A road mobile mapping device for supervised classification of amphibians on roads

  • Neftalí SilleroEmail author
  • Hélder Ribeiro
  • Marc Franch
  • Cristiano Silva
  • Gil Lopes
Original Article
Part of the following topical collections:
  1. Road Ecology


We present the classification results of a supervised algorithm of road images containing amphibians. We used a prototype of a mobile mapping system composed of a scanning system attached to a traction vehicle capable of recording road surface images at speed up to 30 km/h. We tested the algorithm in three test situations (two control and one real): with plastic models of amphibians; with dead specimens of amphibians; and with real specimens of amphibians in a road survey. The classification results of the algorithm changed among tests, but in any case, it was able to detect more than 80% of the amphibians (more than 90% in control tests). Unfortunately, the algorithm presented as well a high rate of false-positive detections, varying from 80% in the real test to 14% in the control test with dead specimens. The Mobile Mapping Systems (MMS) is ideal for passive surveys and can work by day or night. This is the first study presenting an automatic solution to detect amphibians on roads. The classification algorithm can be adapted to any animal group. Robotics and computer vision are opening new horizons for wildlife conservation.


Robotics Computer vision Conservation Road ecology Mobile Mapping System 


Funding information

This work is funded by the Life LINES project LIFE14 NAT/PT/001081. Previous work was financed by FEDER Funds, through the Operational Programme for Competitiveness Factors—COMPETE, and by National Funds through FCT—Foundation for Science and Technology of Portugal, under the project PTDC/BIA/BIC/4296/2012: Roadkills – Intelligent systems for mapping amphibian mortality on Portuguese roads. NS is supported by an IF contract by FCT (IF/01526/2013). HR and MF are supported by research grants by Life LINES. CS and MF were supported by research grants by FCT (UMINHO/BI/172/2013 and UMINHO/BI/175/2013 respectively).

Supplementary material

10344_2018_1236_MOESM1_ESM.docx (1 mb)
ESM 1 (DOCX 1058 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.CICGE Centro de Investigação em Ciências Geo-Espaciais, Observatório Astronómico Prof. Manuel de Barros, Alameda do Monte da VirgemFaculdade de Ciências da Universidade do Porto (FCUP)Vila Nova de GaiaPortugal
  2. 2.School of Engineering of the University of MinhoGuimarãesPortugal

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