I recently had the distinct pleasure of addressing the U.S. Park Service, and U.S. Fish and Wildlife Service Geospatial Training Workshop at the National Conservation Training Center outside Shepardstown, West Virginia. The talk was an overview of how far we've come as well as where we're headed in terms of remote-sensing inputs and geospatial understanding.
Al Gore's speech on a future Digital Earth, presented in 1998, was the starting point for this talk, as few have articulated such a far-reaching vision for the future of geospatial technology. If you recall, Gore focused on a virtual-reality experience where a young girl visits her local library to put on a headset and data gloves to fly over Earth and explore nature as well as historical events.
One of the points Gore makes in that speech is a lament on the human brain's capacity to catalog the large volume of data coming from Landsat and the fact that very few of the pixels coming down from space fire any neurons in the human brain. This observation feels quaint in retrospect, given that satellite's capacity to image Earth every two weeks, while several commercial companies are intent on imaging Earth every day.
Assessing Change
What's not lost in this look back is our curiosity and interest in discovery from Earth-observation data. We have a compelling need to answer questions and understand change in Earth systems that no earthbound platform can provide.
Increasingly, the types of applications we're interested in are about monitoring change and informing decisions on adaptation and resilience. We're interested in visualizing the impacts of management decisions and gaining a holistic sense of the areas we set out to steward.
Tackling Questions
The exponential growth of our Earth-observation capacity is evident in commercial constellations that made up just 9 percent of the market prior to 2015, but are projected to exceed 35 percent by 2024 (according to Euroconsult). Information is power, and people pay for advantageous information.
Much of this growth will come from companies that promise insight rather than pixels. Machine learning is making a big dent in our understanding, processing those pixels that no eyes have ever seen. Algorithms are used to detect change and return results thanks to computing power that learns patterns and associates those patterns to return insight.
Aggregating Results
Gore envisioned virtual environments powered by Earth-observation data and 3D immersion into worlds that would become collaboratories for scientific exploration across disciplines. Although this vision of cross-discipline exploration is slow to be realized, many scientific pursuits and localized issues have been mapped in a collaborative commons to engender consensus and provide impetus for action.
Examples such as snowpack monitoring at the watershed scale in the Sierra Nevadas, exploration of Louisiana shoreline loss, and advocacy concerning invasive species and biodiversity all are examples of next-level experience-oriented geographic data sharing.
Al Gore's vision continues to provide a glimpse into what geospatial technology could become in terms of immersion, exploration and science-driven consensus on the management practices we apply to our planet and its resources. Now that virtual-reality headsets are starting to hit the mainstream, perhaps it's time to create the virtual representations we all can explore.
— Matt Ball, founder and editorial director, V1 Media.
