Thermal soaring flight of birds and unmanned aerial vehicles

Thermal soaring saves much energy, but flying large distances in this form represents a great challenge for birds, people and unmanned aerial vehicles (UAVs). The solution is to make use of the so-called thermals, which are localized, warmer regions in the atmosphere moving upward with a speed exceeding the descent rate of birds and planes. Saving energy by exploiting the environment more efficiently is an important possibility for autonomous UAVs as well. Successful control strategies have been developed recently for UAVs in simulations and in real applications. This paper first presents an overview of our knowledge of the soaring flight and strategy of birds, followed by a discussion of control strategies that have been developed for soaring UAVs both in simulations and applications on real platforms. To improve the accuracy of the simulation of thermal exploitation strategies we propose a method to take into account the effect of turbulence. Finally, we propose a new GPS-independent control strategy for exploiting thermal updrafts.     

中国亚热带4个森林动态监测样地无人机可见光遥感影像数据集

常绿阔叶林是我国亚热带地区的地带性植被类型。由于亚热带森林植物群落垂直结构复杂、林冠郁闭度高, 对常绿阔叶林冠层的研究尚缺乏高质量的监测数据。本数据集包含浙江天童山、浙江百山祖、广东车八岭、广东鼎湖山4个大于20 ha的森林动态监测样地2014年8月或2016年9月采集的无人机可见光遥感影像。本数据集是通过将无人机影像、地面控制点和地面调查数据相结合而获得的。每个样地的数据集包括4个文件: ~5 cm空间分辨率的正射影像图和数字表面模型、1 m空间分辨率的森林冠层高度数据和正射影像质量报告。本数据集可为常绿阔叶林的林冠生态学、生物多样性、生态系统功能等研究提供数据支撑。     

Walknet, a bio-inspired controller for hexapod walking

Walknet comprises an artificial neural network that allows for the simulation of a considerable amount of behavioral data obtained from walking and standing stick insects. It has been tested by kinematic and dynamic simulations as well as on a number of six-legged robots. Over the years, various different expansions of this network have been provided leading to different versions of Walknet. This review summarizes the most important biological findings described by Walknet and how they can be simulated. Walknet shows how a number of properties observed in insects may emerge from a decentralized architecture. Examples are the continuum of so-called “gaits,” coordination of up to 18 leg joints during stance when walking forward or backward over uneven surfaces and negotiation of curves, dealing with leg loss, as well as being able following motion trajectories without explicit precalculation. The different Walknet versions are compared to other approaches describing insect-inspired hexapod walking. Finally, we briefly address the ability of this decentralized reactive controller to form the basis for the simulation of higher-level cognitive faculties exceeding the capabilities of insects.     

Supporting the annual international black-faced spoonbill census with a low-cost unmanned aerial vehicle

The black-faced spoonbill (BFS) is a globally endangered species. The annual international BFS census (IBFSC) thus serves as an important initiative to manage and protect the population of this bird. This work attempts to investigate the feasibility of supporting the annual IBFSC with a low-cost unmanned aerial vehicle system (UAVS). A total of six missions were completed to investigate various locations and areas from November 2012 to April 2013, when BFS transited at Taijiang National Park. The flight plan for each mission was made through the automatic mission planning system. All photographs taken in one mission were stitched to a seamless and color-balanced mosaic that can be geo-referenced and displayed on a Web-based platform, such as Google Earth. A close-up photograph of a few BFSs was acquired at a low altitude of 50 m to validate the proposed approach of image processing, including unsupervised classification, hit or miss transform and binary large object analysis. The results show that the selection of one statistical attribute (maximum value in red channel) and two geometrical attributes (size and circularity) is appropriate for identifying BFS without ambiguity. The success of this work encourages us to conduct a large-scale deployment of UAVS in the coming IBFSC.     

