From the launch of the first Earth observing satellite, to today’s growing space industry, the volume of remote sensing data continues to grow at a remarkable rate. Furthermore, with the emerging utilization of drones, aka unmanned aerial vehicles, and deployment of low-cost satellite constellations, we are on the cusp of a momentous leap forward in data accessibility.
For example, consider the growth of private-sector drones, i.e., those used for scientific research, civil applications and business development. According to a March 2013 report from the Association for Unmanned Vehicle Systems International (AUVSI), assuming the FAA determines how drones fit within commercial airspace by 2015, it is expected that in just ten years the drone industry in the U.S. will generate more than 100,000 jobs and $80 billion of revenue. This includes an immense number of individual drones, on the order of hundreds of thousands, each generating their own streams of remote sensing data.
As another example, consider the pending growth of new low-cost commercial satellite constellations, such as those planned by Skybox Imaging and Planet Labs. Current plans include 28 satellites to be launched by Planet Labs and 24+ satellites to be launched by Skybox Imaging, where each constellation has the objective of achieving cost-effective, near real-time, high-resolution imaging of our planet’s surface. Planet Labs plans to launch its constellation in early 2014, and Skybox Imaging plans to begin launching later in 2013, so data from both companies will soon be available.
There are many questions associated with all of this growth: Where will all this data be stored? How will data be efficiently discovered, accessed and visualized? What types of processing and data management tools will be needed? How will this data be used? What new types of applications will be devised to leverage the information derived from this data?
Amongst these questions, we focus our discussion here on the applications. However, note that the challenges associated with data storage, discovery and dissemination are not trivial, and are equally critical to the success of this industry. But for now let’s consider some of applications that utilize information derived from this imagery.
The AUVSI report indicates a number of areas where drones are already being utilized, including: wildfire mapping, agricultural monitoring, disaster management, power line surveys, law enforcement, telecommunication, weather monitoring, aerial imaging/mapping, television and movies production, oil and gas exploration, freight transport, and environmental mapping. Similar application areas are also highlighted in informational material from Skybox Imaging and Planet Labs, as well as in discussions throughout the remote sensing industry.
To provide more specific examples, the following hypothetical applications were recently reported in an article on Skybox Imaging in Wired (06.18.13): “the number of cars in the parking lot of every Walmart in America; the number of fuel tankers on the roads of the three fastest-growing economic zones in China; the size of the slag heaps outside the largest gold mines in southern Africa; the rate at which the wattage along key stretches of the Ganges River is growing brighter.”
Other example applications include: lawn and vegetation greenness indices for marketing landscape maintenance; water surface conditions for commercial and recreational fishing; flooding and damage assessments for insurance claims; number of beach visitors for targeted advertising; crop health for precision agriculture and investment futures; and many more.
Even with these few examples we see a glimpse of the enormous economic potential for the growing remote sensing industry. A common theme throughout is the need to accurately and efficiently deliver information in a timely manner. To do so still requires the development and implementation of many new hardware and software solutions; however, in that regard there are also many opportunities. This is a significant time for remote sensing, and it will be exciting to see how the industry develops in the near future.
This is part 2 of a series on big data and remote sensing… visit part 1 here.