A Linear Domain System Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Genetic Algorithm

<正> This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft.Byusing the flash memory integrated into the micro guide navigation control module, system records the data sequences of flighttests as inputs (control signals for servos) and outputs (aircraft's attitude and velocity information).After data preprocessing, thesystem constructs the horizontal and vertical dynamic model for the small unmanned aerial rotorcraft using adaptive geneticalgorithm.The identified model is verified by a series of simulations and tests.Comparison between flight data and the one-stepprediction data obtained from the identification model shows that the dynamic model has a good estimation for real unmannedaerial rotorcraft system.Based on the proposed dynamic model, the small unmanned aerial rotorcraft can perform hovering,turning, and straight flight tasks in real flight tests.     

Aerial Surveys for Estimating Wild Turkey Abundance in the Texas Rolling Plains

Abstract: Aerial surveys have been used to estimate abundance of several wild bird species including wild turkeys (Meleagris gallopavo). We used inflatable turkey decoys at 3 study sites in the Texas Rolling Plains to simulate Rio Grande wild turkey (M. g. intermedia) flocks. We evaluated detectability of flocks and errors in counting flock size during fixed-wing (Cessna 172) aerial surveys using logistic and linear regression models. Flock detectability was primarily influenced by flock size and vegetative cover, and errors in counting flock size were primarily influenced by size of flocks. We conducted computer simulations to evaluate the accuracy and precision of fixed-wing aerial surveys and examined power to detect trends in population change. Our simulations suggested abundance estimates from fixed-wing aerial surveys may be underestimated by 10-15% (2.0-4.8% CV). Power analyses suggested that fixed-wing aerial surveys can provide sufficient power (>0.80) to detect a population change of 10-25% over a 4-5-year period. We concluded fixed-wing aerial surveys are feasible on ecoregion scales.     

无人机遥感在生态学中的应用进展

无人机与遥感技术的结合,即无人机遥感。与传统的以卫星和有人机遥感相比,无人机遥感具有高时效、高时空分辨率、云下低空飞行、高机动性等优势,是传统卫星和有人机遥感手段所无法比拟的。这些优点使得无人机在生态学和保护生物学等领域获得迅速发展。首先对无人机遥感技术的发展历程、系统组成、分类与选型、应用优势等进行了介绍。在此基础上,对无人机在生态学中的应用案例进行了总结,内容涉及生境监测、植物物候调查、动物监测等方面。最后通过比较国内外相关领域的研究进展对无人机生态学存在的问题(技术门槛较高和法律法规不完善等)和潜在应用前景进行了探讨。     

A Double-Observer Method to Estimate Detection Rate During Aerial Waterfowl Surveys

Abstract We evaluated double-observer methods for aerial surveys as a means to adjust counts of waterfowl for incomplete detection. We conducted our study in eastern Canada and the northeast United States utilizing 3 aerial-survey crews flying 3 different types of fixed-wing aircraft. We reconciled counts of front- and rear-seat observers immediately following an observation by the rear-seat observer (i.e., on-the-fly reconciliation). We evaluated 6 a priori models containing a combination of several factors thought to influence detection probability including observer, seat position, aircraft type, and group size. We analyzed data for American black ducks (Anas rubripes) and mallards (A. platyrhynchos), which are among the most abundant duck species in this region. The best-supported model for both black ducks and mallards included observer effects. Sample sizes of black ducks were sufficient to estimate observer-specific detection rates for each crew. Estimated detection rates for black ducks were 0.62 (SE = 0.10), 0.63 (SE = 0.06), and 0.74 (SE = 0.07) for pilot-observers, 0.61 (SE = 0.08), 0.62 (SE = 0.06), and 0.81 (SE = 0.07) for other front-seat observers, and 0.43 (SE = 0.05), 0.58 (SE = 0.06), and 0.73 (SE = 0.04) for rear-seat observers. For mallards, sample sizes were adequate to generate stable maximum-likelihood estimates of observer-specific detection rates for only one aerial crew. Estimated observer-specific detection rates for that crew were 0.84 (SE = 0.04) for the pilot-observer, 0.74 (SE = 0.05) for the other front-seat observer, and 0.47 (SE = 0.03) for the rear-seat observer. Estimated observer detection rates were confounded by the position of the seat occupied by an observer, because observers did not switch seats, and by land-cover because vegetation and landform varied among crew areas. Double-observer methods with on-the-fly reconciliation, although not without challenges, offer one viable option to account for detection bias in aerial waterfowl surveys where birds are distributed at low density in remote areas that are inaccessible by ground crews. Double-observer methods, however, estimate only detection rate of animals that are potentially observable given the survey method applied. Auxiliary data and methods must be considered to estimate overall detection rate.     