无人机在生物多样性遥感监测中的应用现状与展望

近十年, 无人机平台由于其灵活机动、成本低等优势在植被生态调查、资源环境监测、生物多样性保护等领域逐渐兴起。本文从生物多样性遥感监测应用角度首先介绍了无人机分类系统, 为具体工作开展过程中如何选择合适的载体和传感器提供了参考; 继而总结了不同类型无人机的适用性及其可搭载传感器的用途与区别。在此基础上, 针对无人机平台的高精度遥感信息具体应用案例, 就反映生物多样性变化并揭示其驱动机制方面的无人机遥感直接和间接指标的相关研究进展展开阐述。最后, 就目前无人机遥感技术在生物多样性监测领域的应用中存在的限制, 如软硬件结合匹配程度不够、部分设备过于昂贵、法律法规不完善、与传统生物多样性监测手段结合较弱等问题进行探讨。我们认为: 无人机遥感技术可以很好地弥补地面监测与航天、卫星遥感之间的尺度空缺, 更好地将监测点上的结果以准确、可靠的推绎方法扩展到区域尺度供决策分析使用。今后迫切需要进一步加大生物多样性近地面遥感监测项目建设的实施力度, 从整体上提高生物多样性热点区域应对变化的分析预警能力。     

低空无人机遥感在草原监测评价中的应用进展

低空域无人机遥感技术具有高时效性、高分辨率、低成本、易操控等优势,作为地面与高空遥感（航天与航空遥感）间测量尺度空缺的有益补充,低空无人机遥感扩展了样地样方空间尺度,提高了中、小尺度遥感观测信息的精细化程度,实现了草原生境信息的快速采集、处理与分析应用,是草原"星-空-地"一体化监测的重要组成。针对草原监测评价,总结了国内外低空无人机遥感在草原基况调查（草原草层高度监测、草原植被覆盖度监测与草原地上生物量估算）、草原动态监测（草原植被长势监测、草原产草量估测与草畜平衡监测）和草原应急管理（草原火灾、雪灾与生物灾害监测）中的应用。结合大数据、人工智能、云计算与物联网等新型技术,分析了低空无人机遥感在草原生态监测领域存在的不足和未来的发展方向,以期为低空无人机遥感关于草原监测评价与智慧草原的后续研究提供参考。     

Individual tree crown width detection from unmanned aerial vehicle images using a revised local transect method

The width of individual tree crowns is a critical parameter of canopy structure that can indirectly determine the stand diameter at breast height, tree height, competition, and understory light. Additionally, accurate estimation of crown width is gainful in improving forest carbon storage estimations. However, detecting automatic and accurate crown widths based on visible images is still challenging owing to the influence of crown overlap, shadows, and background. Therefore, we proposed a revised local transect method to detect crown widths from three high-spatial-resolution unmanned aerial vehicle images. Two parameters, the boundary point adjustment parameter (α) and percentile parameter (β), were added to remove the outliers for crown width estimate, reducing the influence of crown overlap, background, and shadow on boundary point detection and delineating the crown width more accurately. The results showed that α had a more significant effect on the crown-width detection accuracy than β. A larger smoothing window size was necessary to improve the accuracy of crown width detection for images with very high spatial resolution. With the optimal α (10%) and smoothing window size, the coefficients of determination between the detected crown width estimates and referenced crown width were between 0.75 and 0.78, and the relative root mean square errors were between 7.50% and 14.65%. Overall, the revised local transect method for detecting crown width is feasible and provides technical support for the accurate detection of crown width based on visible images from unmanned aerial vehicles.     

Aerodynamics of a bio-inspired flexible flapping-wing micro air vehicle

MAVs (micro air vehicles) with a maximal dimension of 15 cm and nominal flight speeds of around 10 m s?1, operate in a Reynolds number regime of 10? or lower, in which most natural flyers including insects, bats and birds fly. Furthermore, due to their light weight and low flight speed, the MAVs' flight characteristics are substantially affected by environmental factors such as wind gust. Like natural flyers, the wing structures of MAVs are often flexible and tend to deform during flight. Consequently, the aero/fluid and structural dynamics of these flyers are closely linked to each other, making the entire flight vehicle difficult to analyze. We have recently developed a hummingbird-inspired, flapping flexible wing MAV with a weight of 2.4-3.0 g and a wingspan of 10-12 cm. In this study, we carry out an integrated study of the flexible wing aerodynamics of this flapping MAV by combining an in-house computational fluid dynamic (CFD) method and wind tunnel experiments. A CFD model that has a realistic wing planform and can mimic realistic flexible wing kinematics is established, which provides a quantitative prediction of unsteady aerodynamics of the four-winged MAV in terms of vortex and wake structures and their relationship with aerodynamic force generation. Wind tunnel experiments further confirm the effectiveness of the clap and fling mechanism employed in this bio-inspired MAV as well as the importance of the wing flexibility in designing small flapping-wing MAVs.     

