An academic article was published in Scientific Reports this month that illustrates just how useful drones can be for research and data collection.
The paper describes how a team of scientists from Duke University flew a fixed wing UAV, equipped with thermal sensors, to image two grey seal breeding colonies in eastern Canada. A human team analyzed and counted the seals that were photographed, while an automated computer system did the same.
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The automated results fell within 95 to 98% of the humans' count. And where there was a discrepancy, it was due largely to human error.
The results show that the algorithm used to automatically sort wildlife populations is effective.
And the implications?
Automated image classification models like the one in this study synergize well with unmanned aircraft systems (UAS). Appropriate use of UAS can output more precise counts than traditional methods and can yield cost savings. Additionally, UAS assessment of marine vertebrate populations can reduce human risk, and a recent review of job-related mortalities of wildlife biologists revealed that a significant proportion arose from aviation accidents. This type of risk is amplified when working in coastal regions or over the water. The combination of automated image classification and UAS in this study presents a compelling argument for a decrease in the cost of wildlife assessments, a reduction in analyst time and minimization of risk to human surveyors.
In other words, it's cheaper, more accurate, and safer.
Read the full fascinating report here: http://www.nature.com/articles/srep45127#f5
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