热带地理 ›› 2019, Vol. 39 ›› Issue (4): 546-552.doi: 10.13284/j.cnki.rddl.003145

• 专刊:无人机在生态学和地理学中的应用 • 上一篇    下一篇

无人机水禽监测模式的设立原则探讨

李 杰1,刘 强2   

  1. (1. 云南财经大学 城市与环境学院,昆明 650221;2. 西南林业大学 湿地学院,昆明 650224)
  • 出版日期:2019-07-10 发布日期:2019-07-10
  • 作者简介:李杰(1984—),河北保定人,讲师,博士,主要从事自然地理学研究,(E-mail)jli_1984@hotmail.com。
  • 基金资助:

    国家自然科学基金项目(41601060)

Prerequisites of Waterfowl Monitoring Using Unmanned Aerial Vehicle

Li Jie1 and Liu Qiang2   

  1. (1. School of Urban and Environment, Yunnan University of Finance and Economics, Kunming 650221, China; 2. Collage of Wetlands, Southwest Forest University, Kunming 650224, China)
  • Online:2019-07-10 Published:2019-07-10

摘要:

无人机水禽监测具有高时空分辨率、高机动性等特性,较传统方法在监测范围、观察视角及数量统计精度等方面均有不同程度质量提升。但因其飞行方式灵活,且在监测水禽过程中与对象物种或集群距离较近,会对其行为等方面造成直接影响。因此,亟需构建合理有序的无人机水禽监测模式。文章使用微型多旋翼无人机(大疆御2 Pro)针对国际重要湿地纳帕海3种集群水鸟:①体长在80~120 cm之间的大型鸟:黑颈鹤(Grus nigricollis)集群;②体长在40~80 cm之间的中型鸟:绿头鸭(Anas platyrhynchos)集群;③体长<40 cm的小型鸟:骨顶鸡(Fulica atra)集群,通过不同飞行高度、拍摄角度等航拍方式对其进行无人机监测,并对比不同监测方式下,各水禽集群特征识别的差异及特点。文章列举了目前无人机水禽监测中对监测结果产生影响的部分问题,同时也提出了无人机水禽监测的一些原则供参考:1)无人机应尽量轻、小,以避免水禽将其误认为捕食者;2)在不惊飞水禽的前提下,尽量选择较低的飞行高度及合适速度;3)抵近水禽集群时,保持操作平顺与平稳,减少无人机状态突变;4)尽量减少无人机抵近水禽的时长,长时间监测应使无人机保持在水禽集群警戒距离之外,使用长焦镜头;5)因不同物种在不同时段、不同生境条件下对干扰的响应不同,因此无人机水禽监测时段和监测区的选择,应建立在对监测对象充分了解的基础上。

关键词: 无人机, 水禽, 监测模式, 识别, 集群特征

Abstract:

Use of Unmanned Aerial Vehicles (UAVs) to monitor waterfowl at a high spatial-temporal resolution and mobility offers enormous advantages by not only expanding the scope of monitoring but also the accurate identification of different species. However, due to its flexibility in movement, the UAV can easily move closer to the target and can impact the birds. In this study, in order to build a UAV waterfowl monitoring mode that is reasonable and orderly, a multi-rotor UAV, DJI Mavic 2 Pro (weight 907 g) was used to monitor the wintering waterfowl in the Napahai Wetland, a Ramsar site in Northwest Yunnan, China. The waterfowls were broadly divided into three categories according to their body size as: 1) big-sized birds with body lengths of 80-120 cm, 2) medium-sized birds with body lengths of 40-80 cm, and 3) small-sized birds with body lengths less than 40 cm. Using the multi-rotor UAV at different flight heights and camera shooting angles, three flocks, namely the black-necked crane (Grus nigricollis) as the typical species representing big-sized birds, the mallard (Anas platyrhynchos) as the typical species representing medium-sized birds, and the common size of coot is less than 40 cm. It has different traits with the ducks. And it has a large population in the study area, were monitored and results were compared. During the course of the monitoring process we recognized that multiple factors influenced the study results. The factors that influenced monitoring include the following: The distinguishability of the camera was a decisive factor in the identification of the species, but this factor is relatively insignificant while using the multi-rotor UAV camera. Second, although the fixed wing UAV has a high-resolution camera, it is unable to stop midair or adjust its altitude quickly. Also, it requires a proposed flight path. Third, waterfowl behavior was influenced by the type of UAV including its size, weight, flight height, and noise, apart from the monitoring time. It is difficult to quantify the effect as these factors have a compound effect. Fourth, automatic identification based on UAVs and the image recognition of waterfowl requires large datasets of images of birds from the top view, whereas regular images mostly comprise the side view. The top view images mainly provide features of the waterfowl’s back, while the side view angle mainly provides features of waterfowl’s head, chest and wing. Fifth, when the waterfowl cluster is large, several images may be required to cover the whole cluster and these images need to spliced into a big image. The high overlap rate of the images may cause major errors while arriving at the final population of the birds. We have summarized some of the prerequisites for UAV waterfowl monitoring as follows: 1) the UAV should be light and small to ensure that waterfowl do not mistake them for predators; 2) the UAV must be flown at a lower altitude and an appropriate speed without disturbing the waterfowl cluster to fly; 3) smooth and stable operation should be ensured as the UAV approaches the waterfowl colony; 4) the monitoring time must be minimized when the UAV is close to the waterfowl, and in case of extended monitoring, the UAV should be kept away from the waterfowl cluster (use of the telephoto lens is recommended); and 5) the selection of monitoring time periods and areas for waterfowl using UAV should be based on a complete understanding of the target colony because different species respond differently to various kinds of disturbances at various times and in different habitats.

Key words: Unmanned Aerial Vehicle, waterfowl, monitoring mode, identification, cluster trait