Exploiting Time-Series Image-to-Image Translation to Expand the Range of Wildlife Habitat Analysis

Abstract

Characterizing wildlife habitat is one of the main topics in animal ecology. Locational data obtained from radio tracking and field observation are widely used in habitat analysis. However, such sampling methods are costly and laborious, and insufficient relocations often prevent scientists from conducting large-range and long-term research. In this paper, we innovatively exploit the image-to-image translation technology to expand the range of wildlife habitat analysis. We proposed a novel approach for implementing time-series imageto-image translation via metric embedding. A siamese neural network is used to learn the Euclidean temporal embedding from the image space. This embedding produces temporal vectors which bring time information into the adversarial network. The well-trained framework could effectively map the probabilistic habitat models from remote sensing imagery, helping scientists get rid of the persistent dependence on animal relocations. We illustrate our approach in a real-world application for mapping the habitats of Bar-headed Geese at Qinghai Lake breeding ground. We compare our model against several baselines and achieve promising results.

Image-to-Image Translation: Methods and Applications

“…We also notice that two special types of data are used in I2I algorithms for particular tasks: remote sensing imaging for wildlife habitat analysis [211] and medical imaging for disease diagnosis [212], [213], [214], [192], dose calculation [215] and surgical training phantoms improvement [216].…”

Placing Green Bridges Optimally, with a Multivariate Analysis

“…[...] In addition, different species use different habitats, influencing their movements and where they want to cross the road. [11, p. 16] Connect GBP Reach GBP Closed GBP ≥ P ≤P 1-Reach GBP 1-Closed GBP In addition, it is pointed out that data about wildlife habitats is basic for mitigation plans, yet challenging to obtain [19]. In this work, our main problem is placing green bridges at low cost and under several variants of habitat-connectivity requirements, thereby inherently modeling different availabilities of data on habitats.…”