Identification and Counting of European Souslik Burrows from UAV Images by Pixel-Based Image Analysis and Random Forest Classification: A Simple, Semi-Automated, yet Accurate Method for Estimating Population Size

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 9; p. 2025
• Main Authors: Gedeon, Csongor I., Árvai, Mátyás, Szatmári, Gábor, Brevik, Eric C., Takáts, Tünde, Kovács, Zsófia A., Mészáros, János
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2022
• Subjects: Accuracy; Algorithms; Automation; Classification; Coefficient of variation; Ecosystem services; Estimation; Grasslands; Histograms; Identification methods; Image analysis; Image classification; Image processing; Iterative methods; Methods; model stability; pixel-based imagery; Pixels; Population; Population number; population size; Population statistics; random forest; Remote sensing; Sensitivity; Soils; Unmanned aerial vehicles; Vegetation; Hungary

Burrowing mammals such as European sousliks are widespread and contribute significantly to soil ecosystem services. However, they have declined across their range and the non-invasive estimation of their actual population size has remained a challenge. Results support that the number of burrow entra...