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Exploring the feasibility of unmanned aerial vehicles and thermal imaging for ungulate surveys in forests - preliminary results

机译:探索无人飞行器和热成像技术在森林中有蹄类动物调查中的可行性-初步结果

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摘要

Effective wildlife management and conservation require reliable assessments of animal abundance. However, no ungulate monitoring methods is entirely satisfying in terms of cost-effectiveness and accuracy. A new method combining unmanned aerial vehicles (drones) and thermal infrared (TIR) imaging may have great potential as a tool for ungulate surveys. Drones enable safe operations at low flying altitudes, and at night - a time that often offers the optimal conditions for wildlife monitoring. To assess the feasibility of the proposed method we used fixed-wing drones with TIR cameras to conduct test surveys in Drawieski National Park, Poland. We demonstrated that ungulate thermal signatures are visible both in leafless deciduous and in pine-dominated coniferous forests. Survey timing highly influenced the results - the best quality thermal images were obtained at sunrise, late evening, and at night. Our preliminary results indicated that thermal surveys from drones are a promising method for ungulate enumeration. We demonstrated that with ground resolution of similar to 10cm it is possible to visibly distinguish large species (i.e. red deer) and achieve a good level of area coverage. The main challenges of the method are difficulties in species identification due to relatively low resolution of TIR cameras, regulations limiting drone operations to visual line of sight, and high dependence on weather.
机译:有效的野生动植物管理和保护需要对动物丰度进行可靠的评估。然而,就成本效益和准确性而言,没有蹄类动物的监测方法不能完全令人满意。结合无人机(无人机)和热红外(TIR)成像的新方法作为有蹄类动物调查工具可能具有巨大潜力。无人驾驶飞机可以在低空飞行高度和夜间安全运行-这段时间通常为监视野生生物提供了最佳条件。为了评估该方法的可行性,我们使用了带有TIR摄像机的固定翼无人机在波兰Drawieski国家公园进行了测试。我们证明了在无叶落叶和以松树为主的针叶林中都可以看到有蹄类动物的热特征。勘测时间对结果影响很大-在日出,傍晚和晚上都可获得最佳质量的热图像。我们的初步结果表明,从无人机进行热调查是一种有希望的有蹄类枚举方法。我们证明,在接近10厘米的地面分辨率下,可以明显地区分大型物种(即马鹿),并实现良好的区域覆盖率。该方法的主要挑战是由于TIR摄像机的分辨率相对较低而难以进行物种识别,法规将无人机操作限制在视线范围内以及对天气的高度依赖。

著录项

  • 来源
    《International journal of remote sensing》 |2018年第16期|5504-5521|共18页
  • 作者单位

    Polish Acad Sci, Museum & Inst Zool, Warsaw, Poland;

    Polish Acad Sci, Museum & Inst Zool, Warsaw, Poland;

    Univ Warsaw, Dept Geoinformat Cartog & Remote Sensing, Fac Geog & Reg Studies, Warsaw, Poland;

    Taxus SI, Warsaw, Poland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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