无人机调查白鹤种群数量和越冬分布

白鹤(Leucogeranus Leucogeranus)是国家Ⅰ级重点保护野生动物,唯一一种极度濒危(CR)鹤类,分布和种群数量是评估其濒危程度的重要参数。无人机调查作为目前生态学研究的一个重要调查方法,为查明白鹤的越冬分布、种群数量及幼鸟比例,于2022年1月使用地面监测结合无人机调查的方法在江西、山东、安徽、湖南、湖北等地的湖泊和农田中开展越冬白鹤调查。野外调查共记录白鹤5607只,网络信息检索在调查区域外的8个地点记录白鹤9只,合计记录越冬白鹤5616只。其中江西鄱阳湖记录到越冬白鹤4813只,占总数的85.7%,主要分布在康山垦殖场、五星垦殖场和成新垦殖场;山东黄河三角洲记录到越冬白鹤625只,占总数的11.1%。安徽、湖南、湖北分别记录到越冬白鹤34,63和72只。对部分群体的白鹤幼鸟数量进行统计,4680只白鹤中,记录到幼鸟674只,幼鸟比例为14.4%,其中湖南越冬白鹤幼鸟比例最高,达28.6%,山东越冬白鹤幼鸟比例最低,为11.5%。调查刷新了白鹤种群数量,证实了山东黄河三角洲是目前除江西鄱阳湖外最重要的白鹤越冬地,缓解了白鹤越冬期过度集中的压力。基于本研究结果,我们...     

Southern right whales show no behavioral response to low noise levels from a nearby unmanned aerial vehicle

Unmanned aerial vehicles (UAVs) are increasingly used for wildlife research and monitoring, but little information exists on their potential effect on marine mammals. We assessed the effects of a UAV on the behavior of southern right whales (Eubalaena australis) in Australia. Focal follows of ten right whale mother-calf pairs were conducted using a theodolite. Control data were recorded for 30 min, and then a DJI Inspire 1 Pro was flown above the whales for 10 min at 5 m altitude. Potential changes to horizontal behavior (swim speed and turning angle) and surfacing pattern (interbreath intervals) were investigated by comparing mother-calf behavior before and during UAV approaches. Changes in respiration rate were used to quantify energetic effects. We also explored acoustic cue perceptibility of the UAV at 5, 10, and 30 m altitude, by measuring the received UAV underwater noise level on whales equipped with acoustic tags (DTAGs). The received noise levels were 86.0 ± 3.9 dB re 1 μPa, while the measured ambient noise was 80.7 ± 7.3 dB re 1 μPa in the same frequency band (100–1,500 Hz). No behavioral response to the UAV was observed. This provides support for UAVs as a noninvasive tool to study baleen whale behavior and ecophysiology.     

A dengue outbreak in a rural community in Northern Coastal Ecuador: An analysis using unmanned aerial vehicle mapping

