There’s no doubt that geospatial datasets are a prime example of “big data.” Clearly, when the goal of the geospatial industry is to record Earth’s changes through mapping and geospatial products and services, a planet-sized dataset can’t be small. The fact that the world is constantly changing and there’s continual innovation in the sensors and platforms that capture global data means we’re going from big to HUGE datasets.
In 1998, when Microsoft Research went looking for a dataset to test new online database technology, the company chose public-domain data from the U.S. Geological Survey and soon announced TerraServer. Since then, the entire archive of Landsat imagery has moved online via multiple repositories, with support from Esri, Google and others. And, with the advent of cloud computing, more data than ever are being warehoused and analyzed these days. Now geospatial professionals have far greater flexibility in finding the data they need, processing the data with an assist from cloud-based computing and using algorithms that analyze the data to reveal new insights.
A new player in today’s geospatial data explosion is unmanned aircraft system (UAS) technology, which is poised to provide personal aerial mapping platforms. The technology is proven and getting fine-tuned with automation that will make drones accessible to anyone. It’s just a matter of time before regulations and legislation are resolved to unleash the power of UAS technology for the masses.
Can you imagine a million UAS flights per day in the United States alone by 2020? That’s the figure predicted by the Consumer Electronics Association based on new research. With momentum growing for these new platforms, expect to see dramatic changes in the geospatial industry. See “Moving Forward with UAS Mapping,” beginning on page 24, for more details on today’s UAS capabilities and mapping workflows.
Commercial satellite imagery providers have been highlighting insights over pixels for years in their marketing pitches. We’ve heard again and again that the deliverable is often a report or simply an answer to a business query rather than an image or a map. This evolution is made possible thanks to an ever-increasing archive of Earth imagery, the ability to automate change detection and some serious advances in computing capacity that allow users to sift quickly through thousands of images.
Orbital Insight is a pioneering company that harnesses artificial intelligence and custom, cloud-based workflows to process massive amounts of data to create such insights. Read “Orbital Insight Tackles Global Trends Through Advanced Image Processing,” starting on page 38, for insight into the company’s process and how neural networks help derive patterns from pixels.
Geospatial intelligence (GEOINT) is another discipline that relies on insights gleaned from pixels. GEOINT analysts are also embracing automation to help make sense of today’s exponentially increasing data streams. In fact, the GEOINT community is at the forefront of automation, with mandates to deliver integrated intelligence and an immersive experience that communicates near real-time insights.
The analysts and vendors behind these advancements have had to adopt and adapt to innovative workflows that build on time-tested remote sensing foundations while taking advantage of new tools and data. Learn how this evolution has occurred and how it’s benefiting the next generation of GEOINT analysts in “Moving from Pixels to GEOINT Information” starting on page 14.
It’s fascinating to think that we only have a few decades’ worth of digital geospatial data to date. During that time we’ve gone from a lack of data limiting our insight to ever-increasing data volumes that have challenged our ability to archive, store and query them to empower new insights and opportunities. Many geospatial pioneers have commented on the exciting pace of today’s innovations, and we’re only scratching the surface of our understanding. The best is yet to come.
— Matt Ball, founder and editorial director, V1 Media