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Conference Proceeding

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This paper provides an overview of oil spill scenarios and the remote sensing methods used for detection and mapping the spills. It also discusses the different kinds of thermal sensors used in oil spills detection. As UAS is becoming an important player in the oil and gas industry for the low operating costs involved, this research involved working with a cheap thermal airborne sensor mounted on DJI Phantom 4 system. Data were collected in two scenarios, first scenario is collecting data in Michigan’s Upper Peninsula at a petroleum company location and the second scenario was an indoor experiment simulating an offshore spill. The aim of this research is to inspect the capability of Lepton LWIR inexpensive sensor to detect the areas contaminated with oil. Data processing to create classification maps involved using ArcGIS 10.5.1, ERDAS Imagine 2015 and ENVI 5.3. Depending accuracy assessment (confusion matrices) for the classified images and comparing classified images with ground truth, results shows the Lepton thermal sensor worked well in differentiating oil from water and was not a good option when there are many objects in the area of interest. Future research recommendations and conclusions are presented.

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© Author(s) 2018. Paper deposited here in compliance with publisher policies. Publisher's version of record:

Paper presented at: ISPRS TC V Mid-term Symposium “Geospatial Technology – Pixel to People”, 20–23 November 2018, Dehradun, India

Publication Title

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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