Dengue is recognized as a major health issue in large urban tropical cities but is also observed in rural areas. In these environments, physical characteristics of the landscape and sociodemographic factors may influence vector populations at small geographic scales, while prior immunity to the four dengue virus serotypes affects incidence. In 2019, a rural northwestern Ecuadorian community, only accessible by river, experienced a dengue outbreak. The village is 2–3 hours by boat away from the nearest population center and comprises both Afro-Ecuadorian and Indigenous Chachi households. We used multiple data streams to examine spatial risk factors associated with this outbreak, combining maps collected with an unmanned aerial vehicle (UAV), an entomological survey, a community census, and active surveillance of febrile cases. We mapped visible water containers seen in UAV images and calculated both the green-red vegetation index (GRVI) and household proximity to public spaces like schools and meeting areas. To identify risk factors for symptomatic dengue infection, we used mixed-effect logistic regression models to account for the clustering of symptomatic cases within households. We identified 55 dengue cases (9.5% of the population) from 37 households. Cases peaked in June and continued through October. Rural spatial organization helped to explain disease risk. Afro-Ecuadorian (versus Indigenous) households experience more symptomatic dengue (OR = 3.0, 95%CI: 1.3, 6.9). This association was explained by differences in vegetation (measured by GRVI) near the household (OR: 11.3 95% 0.38, 38.0) and proximity to the football field (OR: 13.9, 95% 4.0, 48.4). The integration of UAV mapping with other data streams adds to our understanding of these dynamics.     

基于无人机影像的阿拉善东南部荒漠灌丛植被空间格局研究

干旱区灌丛植被空间格局受多种物理和生态过程影响,能够指示生态系统的状态。研究通过量化灌丛斑块大小的空间分布来评估阿拉善高原东南部覆沙荒漠植被生态系统的状态,采用点格局分析法分析灌木种群的相互关系,以阐明不同灌木种在斑块格局形成中的作用,并结合土壤条件及下垫面粗糙度等指标验证评估的准确性,探讨灌丛空间格局差异的内在机理。结果表明,研究区样方2灌丛斑块大小符合截尾幂律分布,其他样方符合对数正态分布,前者的空间结构及生境条件均优于后者,说明植被空间格局可以准确表征生态系统状态。在局地尺度上灌木种内和种间呈现不同的相互关系,以竞争关系为主导是导致斑块破碎化的主要驱动机制。小灌木（如猫头刺）的种内互利关系有利于促进多样化斑块形态的形成,而大灌木（如沙冬青和蒙古扁桃）种间的互利作用则有利于形成异质性更强的复杂空间格局。基于灌丛斑块的空间格局评估生态系统状态,可为保护和恢复生态脆弱区受损植被提供重要的借鉴。     

基于无人机航测的漯河市土地利用景观格局尺度效应

景观格局的尺度效应一直是景观生态学研究的核心内容,对于揭示景观空间格局变化规律及其生态过程具有重要意义。以漯河市中心城区为研究对象,基于景观生态学原理,采用无人机航测技术获取空间分辨率为0.09 m的无人机影像,结合GIS空间分析法,量化分析了漯河市土地利用景观格局的尺度效应。结果表明:(1)漯河市中心城区土地利用景观格局具有明显的粒度和幅度效应。(2)粒度越小,景观格局指数随空间粒度的变化趋势越稳定,其表达的生态过程越真实;景观水平上景观格局的粒度效应是由建筑、道路和绿地景观在景观优势度、破碎度和聚集度等方面的变化导致的;35 m和3 m分别为研究粒度效应的临界阈值和最佳粒度。(3)景观优势度、破碎度和蔓延度随空间幅度的增加而降低,景观复杂程度和聚集度随空间幅度的增加而增加;景观格局具有明显的空间梯度分布特征——从市中心往外由不透水地面向透水地面过渡;建筑和道路在城市中心区聚集度较高,而绿地景观在城市内部破碎度较高,进而主导了整体景观格局的梯度变化;景观组分的稳定与城市规模有关。(4)无人机航测技术可以更快速、准确地获取城市尺度上的景观生态信息,揭示景观格局对尺度效应的响应特征,可为景观格局优化和城乡景观规划提供科学依据。     

Applications of an unmanned aerial vehicle and thermal-imaging camera to study ducks nesting over water

