Abstract

The Florida Everglades is infested with Burmese pythons caused by the release of exotic pets in the 1980s. The current estimates are between 30,000 and 300,000 pythons, where the result is a severe decline in Everglade mammals: 90% reductions in raccoon, opossum, bobcats, and foxes. The marsh rabbits are completely gone. The population of the pythons is rapidly increasing exponentially with 20–50 eggs per snake with a life span of up to 20 years. Pythons have been captured in the Everglades with lengths of nearly 6 m. Researchers in the state of Florida are concerned that these pythons are (1) permanently damaging the Everglades, (2) migrating further north into populated areas of Florida, and (3) endangering wildlife, pets, and eventually, people. There have been a number of sensing efforts attempted in the large-area detection of pythons, where limited success has been achieved. For example, infrared sensors have been applied to the problem, but the pythons are cold-blooded, so the infrared bands do not work well. Imec has leveraged its expertise and infrastructure in semiconductor processing to produce highly compact, higher performance, and relatively cheaper hyperspectral image sensors and camera systems. In this work, Imec teamed with the University of Florida and Extended Reality Systems to obtain hyperspectral reflectivity measurements of Burmese pythons along with natural Florida background foliage to determine bands or band combinations that may be exploited in the large-area detection of pythons. The bands investigated are the visible-near infrared (or VisNIR) and the shortwave infrared (SWIR) bands. The results show that there are enough differences in the data collection such that a single band, inexpensive VisNIR band camera may provide reasonable results and a two-band, VisNIR/SWIR combination may provide higher performance results. In this paper, we provide the VisNIR results.

© 2019 Optical Society of America

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