Biodiversity crisis is still accelerating. Estimating animal abundance is of critical importance to assess, for example, the consequences of land-use change and invasive species on species composition, or the effectiveness of conservation interventions. Camera trap distance sampling (CTDS) is a recently developed monitoring method providing reliable estimates of wildlife population density and abundance. However, in current applications of CTDS, the required camera-to-animal distance measurements are derived by laborious, manual and subjective estimation methods. To overcome this distance estimation bottleneck in CTDS, this study proposes a completely automatized workflow utilizing state-of-the-art methods of image processing and pattern recognition.
翻译:估计动物丰量对于评估土地使用变化和入侵物种对物种组成或养护干预措施的效果等的影响至关重要。摄像陷阱远程取样是最近开发的一种监测方法,提供了野生动物种群密度和丰度的可靠估计。然而,在目前应用的CTDS中,所需的摄影机到动物距离测量是通过艰苦、手工和主观的估计方法得出的。为克服CTDS中的这种距离估计瓶颈,本研究建议采用最新工艺的图像处理和模式识别方法,实现完全自动化工作流程。