Disturbance Caused by Aerial Waterfowl Surveys During the Nonbreeding Season

Aerial surveys flown at low altitudes allow detection, identification, and enumeration of waterfowl and other waterbirds, but few studies have assessed disturbance to these guilds during the nonbreeding period. Excessive disturbance can potentially increase energy expenditure and exposure to hunting mortality contrary to objectives of many waterfowl sanctuaries where surveys are conducted. We used concurrent ground and aerial surveys to estimate the proportion of waterfowl and other waterbirds that exhibited a noticeable reaction (i.e., disturbance) or left the survey area entirely (i.e., abandonment) during low-altitude (i.e., 60–90 m above ground level) aerial surveys during September through January 2014–2017 in Illinois, USA. Overall, disturbance and abandonment probabilities of waterfowl (x̄ = 14 ± 2% [SE] and x̄ = 3 ± 1%, respectively) during aerial surveys were low. However, disturbance and abandonment probabilities varied considerably among taxa (e.g., American coot [Fulica americana] x̄ = 2 ± 1% and x̄ = 0 ± 0%, respectively; killdeer [Charadrius vociferus] x̄ = 92 ± 8% and x̄ = 17 ± 17%, respectively). Additionally, disturbance and abandonment probabilities of light geese (i.e., snow goose [Chen caerulescens] and Ross's goose [C. rossii]) and greater white-fronted geese (Anser albifrons) were relatively high, and nearly all light geese abandoned a survey location as a result of the aerial survey. Among waterfowl taxa, the odds of disturbance from the survey aircraft were 2.2–6.2 times greater at locations closed to waterfowl hunting than locations open to waterfowl hunting. Temperature, wind speed, and cloud cover were not important predictors of disturbance for most guilds, except for a negative influence of temperature on disturbance of geese. Low-altitude aerial surveys were not a significant source of disturbance for many taxa and abandonment events were rare, except events involving light geese. Periodic low-altitude aerial surveys appear to be compatible with objectives of providing sanctuary conditions for most waterfowl and other waterbirds. © 2020 The Wildlife Society.     

轻小型无人机低空遥感及其在生态学中的应用进展

无人机低空遥感系统弥补了航天和航空遥感在影像分辨率、重访周期、云层影响以及高成本等方面的不足,为中观尺度的生态学研究提供了新方法.本文介绍了轻小型无人机低空遥感系统的组成,从物种、种群、群落和生态系统尺度综述了其在生态学中的应用现状,并指出目前存在的不足和未来的发展方向,以期为无人机生态学的后续研究提供参考.无人机生态学当前面临的挑战和未来发展的方向主要有物种形态和光谱特征库的建立、物种自动识别、光谱数据与植物生理生态过程之间关系的进一步挖掘、生态系统三维立体监测、多来源多尺度遥感数据融合等.随着无人机平台技术、传感器技术以及数据传输处理技术的成熟,以无人机低空遥感技术为基础的无人机生态学将迎来发展的机遇和曙光.     

