Object detection in order to determine locations for wildlife crossings

N. Vagić, A. Peulić, Sanja Stojković
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引用次数: 0

Abstract

The intensive construction of road infrastructure due to urbanization and industrialization around the world carries with it negative environmental impacts, primarily due to increased emissions of gases, but also due to the separation of natural habitats and ecosystems. In order to overcome this problem, without affecting the mobility of the population, it is necessary to allow wild animals to cross over or below the roads, i.e. to create wildlife crossings, which requires knowledge of the locations where the corridors of animal movements intersect with existing or planned roads. This paper analysis the establishment of a camera system and the application of a deep learning methodology for the automatic identification of animals by species and number, in order to determine locations for the construction of crossings for large wildlife. Also, the paper presents the possibility of using geographic information systems to analyze information obtained by monitoring built wildlife crossings.
目标检测,以确定野生动物过境点的位置
由于世界各地的城市化和工业化,道路基础设施的密集建设带来了负面的环境影响,主要是由于气体排放的增加,但也由于自然栖息地和生态系统的分离。为了克服这一问题,在不影响人口流动的情况下,有必要允许野生动物越过或低于道路,即创建野生动物过境点,这需要了解动物活动走廊与现有或规划道路相交的位置。本文分析了摄像机系统的建立和深度学习方法的应用,用于根据物种和数量自动识别动物,以确定大型野生动物过境点的建设位置。此外,本文还提出了利用地理信息系统分析通过监测野生动物过境点获得的信息的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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