Leveraging new technologies for mapping and data generation

Since its inception in the 1960s, GIS has come a long way, especially in the past decade or so. While a lot of industries didn't even know of its existence let alone its application for the decision-making process – fast forward to now, GIS has managed to revolutionise most sectors, such as real estate, disaster management, retail, marketing, etc.

With all the advancements in technology, it continues to penetrate other industries and its future depends on the various applications, that practitioners come up with in their arena of work.

The development of GIS has been intrinsically linked with the progress of information technology. While on one hand, the development of information technology promotes the progress of GIS, like tools for spatiotemporal big data collection, application, analysis, and mobile-based navigation services etc.

Information technology today has reached a new era of big data, AI, IoT, mobile computing, and cloud computing, and owing to these, new opportunities have arisen for GIS, as well for mapping and data generation.

The ascent of the next generation of GIS

GIS has witnessed great changes in the fields of data acquisition, data management, technology platform, app development, project implementation, etc., with the development of IT. So, let's take a look at a few new research and application feels that have arisen.

Geo AI

Combining spatiotemporal Big Data Analysis and AI technology, Geo-AI possesses features of automation, data-driven, soft learning, as well as support for optimal decision making.

The geospatial data pre-processing, simulation modelling, and scenario-based optimization approach can help in the creation of a new modelling strategy — using traditional and new models in joint innovation is the typical direction of development for Geo AI. GeoAI will also enable users to derive meaningful insights from the voluminous data, which otherwise is difficult to analyse and process.

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Spatial Big Data and spatiotemporal cloud computing

Spatial cloud computing, can be described as cloud computing that is driven by geospatial science. The environment optimisation is through the law of time in space, so that it facilitates geospatial science discovery, research and application in a distributed environment.

Spatial cloud computing provides a reference for GIS in the new era of information technology.

Cloud computing also allows handling of voluminous data in collaborative environment for variety of application, which make the technology available on browsers and on edge computing devices.

Application scenarios for new GIS technologies

With the help of Big Data, IoT, cloud computing, and other new technologies, GIS has gained more applications scenarios. For example, smart city is an important platform for these new domains, which includes a lot of technology and business perspectives. In fact, based on a report by Global Market Insights Inc., the GIS market size is poised to exceed $9 billion by 2024.

Cloud-based systems have gained traction amongst organisations — owing to the complexities that are associated with the storage and management of location-based data — so that they can help in achieving cost reduction, better productivity and efficient management of data.

AI and ML are fundamentally changing how analysis can support day to day business operations, and provide better intelligence opportunities for a multitude of sectors. For example, ML can help with insurance intelligence within the car insurance market, wherein risk factors like driving patterns of a driver can be processed and analysed by ML systems with onboard services, and link to a particular location in order to give a tailored analysis.

There has been an increase in the range of sensing capabilities that are available in established technologies like LiDAR, Thermal IR, Multi‑spectral, and Oblique Imaging etc. that will be beneficial for industries that require highly granular ground-level data, for example, agriculture, urban planning, infrastructure, mining etc.

Apart from this new opportunities will arise in other sectors that will use a combination of aerial imagery with other map data and land use data. A great example of this could be for understanding urban environments in a more nuanced manner, that will enable highly accurate 3-D models. Combining such high resolution data along with ground truthing using edge computing devices will enable GIS analyst to model the environment and solve complex problems in variety of sectors.

Another area where there is major geospatial interest is in drone technology. As drones continued to become a crucial part of urban environments, their usage in urban traffic management initiatives will increase in the future. Research is underway to develop future swarm capabilities, in command and control systems.

Over the next few years, the usage of drones will probably extend to monitoring of projects, into the domains of personal and passenger delivery as well. For GIS, the primary goal will then become to provide first and last-mile geospatial reference and navigation data, that can support these systems.

This, of course,will end up further developments in systems such as geo awareness, geo-fencing and GNSS based locational requirements

If you look at the GIS landscape, its competitiveness has been characterised by the emergence of countless innovations in technology. Strategic initiatives such as partnerships and product development are continually stimulating the GIS market.

Through the innovative use of advanced IT technology, multi-source data acquisition, high-performance computing, enhanced data organisation and indexing can be achieved, which will lead to a wider discovery of geographical laws and panoramic visualisation technology that will help in achieving complete geospatial knowledge expression.

Thus, with the ever-increasing use case applications, GIS is on the path of wider adoption that will revolutionise sectors with innovations and help us become more future-ready.