled device.
Some geospatial solutions are already entirely cloud-based, while others rely on the cloud for data storage, computing, and dissemination of geo-information via geo-portals and web maps.
Artificial Intelligence (AI) & Data Science – AI refers to a wide range of algorithms and computing operations used to automate processes and extract patterns and relationships from large amounts of structured and unstructured data. Data science is often used in the same breath, but it refers to the concepts, principles, and methods used to derive new insights from existing data.
Within the geospatial industry, AI is used to identify/classify satellite imagery, automate workflows, and build explanatory/predictive models for spatial distributions.
Big Data & Internet of Things (IoT) – Big data is used to describe extremely large datasets that are analyzed computationally to reveal patterns and trends. Due to the volume and veracity of the data, it relies on cloud computing for storage and processing. Purists could argue that data science is big data science, but the two disciplines now have their own proponents. IoT is arguably a form of big data that is collected, transmitted, and processed in real time by sensors that can measure almost anything (e.g. temperature, air quality).
The geospatial industry has long used big data in the form of satellite imagery, but satellite imagery archives have now grown to terabytes of data. These archives can be analyzed to understand dynamic processes such as land-use changes. By tracking moving devices through GPS data streams the geospatial industry used IoT before the term was even coined. The industry is therefore well placed to carry out spatial-temporal analysis to make sense out of the increasing stores of IoT data.
Augmented Reality (AR), Virtual Reality (VR) & 3D – AR and VR rely on the use of 3D combined with high-resolution satellite imagery or textures and perhaps IoT data to provide an immersive user experience. While AR augments the real world by what showing the invisible (e.g. underground infrastructure, administrative boundaries), VR shows a non-real or future world with the addition of planned buildings or the outcome of planning scenarios.
AR/VR has wide application in the geospatial industry since it helps us to see the world as it is and how we design it to be. 3D GIS/geospatial applications are fast emerging, but they might still require specialized hardware. Even the more common 2D applications are becoming more immersive with faster display, dynamic content, and increased user interaction (e.g. pop-ups, navigation, layer control).
The growth of the geospatial industry has largely been driven by technology innovations and demand from major markets like defense & security, AEC (Architecture, Engineering & Construction) and urban management. Purchasing decisions are increasingly made online and influenced by end-users. Here are some of the buying needs and preferences that service providers in the geospatial industry will have to consider.
Subscription payments – With the advent of cloud services organizations increasingly adopt subscription payments over ownership of IT infrastructure and applications. Subscriptions give them the flexibility to pay for what they need or use rather than invest in what they own. It removes the burden of maintaining and scaling their own infrastructure, which is an arduous task due to spikes in demand. Subscription payments are treated as operating expenditure (OpEx) rather than capital expenditure (CapEx), making it easier for accountants to assess their cost-effectiveness in the organization.
Open and free software and data – Free and Open Source Software (FOSS) has come of age and is now able to compete with proprietary software solutions (e.g. ArcGIS Desktop vs. QGIS) As a result, individuals and organizations are unwilling to pay hefty license fees unless it offers direct and measurable benefits. Software vendors might need to adjust their pricing models and perhaps offer a free entry-level package with basic functionality.
Like FOSS, open data has the power to bring geospatial technology to a much wider audience with free access to all manner of authoritative and crowdsourced spatial data (e.g. demographics, physiography, utilities). The biggest drawback currently is that spatial data can be hard to find, difficult to access, and is provided in formats that are not machine-readable (e.g. pdf). A case in point is Kenya’s open data initiative (KODI) which has no spatial data whatsoever.
End-to-end solutions – Customers expect end-to-end solutions that address their business problems and are less willing to build solutions in-house by integrating different technologies. Changes are that they aren’t specifically looking for a geospatial solution, but a business / IT solution that might have a geospatial component built into it. This will be quite a challenge for geospatial service providers who view the world as a big map, but geospatial technology is already finding its way into data engineering, data science, and Business Intelligence (BI).
User Interface / User Experience (UI/UX) design – This is also referred to as the mobile app revolution since most people interact with the world through their mobile phones. Not all geospatial solutions scale well to a mobile phone so they could be delivered as web apps that are accessed on desktops and tablets. UI/UX design is critical since apps need to be built with the user experience in mind. This means that an app has good performance, is intuitive to use, and interacts with the user. Geospatial apps haven’t always had good UI/UX design, but this is changing as exemplified by immersive story maps and interactive geospatial dashboards.
Paradigm shifts are not easy to notice, so for that reason, we took time discussing the drivers that are affecting the geospatial industry. We can observe these drivers as early-warning indicators of impending change. Nonetheless, the following shifts are slowly but surely taking place.
Industry Convergence – Mergers, acquisitions, and partnerships are the most telling signs of industry convergence and consolidation. The debate on whether GIS is dead or alive might not go away soon, but drawing boundaries between surveying, earth observation, and GIS/geo-analytics is becoming increasingly difficult. The different sub-sectors all gather, manage, process, and disseminate spatial data and as a geospatial industry, they constitute a powerful value chain.
Data Pipelines / Connected Workflows – Traditional GIS/geospatial workflows are disconnected and project-based with a (web) map as the main deliverable. Increasingly organizations want to adopt seamless and integrated workflows to provide insights for action and decision-making. These insights can be published on a dashboard, obtained through an algorithm, or delivered as an interactive app. Data pipelines will have to connect to live data streams if they are expected to deliver insights in near real-time. While traditional maps are largely qualitative (colors on a map), these novel applications are expected to provide quantitative and statistical information.
In the September meetup, we had a welcome address from Geospatial Advocacy Kenya (GAK) and user presentations from KenGen and Gro Intelligence. The GAK address identified geospatial as an umbrella term that represents different technologies (e.g. remote sensing, GIS, surveying) and multiple sectors. It called upon the different sectors to recognize and play its unique role in growing the geospatial industry in Kenya.
The KenGen presentation highlighted the application of geospatial technology for geothermal resource development during the exploration, drilling, and steam gathering phases. These applications are largely project-driven, but KenGen has recognized the need for integrating their geospatial data with other data for better decision-making.
Gro Intelligence seeks to bridge the data gap in agriculture by building a comprehensive agricultural data platform. It uses a data pipeline to convert data from disparate sources to build a single repository of agricultural data in a reusable format. The data can be accessed through an API for further processing and visualization. Geospatial technology plays a critical role in deriving, geo-referencing and disseminating Gro Intelligence’s data products.
To some extent, these two user stories represent the old and the new paradigm, but both are great examples of digital transformation. Regardless of whether we build on past successes or disruptively innovate, geospatial technology will play a key role once we recognize its potential in the context of our own individual and institutional goals and objectives.