Kernel methods for estimating the utilization distribution in home-range studies

Worton introduced kernel density estimation to home-range analysis, providing a way to estimate the utilization distribution, a probability surface describing how intensively an animal uses each part of its range, rather than just a bounding polygon. By placing a smoothing kernel over each location and summing, the method produces continuous contours that reveal core areas and multiple activity centers. Kernel density estimation became the dominant home-range tool for decades and remains a standard benchmark, though its accuracy depends heavily on the choice of smoothing bandwidth. For felid studies, it offered the first principled picture of where cats concentrate their activity. The paper is among the most cited in spatial ecology and reshaped how home range is conceived and measured.