Details
| Original language | English |
|---|---|
| Pages (from-to) | 2007-2013 |
| Number of pages | 7 |
| Journal | Ecology |
| Volume | 90 |
| Issue number | 7 |
| Publication status | Published - 1 Jul 2009 |
| Externally published | Yes |
Abstract
The recognition of tracks plays an important role in ecological research and monitoring, and tracking tunnels are a cost-effective method for indexing species over large areas. Traditionally, tracks are collected by a tracking system, and analysis is carried out in a manual identification procedure by experienced wildlife biologists. Unfortunately, human experts are unable to reliably distinguish tracks of morphologically similar species. We propose a new method using image analysis, which allows automatic species identification of tracks, and apply the method to identifying cryptic small-mammal species. We demonstrate the method by identifying footprints of three invasive rat species with similar morphology that co-occur in New Zealand, including detection of a recent invasion of a rat-free island. Automatic footprint recognition successfully identified the species of rat for <70% of footprints, and <83% of tracking cards. With appropriate changes to the image recognition, the method could be broadly applicable to any taxa that can be tracked. Identification of tracks to species level gives better estimates of species presence and composition in communities.
Keywords
- Automated species identification, Binarization, Index, Invasive species, New Zealand, Rats, Rattus exulans, Rattus norvegicus, Rattus rattus, Rodents, Template matching, Tracking
ASJC Scopus subject areas
- Agricultural and Biological Sciences(all)
- Ecology, Evolution, Behavior and Systematics
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In: Ecology, Vol. 90, No. 7, 01.07.2009, p. 2007-2013.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Automatic track recognition of footprints for identifying cryptic species
AU - Russell, James C.
AU - Hasler, Nils
AU - Klette, Reinhard
AU - Rosenhahn, Bodo
PY - 2009/7/1
Y1 - 2009/7/1
N2 - The recognition of tracks plays an important role in ecological research and monitoring, and tracking tunnels are a cost-effective method for indexing species over large areas. Traditionally, tracks are collected by a tracking system, and analysis is carried out in a manual identification procedure by experienced wildlife biologists. Unfortunately, human experts are unable to reliably distinguish tracks of morphologically similar species. We propose a new method using image analysis, which allows automatic species identification of tracks, and apply the method to identifying cryptic small-mammal species. We demonstrate the method by identifying footprints of three invasive rat species with similar morphology that co-occur in New Zealand, including detection of a recent invasion of a rat-free island. Automatic footprint recognition successfully identified the species of rat for <70% of footprints, and <83% of tracking cards. With appropriate changes to the image recognition, the method could be broadly applicable to any taxa that can be tracked. Identification of tracks to species level gives better estimates of species presence and composition in communities.
AB - The recognition of tracks plays an important role in ecological research and monitoring, and tracking tunnels are a cost-effective method for indexing species over large areas. Traditionally, tracks are collected by a tracking system, and analysis is carried out in a manual identification procedure by experienced wildlife biologists. Unfortunately, human experts are unable to reliably distinguish tracks of morphologically similar species. We propose a new method using image analysis, which allows automatic species identification of tracks, and apply the method to identifying cryptic small-mammal species. We demonstrate the method by identifying footprints of three invasive rat species with similar morphology that co-occur in New Zealand, including detection of a recent invasion of a rat-free island. Automatic footprint recognition successfully identified the species of rat for <70% of footprints, and <83% of tracking cards. With appropriate changes to the image recognition, the method could be broadly applicable to any taxa that can be tracked. Identification of tracks to species level gives better estimates of species presence and composition in communities.
KW - Automated species identification
KW - Binarization
KW - Index
KW - Invasive species
KW - New Zealand
KW - Rats
KW - Rattus exulans
KW - Rattus norvegicus
KW - Rattus rattus
KW - Rodents
KW - Template matching
KW - Tracking
UR - http://www.scopus.com/inward/record.url?scp=67650689573&partnerID=8YFLogxK
U2 - 10.1890/08-1069.1
DO - 10.1890/08-1069.1
M3 - Article
C2 - 19694147
AN - SCOPUS:67650689573
VL - 90
SP - 2007
EP - 2013
JO - Ecology
JF - Ecology
SN - 0012-9658
IS - 7
ER -