Abstract
While the human population continues to grow and the economy is developing, biodiversity is decreasing in the wake of land development, for instance. However, biodiversity is the essential for humans to obtain ecosystem services. Therefore it is required to preserve biodiversity and its sustainable development. Wildlife monitoring is necessary for its preservation. Recently we can obtain the accurate position of wildlife by GPS (Global Positioning System) telemetry. However the use of telemetry is allowed for a limited number of wildlife. Therefore it is expected to increase the ecological knowledge through our constructing the system which obtains ecological information from remote sensing images.
We developed DTR algorithm which is for computer aided detection of animal tracks in the snow using high spatial resolution remote sensing images. DTR algorithm reduces hard labor to find out directly the tracks by visually examination of remote sensing images and avoids overlooking the tracks. This time we apply DTR algorithm to the aerial images taken in Sarufutsu in Hokkaido. And we distinguished species which left the detected tracks by visual examination and discriminant analysis based on field investigation. As a result, animals which left detected tracks were interpreted as sika deer (Cervus Nippon yesoensis) according to length and width of one set of the footprints. Also we estimated population density of target animals by applying INTGEP (Intersection Points Counting Method Based on Geometrical Probability) method to lengths of sika deer's tracks. Comparisons of footprints from the DTR algorithm and from visually examination proved that 76% of the footprints in the snow could be detected using the DTR algorithm. It is shown that automatic detection of the tracks in the snow in remote sensing images is possible using the DTR algorithm.
