Utilizing digital elevation models for camera-trap distance estimation

Leopold Böss, Stephanie Wohlfahrt, David C. Schedl

Publikation: Beitrag in FachzeitschriftKonferenzartikelBegutachtung

Abstract

Camera traps have become a norm for estimating wildlife populations utilizing random encounter models to express metrics such as abundance and density. One essential parameter required to evaluate such models is the speed of the trapped animal. This speed can be estimated by labeling the contact point of instances with the ground across image sequences and projecting the resulting pixels onto a model describing said ground. Our approach proposes using digital elevation models recorded via airborne laser scanning as an alternative to manually calibrating simpler ground models. A study to investigate the impact of DEMs’ level of complexity on the accuracy of projected pixel distance estimates was conducted using a realistic dataset of 2629 2D labels and DEMs of three different resolutions. Reducing the resolution of the used DEM from 3 m to 20 m and 50 m leads to an average skew in distances of 2.84 m and 3.94 m, respectively, with widely dispersed individual errors. Further work is needed to assess the impact of these errors on speed and wildlife density calculations. Despite these challenges, the method shows promise as an alternative to currently used methods.

OriginalspracheEnglisch
Seiten (von - bis)15-21
Seitenumfang7
FachzeitschriftCEUR Workshop Proceedings
Jahrgang3786
PublikationsstatusVeröffentlicht - 2024
Veranstaltung4th International Workshop on Camera Traps, AI, and Ecology, CamTraps 2024 - Hagenberg, Österreich
Dauer: 5 Sep. 20246 Sep. 2024

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