We have entered the era of virtual and augmented reality with advancements to immersive headsets and an explosion of 3D data collection capability with drone capture and automated modeling tools. GIS has long had the ability to view and navigate 3D, however, the scale and pace of this disruption may bypass traditional geospatial players.
There are many issues regarding the handling, processing and presentation of the 1:1 map from reality capture technology. The volume and frequency of these data has caused headaches with all who have been handling it, with automation a growing means of dealing with this data pipeline. Transitioning from simply handling and processing these data to incorporating into a GIS with extracted attributes poses a far more difficult problem.
Presenting different levels of detail within a mapping environment have helped to address scaling problems and have allowed computing to render and display far more detailed geospatial information at larger and larger geographies. Algorithms have also advanced greatly to decrease the complexity of 3D objects, while hardware advancements are increasing the efficiency of rendering capabilities. Processing has also taken leaps forward via the infinite computing capacity of the cloud, helping to scale and speed rendering by spreading this task to many machines.
While these technology advancements have been fruitful for ingesting captured reality of small geographies such as construction sites or farm fields, there are issues when scaling highly-detailed models within the framework of GIS.
The workflows of reality capture are being simplified and automated to the point where still imagery data collected from drones can be quickly processed to create orthomosaics and 3D meshes for integration into modeling software and GIS. The distinction drawn between this capability and true integration is the ability to understand and query attributes of this information and to allow this freshest data to update what’s existing in order to improve the accuracy as well as the intelligence that is contained in the GIS.
The pace at which reality capture is feeding immersive experiences may mean that the way users wish to view and experience this data bypasses their GIS. The workflow from drone to video or drone to virtual reality headset may give users all that they’re after. The key for GIS and other modeling software is to insert seamlessly within that workflow to catalog the change history or to overlay other datasets for improved insight while preserving the simplicity of the capture and view workflow.
The area that GIS could greatly impact is the transition from virtual reality toward augmented reality. Augmented reality describes the process of adding intelligence to our ability to navigate 3D virtual realities with valuable information that helps users navigate toward their goal or even guides users through the completion of a task. Augmented reality also holds promise for presenting spatial analytical outputs that give users a much greater understanding of historical context, environmental impact or the complex interactions between our built environment and the environment.
GIS has established itself as a multidisciplinary means of communicating geography for a wide number of application areas. Years of data updates and enterprise integrations have served the full continuum from managers to field workers. This place has been secure because of continual advancements in the technology and flexibility that has allowed this data and the analytical tools to be accessed from desktop to mobile and to Web.
Navigating this next step to the virtual/augmented reality headset could be the most important leap for the future of geospatial technology and its continued relevance as the medium of choice for geospatial communication. The applications for augmented and virtual reality completely cross over the geospatial application space. Let’s hope that seamless and easy integration with captured reality solidifies the necessity of geospatial investments.