DOI: 10.5061/dryad.nvx0k6f46
title: Data from: Seasonal variations and challenges in estimating populations and identifying species of Korean ungulates using drone-derived thermal orthomosaic maps

description: Drones equipped with thermal infrared (TIR) cameras offer significant time
 and labor savings in estimating wild ungulate populations. However,
 accurately monitoring forest-dwelling ungulates remains challenging due to
 their elusive behavior and complex habitat. This study evaluated the
 feasibility of using TIR orthomosaic maps derived from drone surveys to
 estimate the population size of three Korean ungulate species: Water deer
 (Hydropotes inermis), Roe deer (Capreolus pygargus), and Long-tailed goral
 (Naemorhedus caudatus) in a semi-controlled environment. We generated 15
 paired TIR and RGB orthomosaic maps from drone flights conducted in March
 and June 2024. Ungulate counts from TIR imagery were cross-verified using
 Red, Green, and Blue (RGB) maps. Two error metrics—counting error and
 detection error—were calculated using the maximum verified count per month
 as a proxy for the true population size. Regression analysis indicated
 that Ground Sample Distance (GSD) was positively associated with counting
 error, while no clear relationship was found between GSD and detection
 error. These results suggest that environmental and behavioral factors may
 influence detection reliability more strongly than image resolution alone.
 In addition, we analyzed thermal body measurements to explore the
 potential for species identification. While TIR orthomosaic maps were
 generally effective for estimating body size, variation in
 posture—particularly lying positions—substantially affected measurement
 accuracy and limited their usefulness for distinguishing species. This
 study highlights both the capabilities and limitations of using TIR
 orthomosaic maps for ungulate monitoring and offers practical
 considerations for applying drone-based surveys in more complex natural
 settings.
description: <strong>Experimental Design</strong>
 The data was collected from 15 paired thermal infrared and RGB
 orthomosaic maps generated from drone flights over a 20,227㎡ fenced deer
 park housing approximately 19 water deer (<em>Hydropotes
 inermis</em>), 5 roe deer (<em>Capreolus pygargus</em>),
 and 4 long-tailed goral (<em>Naemorhedus caudatus</em>)1. Two
 drone platforms were utilized: the DJI Matrice 350 RTK equipped with a
 Zenmuse H20T camera and the DJI Mavic Pro 3 Thermal, both capturing
 thermal images with 640×512 pixel resolution.
 <strong>Data Collection
 Methodology</strong> Thermal signatures of
 ungulates were manually identified and measured using QGIS software from
 the orthomosaic maps1. All measurements were cross-verified with
 corresponding RGB orthomosaic maps to ensure accurate species
 identification1. The dataset includes body measurements from 149 thermal
 signatures, with animals classified by species and posture (standing vs.
 lying). Measurements were taken for four distinct body parts: total body
 length (T1), shoulder width (T2), waist width (T3), and hip width
 (T4). This dataset supports research on thermal-based
 wildlife monitoring techniques and provides baseline morphometric data for
 Korean ungulate species as measured through drone-based thermal imaging
 technology.
description: # Data from: Seasonal variations and challenges in estimating populations
 and identifying species of Korean ungulates using drone-derived thermal
 orthomosaic maps Dataset DOI:
 [10.5061/dryad.nvx0k6f46](10.5061/dryad.nvx0k6f46) ## Data Description for
 Thermal Orthomosaic Measurement Dataset This dataset contains thermal body
 measurements of three Korean ungulate species collected as part of a
 drone-based population monitoring study conducted at the National
 Institute of Ecology, Seocheon, South Korea, during March and June 2024.
 The experimental efforts aimed to evaluate the feasibility of using
 thermal infrared (TIR) orthomosaic maps derived from drone surveys to
 estimate population sizes and explore the potential for species
 identification based on thermal body measurements. ### Files and variables
 #### File: S1.\_Thermal\_Orthomosaic\_measure.csv **Description:** This
 dataset contains thermal body measurements of three Korean ungulate
 species collected as part of a drone-based population monitoring study
 conducted at the National Institute of Ecology, Seocheon, South Korea,
 during March and June 2024. ##### Variables * **map**: Flight identifier
 corresponding to specific drone survey sessions * **Species**: Species
 classification (WD = Water deer, RD = Roe deer, AG = Long-tailed goral, BB
 = Fawn/juvenile) * **Posture**: Animal posture during measurement (L =
 Lying, S = Standing) * **BodyLength**: Total length from head to tail (T1)
 in meters * **ShoulderWidth**: Width measurement at shoulder region (T2)
 in meters * **WaistWidth**: Width measurement at waist region (T3) in
 meters * **HipWidth**: Width measurement at hip region (T4) in meters ##
 Code/software n/a