Geospatial is at the centre of where every day “change” occurs. All actors, including global financial institutions, have spotted this, creating more robust and consolidated geospatial powerhouses worldwide.

Emerging technologies such as AI and ML are accelerating the processing power for analyzing, correcting, and augmenting different types of geospatial data. AI, ML, IoT are no longer industry trends, they are here to stay and gradually be absorbed in all IT-initiatives including geospatial powered ones.

Seamless Data Flow

The geospatial community witnesses huge digital transformations and daily explosions of new raw data that flows in at real-time speeds. Although the data capturing process is fast, maintaining the right quality level as data evolves, remains the bigger challenge.

We see, too much, degrading data quality over time that has the potential to lead to wrong business decisions. To load it once has become easy. The real challenge is updating data and syncing it.

There is a need of good quality actionable data with a focus to keep the “system of record” up-to-date using Digital Twin concepts.

In order to foster a comprehensive and innovative geospatial ecosystem, there is a need to introduce continuous real-time feed-back from the field.

The Digital Twin market is going to flourish, as it supports all forms of asset mapping. For a Digital Twin to be of significance, there has to be data collection and a seamless and continuous flow of information from the physical to the digital model.

Geospatial is the true eye-opener. People see what is going on, not by using an abstract tabular report but with the power of intelligent maps.

Though it appears easy, but there is a need for the right enterprise software toolsets and vast industry expertise to make it a reality.

“Geospatial is the true eye-opener. People see what is going on, not by using an abstract tabular report but via the power of maps. Though it appears easy, there is a need for the right software toolsets and industry expertise to make it a reality.”

Real-time Insights

ML and computer vision are not new to the geospatial imaging market. They have been heavily used since more than a decade. The execution speed of digital transformation is a direct effect of AI, which will only accelerate in the future.

There is still a lot of undiscovered potential when it comes to decision- makers embracing spatial technologies to harmonise economic necessities, because in many ways geospatial remains the domain of the specialists, the academic community and engineers.

As more data can be trusted, geospatial dashboard technology will surface. This would allow decision-makers to to look at a spectrum of data real-time making right decisions on-the-fly.

Disclaimer: Views Expressed are Author's Own. Geospatial World May or May Not Endorse it