Combining Multi-View UAV Photogrammetry, Thermal Imaging, and Computer Vision Can Derive Cost-Effective Ecological Indicators for Habitat Assessment

Qiao Hu, Ligang Zhang, Jeff Drahota, Wayne Woldt, Dana Varner, Andy Bishop, Ted LaGrange, Christopher M.U. Neale, Zhenghong Tang

Research output: Contribution to journalArticlepeer-review

Abstract

Recent developments in Unmanned Aircraft Vehicles (UAVs), thermal imaging, and Auto-machine learning (AutoML) have shown high potential for precise wildlife surveys but have rarely been studied for habitat assessment. Here, we propose a framework that leverages these advanced techniques to achieve cost-effective habitat quality assessment from the perspective of actual wildlife community usage. The framework exploits vision intelligence hidden in the UAV thermal images and AutoML methods to achieve cost-effective wildlife distribution mapping, and then derives wildlife use indicators to imply habitat quality variance. We conducted UAV-based thermal wildlife surveys at three wetlands in the Rainwater Basin, Nebraska. Experiments were set to examine the optimal protocols, including various flight designs (61 and 122 m), feature types, and AutoML. The results showed that UAV images collected at 61 m with a spatial resolution of 7.5 cm, combined with Faster R-CNN, returned the optimal wildlife mapping (more than 90% accuracy). Results also indicated that the vision intelligence exploited can effectively transfer the redundant AutoML adaptation cycles into a fully automatic process (with around 33 times efficiency improvement for data labeling), facilitating cost-effective AutoML adaptation. Eventually, the derived ecological indicators can explain the wildlife use status well, reflecting potential within- and between-habitat quality variance.

Original languageEnglish (US)
Article number1081
JournalRemote Sensing
Volume16
Issue number6
DOIs
StatePublished - Mar 2024

Keywords

  • Unmanned Aircraft Vehicle (UAV)
  • automated detection
  • habitat quality
  • thermal imagery
  • wetland habitats
  • wildlife censusing

ASJC Scopus subject areas

  • General Earth and Planetary Sciences

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