What does it really mean to “Exploit” imagery – or how about the definitions of “Data analytics”, “Server-side processing”, “Cloud computing”, “Web-enabled OGC services”, please – somebody stop me! These terms are uttered with such frequency that I often find myself wondering – what is the ultimate goal we are trying to achieve? Are we trying to coerce hidden objects to be visually obvious; apply fancy algorithms to eliminate haze; identify linear features in remote areas?
Of course all of these things (and many more) are true. And recently I’ve had an epiphany in terms of the meanings to these phrases, the same way those newer, faster, smarter algorithms are developed, is the same way that our analytics are modernized, and so are our ways to implement these modernizations. What this means is that geospatial information access is available via hundreds of thousands of handheld devices to foresters in the field, soldiers on the ground, and sailors at sea.
The first step in this modernization has already occurred in bringing the analytics to the data. This way, big data and data analytics are literally coexisting in powerful processing environments. The next step is to define the discrete tools – or apps – to exploit this information and bring solutions to real-world problems and answers to real-world questions.
Case in point is a recent article published on defensystems.com; NGA apps for GEOINT facilitate mobile tactical tools.
In reference to the NGA app store, more than 150 different apps – or discrete processing tools – are already available for their users to consume. Many of these apps are created internally – although access to large geodatabase repositories via open standards enables external developers to create consumable analytics. The vision to grow these capabilities is to “create apps for the cloud, put them up there, verify that the apps work as intended, and then let the analysts and people choose the apps that they want.”
From what I have seen to date, applications like line of sight analysis, vegetation delineation, object identification, atmospheric correction, and many others have barely scratched the surface of what is possible. I think about the every-day desktop applications and some of the challenges related to desktop processing power and limited data access. I truly believe the possibilities are endless when it comes to the next generation of web-enabled image analytics. What apps are you working on or working with?