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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2018

Autores

sillero, n (Autor) FCUP; Ribeiro, H (Autor) Outra; Franch, M (Autor) Outra; Silva, C (Autor) Outra; Lopes, G (Autor) Outra

Revista

Título: European Journal of Wildlife Research

Vol. 64

ISSN: 1612-4642

Editora: Springer Nature

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 4 Citações

Outras Informações

ID Authenticus: P-00P-Z18

DOI: 10.1007/s10344-018-1236-4

Abstract (EN): 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 30km/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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6