Preliminary assessment of thermal imaging equipped aerial drones for secretive marsh bird detection

被引:3
|
作者
Olsen, Tabitha W. [1 ]
Barron, Trey [2 ]
Butler, Christopher J. [3 ]
机构
[1] Univ Cent Oklahoma, Dept Biol, Edmond, OK 73034 USA
[2] Texas Parks & Wildlife Dept, Victoria, TX USA
[3] Texas A&M Univ, Dept Biol, College Stn, TX 77843 USA
来源
DRONE SYSTEMS AND APPLICATIONS | 2023年 / 11卷 / 1-9期
关键词
black rail; thermal; Texas; nocturnal survey; disturbance; RAIL COTURNICOPS-NOVEBORACENSIS; HUMAN DISTURBANCE; HABITAT USE; AIRCRAFT; MISSISSIPPI; RESPONSES; BEHAVIOR; ALABAMA; ECOLOGY; ESCAPE;
D O I
10.1139/dsa-2022-0046
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Rails are a highly secretive group of marshland obligate species that are difficult to consistently survey and detect. Current survey efforts utilize either call-playback or autonomous recording devices, but the low detection probabilities for rails create challenges for long-term systematic monitoring. Between 8 April and 16 May 2022, we flew a small aerial drone equipped with a thermal camera to survey for six species of rail (Black Rail (Laterallus jamaicensis), Yellow Rail (Coturnicops noveboracensis), Sora (Porzana carolina), Virginia Rail (Rallus limicola), Clapper Rail (Rallus crepitans), and King Rail (Rallus elegans)) along the Gulf Coast of Texas to assess the feasibility of long-term drone monitoring. We successfully conducted 33 flights at 15 m above ground level and detected rails on the first visit at 42% of known occupied points. We achieved 27 total rail detections, including 12 Black Rail/Yellow Rail detections. Of the birds detected, 81% exhibited no response to the drone's first approach. We intend for this preliminary data to shape future survey protocol for secretive species occupying difficult to navigate terrain.
引用
收藏
页码:1 / 9
页数:9
相关论文
共 30 条
  • [1] Preliminary assessment of thermal imaging equipped aerial drones for secretive marsh bird detection
    Olsen, Tabitha W.
    Barron, Trey
    Butler, Christopher J.
    DRONE SYSTEMS AND APPLICATIONS, 2023, 11
  • [2] Use of autonomous recording units increased detection of a secretive marsh bird
    Bobay, Lucas R.
    Taillie, Paul J.
    Moorman, Christopher E.
    JOURNAL OF FIELD ORNITHOLOGY, 2018, 89 (04) : 384 - 392
  • [3] Automated auditory detection of a rare, secretive marsh bird with infrequent and acoustically indistinct vocalizations
    Schroeder, Katie M.
    McRae, Susan B.
    IBIS, 2020, 162 (03) : 1033 - 1046
  • [4] A Preliminary Study on Leakage Detection of Deteriorated Underground Sewer Pipes Using Aerial Thermal Imaging
    Park, Sungyong
    Lim, Hyuntaek
    Tamang, Bibek
    Jin, Jihuan
    Lee, Seungjoo
    Park, Songsik
    Kim, Yongseong
    INTERNATIONAL JOURNAL OF CIVIL ENGINEERING, 2020, 18 (10B) : 1167 - 1178
  • [5] A Preliminary Study on Leakage Detection of Deteriorated Underground Sewer Pipes Using Aerial Thermal Imaging
    Sungyong Park
    Hyuntaek Lim
    Bibek Tamang
    Jihuan Jin
    Seungjoo Lee
    Songsik Park
    Yongseong Kim
    International Journal of Civil Engineering, 2020, 18 : 1167 - 1178
  • [6] Estimating Detection and Occupancy of Secretive Marsh Bird Species in Low and High Saline Marshes in Southwestern Louisiana Using Automated Recording Units
    Waddle, J. Hardin
    Jones, Landon R.
    Vasseur, Phillip L.
    Jeske, Clint W.
    WETLANDS, 2022, 42 (04)
  • [7] Estimating Detection and Occupancy of Secretive Marsh Bird Species in Low and High Saline Marshes in Southwestern Louisiana Using Automated Recording Units
    J. Hardin Waddle
    Landon R. Jones
    Phillip L. Vasseur
    Clint W. Jeske
    Wetlands, 2022, 42
  • [8] Enhancing Wildlife Detection Using Thermal Imaging Drones: Designing the Flight Path
    Chang, Byungwoo
    Hwang, Byungmook
    Lim, Wontaek
    Kim, Hankyu
    Kang, Wanmo
    Park, Yong-Su
    Ko, Dongwook W.
    DRONES, 2025, 9 (01)
  • [9] Human detection in aerial thermal imaging using a fully convolutional regression network
    Haider, Ali
    Shaukat, Furqan
    Mir, Junaid
    Infrared Physics and Technology, 2021, 116
  • [10] Human detection in aerial thermal imaging using a fully convolutional regression network
    Haider, Ali
    Shaukat, Furqan
    Mir, Junaid
    INFRARED PHYSICS & TECHNOLOGY, 2021, 116