光谱多样性在植物多样性监测与评估中的应用

光谱多样性是一种基于植物反射电磁辐射光谱的生物多样性维度, 反映了不同波段光谱反射率在植物种内与种间个体之间的变异程度。由于植物反射光谱特征的差异可以综合地反映植物间生化组分和形态特征的差异, 光谱多样性成为植物多样性监测和评估的重要技术手段。该文介绍了光谱多样性的概念及其生态学意义, 比对了多源、多平台光谱数据各自的技术优势和局限性, 并概述了基于光谱多样性的植物多样性监测和评估方法及其应用, 探讨了光谱多样性整合不同维度生物多样性的能力, 展望了光谱多样性在生物多样性研究中的发展前景。光谱多样性能在多空间尺度服务于植物多样性的监测与评估, 特别是依托基于无人机技术的近地面遥感, 可以实现精细尺度植物多样性的监测与评估, 在生物多样性的保护和管理中具有广阔的应用前景。     

无人机航测在风景园林中的应用研究

近年来随着民用无人机的普及,无人机开始越来越多地应用于风景园林领域中。但目前大多数应用还停留在基础的航拍层面,对于应用潜力更大的航测层面,在风景园林行业中的应用相对较少,也更鲜为人知,现有研究更多聚焦于具体案例的应用方面,未能对其进行系统的认知和介绍。简要介绍无人机航测与遥感系统的构成及常见传感器类型,通过文献综合、项目实践等方法,系统地整理了国内外无人机航测相关的研究与应用进展,进而总结出无人机航测在风景园林中的应用可分为传统航测、倾斜摄影、多种传感器遥感3个方面。最后指出传统航测发展最为成熟,短时间内推广应用的可能性最大;倾斜摄影效率最高;多种传感器遥感未来开发潜力最大。以期对今后无人机在风景园林中的应用与研究有所启发。     

Estimation and Correction of Visibility Bias in Aerial Surveys of Wintering Ducks

Abstract: Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1–100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36–42%, and associated standard errors increased 38–55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):808–813; 2008)     

Cost and Precision Functions for Aerial Quadrat Surveys: a Case Study of Ring-Necked Ducks in Minnesota

ABSTRACT Cost considerations may be as important as precision when making survey-design choices, and the ability to accurately estimate survey costs will be essential if survey budgets become more constrained. We used data from a survey of ring-necked ducks (Aythya collaris) to illustrate how simple distance formulas can be used to construct a cost function for aerial quadrat surveys. Our cost function provided reasonable estimates of effort (hr) and costs, and allowed us to evaluate plot-size choices in terms of expected cost-precision tradeoffs. Although factors influencing costs in wildlife surveys can be complicated, we believe that cost functions deserve more attention and should be routinely considered in conjunction with traditional power analyses.     

Using super‐high resolution satellite imagery to census threatened albatrosses

This study is the first to utilize 30‐cm resolution imagery from the WorldView‐3 (WV‐3) satellite to count wildlife directly. We test the accuracy of the satellite method for directly counting individuals at a well‐studied colony of Wandering Albatross Diomedea exulans at South Georgia, and then apply it to the closely related Northern Royal Albatross Diomedea sanfordi, which is near‐endemic to the Chatham Islands and of unknown recent population status due to the remoteness and limited accessibility of the colonies. At South Georgia, satellite‐based counts were comparable to ground‐based counts of Wandering Albatross nests, with a slight over‐estimation due to the presence of non‐breeding birds. In the Chatham Islands, satellite‐based counts of Northern Royal Albatross in the 2015/2016 season were similar to ground‐based counts undertaken on the Forty‐Fours islands in 2009/2010, but much lower than ground‐based counts undertaken on The Sisters islands in 2009/2010, which is of major conservation concern for this endangered albatross species. We conclude that the ground‐breaking resolution of the newly available WV‐3 satellite will provide a step change in our ability to count albatrosses and other large birds directly from space without disturbance, at potentially lower cost and with minimal logistical effort.     