Finding and monitoring nests are key components of avian research, but they are often expensive, time-consuming, and inefficient operations. This is certainly true for diving ducks that nest in wetlands with thick emergent vegetation where nests are typically located by teams of technicians that wade through a marsh and beat vegetation with sticks, hoping to flush incubating females or encounter nests without a female present. Taking advantage of recent advances in both unmanned aerial vehicles (UAVs) and thermal-imaging cameras, our objectives were to (1) compare our ability to locate duck nests using a UAV and using traditional on-foot searching methods, and (2) determine if nests monitored remotely with the UAV had different survival rates than nests monitored with traditional nest-site visits. We searched for nests with a UAV system in southern Manitoba during the springs of 2018 and 2019. Using the UAV, we located 48 nests not found by ground crews, ground crews found 164 nests not found with the UAV, and 71 nests were found using both methods. Overall, nests were less likely to be detected with the UAV (0.34) than by ground crews (0.71), but surveys were completed approximately four times faster with the UAV. Detectability of nests varied among duck species (range = 0.55–0.04). We found no difference in nest survival between nests monitored with the UAV (0.95) and those repeatedly visited by ground crews (0.95). However, in 2018, ground monitoring resulted in 19 nests being abandoned by females, compared to only one monitored with the UAV. Our results demonstrate that UAVs equipped with thermal cameras can be used to find nests of ducks located over water, with greater success for species that nest earlier and those whose nests are not buried under matted vegetation. Furthermore, monitoring nests with the UAV resulted in lower rates of nest abandonment, and survival of nests monitored with the UAV was similar to that of nests monitored using traditional methods. Additional species- and habitat-specific studies are needed to fully understand the utility and challenges associated with using UAVs equipped with thermal imaging to survey species of wetland wildlife.     

Quantifying senescence in bread wheat using multispectral imaging from an unmanned aerial vehicle and QTL mapping

Environmental stresses from climate change can alter source–sink relations during plant maturation, leading to premature senescence and decreased yields. Elucidating the genetic control of natural variations for senescence in wheat (Triticum aestivum) can be accelerated using recent developments in unmanned aerial vehicle (UAV)-based imaging techniques. Here, we describe the use of UAVs to quantify senescence in wheat using vegetative indices (VIs) derived from multispectral images. We detected senescence with high heritability, as well as its impact on grain yield (GY), in a doubled-haploid population and parent cultivars at various growth time points (TPs) after anthesis in the field. Selecting for slow senescence using a combination of different UAV-based VIs was more effective than using a single ground-based vegetation index. We identified 28 quantitative trait loci (QTL) for vegetative growth, senescence, and GY using a 660K single-nucleotide polymorphism array. Seventeen of these new QTL for VIs from UAV-based multispectral imaging were mapped on chromosomes 2B, 3A, 3D, 5A, 5D, 5B, and 6D; these QTL have not been reported previously using conventional phenotyping methods. This integrated approach allowed us to identify an important, previously unreported, senescence-related locus on chromosome 5D that showed high phenotypic variation (up to 18.1%) for all UAV-based VIs at all TPs during grain filling. This QTL was validated for slow senescence by developing kompetitive allele-specific PCR markers in a natural population. Our results suggest that UAV-based high-throughput phenotyping is advantageous for temporal assessment of the genetics underlying for senescence in wheat.

Temporal multispectral imaging from unmanned aerial vehicles can be used to quantify senescence and identify underlying quantitative trait loci in wheat (Triticum aestivum).     

Inversion reflectance by apple tree canopy ground and unmanned aerial vehicle integrated remote sensing data

Journal of Plant Research - To obtain accurate spatially continuous reflectance from Unmanned Aerial Vehicle (UAV) remote sensing, UAV data needs to be integrated with the data on the ground. Here,...     

植保无人机喷雾对枣树主要害虫防治效果评价

为了解植保无人机低空低容量喷雾对枣园主要害虫的防治效果,在植保无人机喷施农药后,调查了对截形叶螨、枣瘿蚊的防治效果,结果发现:在供试飞行条件下,药后5d25％环氧虫啶(用药量为300 g/hm2)、70％吡虫啉(用药量为150g/hm2)对枣瘿蚊的防治效果最高,分别为87.73％和89.74％,两处理之间无显著差异,均...     

Detection of organic tea farms based on the density of spider webs using aerial photography with an unmanned aerial vehicle (UAV)

Landscape and Ecological Engineering - Organic tea farms promote biodiversity and perform important ecological functions that benefit the environment and supply safe and secure products to...