Roe Deer as a Model Species for Aerial Survey-Based Ungulate Population Estimation in Agricultural Habitats

Tari, Tamás and Czimber, Kornél and Faragó, Sándor and Heffenträger, Gábor and Kalmár, Sándor Flóris and Kovács, Gyula and Sándor, Gyula and Náhlik, András (2025) Roe Deer as a Model Species for Aerial Survey-Based Ungulate Population Estimation in Agricultural Habitats. GEOMATICS, 5 (4). ISSN 2673-7418

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Abstract

To achieve professional roe deer population management and to mitigate wildlife-related agricultural damage, a wildlife population estimation trial was conducted in Hungary using an ultralight aircraft with dual sensors (thermal and DSLR camera) to assess the method’s applicability, using the roe deer as a model species. The test took place in early spring, at an altitude of 400 m above ground level and a flight speed of 150 km/h. The survey targeted a total count of a 1040 hectare area using adjacent 200 m-wide strips. This strip-based design also allowed for a methodological comparison between total count and strip sample count approaches. Object-based image classification was applied, and species-level validation was performed. During the survey, a total of 213 roe deer were localised. The average group size was 9.17 ± 1.7 (x¯ ± SE), with two prominent outliers (28 and 34 individuals). Compared to the density value of 0.205 individuals/ha established through the full-area census, the simulated estimations (50% and 25%) showed considerable under- and overestimation, primarily due to the aggregative behaviour of roe deer. Based on the test, aerial population estimation using dual-sensor technology proved to be effective in agricultural habitats; however, the accuracy of the results is strongly influenced by the sampling design applied.

Tudományterület / tudományág

agricultural sciences > forestry and wildlife management

Faculty

Not relevant

Institution

Soproni Egyetem

Item Type:	Article
SWORD Depositor:	Teszt Sword
Depositing User:	Csaba Horváth
Identification Number:	MTMT:36381549
Date Deposited:	17 Oct 2025 07:58
Last Modified:	17 Oct 2025 07:58
URI:	http://publicatio.uni-sopron.hu/id/eprint/3756

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