Comparison of leaf area index inversion for grassland vegetation through remotely sensed spectra by unmanned aerial vehicle and field-based spectroradiometer

Aims Remote sensing technology has been proved useful in mapping grassland vegetation properties. Spectral features of vegetation cover can be recorded by optical sensors on board of different platforms. With increasing popularity of applying unmanned aerial vehicle (UAV) to mapping plant cover, the study aims to investigate the possible applications and potential issues related to mapping leaf area index (LAI) through integration of remote sensing imagery collected by multiple sensors.     

新一代遥感技术助力生态系统生态学研究

随着气候变化和人类活动的加剧, 生态系统正处于剧烈变化中, 生态学家需要从更大的时空尺度去理解生态系统过程和变化规律, 应对全球变化带来的威胁和挑战。传统地面调查方法主要获取的是样方尺度、离散的数据, 难以满足大尺度生态系统研究对数据时空连续性的要求。相比于传统地面调查方法, 遥感技术具有实时获取、重复监测以及多时空尺度的特点, 弥补了传统地面调查方法空间观测尺度有限的缺点。遥感通过分析电磁波信息从而识别地物属性和特征, 反演生态系统组成、能量流动和物质循环过程中的关键要素, 已逐渐成为生态学研究中必不可少的数据来源。近年来, 随着激光雷达、日光诱导叶绿素荧光等新型遥感技术以及无人机、背包等近地面遥感平台的发展, 个人化、定制化的近地面遥感观测逐渐成熟, 新一代遥感技术正在推动遥感信息“二维向三维”的转变, 为传统样地观测与卫星遥感之间搭建了尺度推绎桥梁, 这也给生态系统生态学带来了新的机遇, 推动生态系统生态学向多尺度、多过程、多学科、多途径发展。因此, 该文从生态系统生态学角度出发, 重点关注陆地生态系统中生物组分, 并分别从生态系统类型、结构、功能和生物多样性等方面, 结合作者在实际研究工作中的主要成果和该领域国际前沿动态, 阐述遥感技术在生态系统生态学中的研究现状并指出我国生态系统遥感监测领域发展方向及亟待解决的问题。     

Estimation of Detection Probability in Manatee Aerial Surveys at a Winter Aggregation Site

Abstract: Estimating components of detection probability is crucial to improving the design of aerial surveys for wildlife populations, and this is especially true for species of marine mammals that are threatened or endangered. To evaluate the probability that Florida manatees (Trichechus manatus latirostris) will be detected by observers during aerial surveys, we conducted 6 series of survey flights, during mornings and afternoons on 14-16 consecutive days over the Tampa Electric Company's (TECO) Big Bend power plant discharge canal in Tampa Bay, Florida, USA (winter 2000 through 2003). Our objective was to understand how our ability to detect manatees at a winter aggregation site affects aerial survey counts, so that we may improve techniques for estimating manatee population size. We estimated the probability that manatees would be present at the warm-water discharge of the plant during winter cold fronts and estimated the overall detection probability of manatees present at the plant and the 2 components that make up the probability of detection (the probability of being available and the probability of being detected given they are available). We used telemetry tags and marker flags (n = 15) to facilitate capture-recapture analyses. The probability that marked manatees would be at the plant varied from 48% to 68% across flight series and was inversely related to the ambient water temperature. Based on sightings of marked animals, estimates of the overall probability of detecting a manatee ranged from 45% to 69% across flight series (x̄ = 58%, n = 6). The probability that a manatee would be available to an observer ranged from 73% to 94% across flight series (x̄ = 83%) but was constant among years (83%, 81%, and 78%; x̄ = 81%). The probability that an available manatee would be detected by an aerial observer was variable across flight series (55-95%) and years (73%, 86%, and 66%, x̄ = 73%). Independent estimates of the probability that a manatee would be available to the observer on one pass were obtained from time-depth data loggers and ranged from 5% to 33% (x̄ = 19%, SE = 3.7%), and the probability that a manatee would be available during ≥1 of 10 passes ranged from 41% to 98% (x̄ = 88%, 95% confidence bounds 0.71-0.95). We adjusted survey counts using measures of detectability. Although corrected counts presented here are site-specific, adjusting counts based on detection probability will greatly improve reliability of population estimates from all aerial surveys. Special sampling to estimate components of detection probability should be built into all aerial surveys to ensure that reliable and unbiased information on species abundance is used to evaluate wildlife populations.     

Fine‐scale bird monitoring from light unmanned aircraft systems

Unmanned aircraft systems (UAS) are remote‐controlled devices capable of collecting information from difficult‐to‐access places while minimizing disturbance. Although UAS are increasingly used in many research disciplines, their application to wildlife research remains to be explored in depth. Here, we report on the use of a small UAS to monitor temporal changes in breeding population size in a Black‐headed Gull Chroicocephalus ridibundus colony. This method makes it possible to obtain georeferenced data on nest locations without causing colony disturbance, which would not otherwise be possible via direct ground observations.     

Mapping Tropical Forest Trees Using High‐Resolution Aerial Digital Photographs

The spatial arrangement of tree species is a key aspect of community ecology. Because tree species in tropical forests occur at low densities, it is logistically challenging to measure distributions across large areas. In this study, we evaluated the potential use of canopy tree crown maps, derived from high‐resolution aerial digital photographs, as a relatively simple method for measuring large‐scale tree distributions. At Barro Colorado Island, Panama, we used high‐resolution aerial digital photographs (~0.129 m/pixel) to identify tree species and map crown distributions of four target tree species. We determined crown mapping accuracy by comparing aerial and ground‐mapped distributions and tested whether the spatial characteristics of the crown maps reflect those of the ground‐mapped trees. Nearly a quarter (22%) of the common canopy species had sufficiently distinctive crowns to be good candidates for reliable mapping. The errors of commission (crowns misidentified as a target species) were relatively low, but the errors of omission (missed canopy trees of the target species) were high. Only 40 percent of canopy individuals were mapped on the air photographs. Despite failing to accurately predict exact abundances of canopy trees, crown distributions accurately reproduced the clumping patterns and spatial autocorrelation features of three of four tree species and predicted areas of high and low abundance. We discuss a range of ecological and forest management applications for which this method can be useful.     

Validating Aerial Photographic Mark-Recapture for Naturally Marked Feral Horses

ABSTRACT Accurately estimating large mammal populations is a difficult challenge because species of interest often occupy vast areas and exhibit low and heterogeneous visibility. Population estimation techniques using aerial surveys and statistical design and analysis methods provide a means for meeting this challenge, yet they have only rarely been validated because wild populations of known size suitable for field tests are rare. Our study presents field validations of a photographic aerial mark-recapture technique that takes advantage of the recognizable natural markings on free-roaming feral horses (Equus caballus) to accurately identify individual animals and groups of animals sighted on multiple occasions. The 3 small populations of feral horses (<400 animals each) in the western United States used in the study were all closely monitored on a weekly basis by local researchers, thus providing test populations of known size. We were able to accurately estimate these population sizes with aerial surveys, despite rugged terrain and dense vegetation that created substantial heterogeneity of sighting probability among horse groups. Our best estimates at the 3 sites were within −6.7%, 2.6%, and −8.6% of known truth (-4.2% mean error, 6.0% mean absolute error). In contrast, we found undercount bias as large as 32% before any statistical corrections. The necessary corrections varied both temporally and spatially, in response to previous sighting history (behavioral response), and by the number of horses in a group. Despite modeling some of the differences in horse-group visibility with sighting covariates, we found substantial residual unmodeled heterogeneity that contributed to underestimation of the true population by as much as 22.7% when we used models that did not fully account for these unmeasured sources. We also found that the cost of the accurate and validated methods presented here is comparable to that of raw count (so called, census) methods commonly employed across feral horse ranges in 10 western states. We believe this technique can assist managers in accurately estimating many feral horse populations and could be applied to other species with sufficiently diverse and distinguishable visible markings.