遥感技术在鸟类生态学研究中的应用

获取鸟类活动及生境信息是鸟类生态学研究的基础, 而遥感技术弥补了传统野外调查方法的缺陷, 提供了获取多种信息的新途径。应用遥感技术的鸟类生态学研究热点从最初的种群行为观察, 到栖息地选择, 再到生境适宜性、破碎化及人为干扰探究等, 随着技术的不断发展也在扩展和变化。不同波段或组合下的遥感技术各有所长。光学遥感应用广泛, 尤其是信息量较大的红外波段图像和作为野外鸟巢及物种活动监测常用工具的红外相机; 多光谱图像常用于栖息地制图以及地物识别, 高空间分辨率的数据甚至可对鸟类种群进行直接计数; 高光谱数据则可对光谱特征相似的地物进行更为精确的区分和反演; 激光雷达遥感主要用于栖息地植被结构的三维探测, 为了解鸟类栖息地选择提供更好的依据。微波遥感在飞鸟探测上应用颇多, 近年来多极化数据在复杂栖息地精确制图上也具有优势, 但成本较高、解译复杂且推广度较低。在实际应用中, 遥感数据时空尺度的选择会影响研究结果, 部分遥感反演参数也缺乏生态学意义。多源遥感数据的结合应用能够提升制图分类的精度, 实现数据的时空分辨率互补, 优化鸟类生态研究所需参数。未来的遥感技术在鸟类生态学中的应用应致力于提供更加明确的光谱信息、相对简便的解译方法, 以及更为合理的多源数据组合方式等。     

浒苔遥感监测研究进展

浒苔大规模集聚形成的绿潮灾害是海洋生态系统主要生态环境问题之一,基于卫星遥感影像监测浒苔及其扩展动态已成为一种及时有效的手段。对国内外浒苔遥感监测方面文献进行归纳整理,认为光学遥感数据、多波段比值法是最常用的遥感数据和监测方法。对遥感监测浒苔机理进行了阐述,并对分类方法进行评价认为监督分类法解译精度不高。目前单波段阈值法和多波段比值法应用广泛,但在监测漂浮浒苔和混合象元解译存在不足。辐射传输模型法能有效提高信息解译的精度,但还处于起步阶段。遥感监测浒苔灾害的未来发展需要提高影像空间分辨率,深入研究监测方法,进行多种平台和多源遥感数据相结合,并由定性走向定量,从而建立健全遥感监测预警系统。     

三江源地区雪豹保护优先区规划

为了将有限资源合理投放到关键区域, 实现物种保护成效的最大化, 找出质量最好的栖息地及它们之间的迁徙通道是制定保护规划的第一步。本研究以三江源的雪豹(Panthera uncia)栖息地为对象, 基于野外调查数据和高分辨率卫星遥感数据, 利用物种分布模型、保护规划模型和连通度分析工具, 找出了三江源地区雪豹的核心栖息地分布和潜在迁徙通道位置, 分析了目前保护中的潜在威胁, 并提出了针对三江源西、中、东三块区域的不同保护对策。结果表明: (1)三江源西部核心栖息地比较小而破碎, 但迁徙通道较多且没有明显窄点, 未来应关注青藏线的潜在阻碍作用, 同时应防范道路沿线的野生动物盗猎; (2)中部区域横跨玉树-杂多-囊谦的雪豹栖息地是三江源最大的核心雪豹栖息地, 在连通其他种群中也处于中心地位, 应通过种群监测确定其健康稳定, 对开发、偷猎等威胁防微杜渐, 保持其源种群的作用; (3)东部区域人口密度高, 受人类活动的影响最大, 需保证阿尼玛卿、年保玉则两块核心栖息地的质量, 并重点监测甘德县境内的省道处雪豹的迁徙通道是否畅通。三江源地区雪豹栖息地总体质量较好, 建议将维持核心源种群的稳定性, 保持种群间迁徙通道的畅通作为三江源的雪豹景观保护工作的整体目标。未来应充分利用天地一体化监测手段, 开展重要保护物种栖息地状况的评估和预警, 尤其是非保护地区域物种核心栖息地的开发建设活动。     

河流生物栖息地调查及评估方法

河流生物栖息地的研究是河流生态修复和流域环境管理的重要基础.本文概述了河流生物栖息地的分类、调查方法（包括调查范围、采样密度、采样季节和数据记录方式）以及调查数据处理等;并从物种与栖息地适宜性关系的角度出发,对目前国际上主要的栖息地评估方法（评估模型）的应用特点和应用范围进行了评述;最后,在探讨发达国家关于栖息地研究现状的基础上,提出了我国河流治理应从生物栖息地角度出发进行生态恢复建设.     

四川山鹧鸪栖息地分析与预测

四川山鹧鸪Arborophila rufipectus属鸡形目雉科山鹧鸪属,是我国特产珍稀鸟类,国家一级重点保护野生动物,IUCN濒危物种。本文应用卫星遥感影像解译技术对该物种的现实栖息地和潜在栖息地进行了分析和预测。结果表明,现存四川山鹧鸪分布格局自四川中南部向云南东北延伸,跨越金沙江,呈现西北-东南走向,分布区涉及大相岭山系南缘、小相岭山系东缘、凉山山系东北部、乌蒙山山系西部,行政区域涉及2省5市(州)19县(区)。栖息地由10片现实栖息地和36片潜在栖息地组成,总面积约5869 km2。"甘洛-金口河-峨边-马边-美姑"片和"雷波-马边-屏山"片是四川省境内呈南北布局的两大核心分布区,"绥江-永善-水富-盐津-大关"片为云南省境内的核心分布区。     

岷山山系南端大熊猫栖息地分布分析

基于大熊猫Ailuropoda melanoleuca野外分布数据及环境变量,利用MaxEnt模型对岷山山系南端的大熊猫适宜栖息地分布进行了预测及分析。结果显示:研究区域内有大熊猫适宜栖息地330.9 km~2,占研究区域内保护区总面积的23.2%;并且龙溪虹口-白水河-九顶山一线的大熊猫的栖息地存在一定的破碎化现象。建议继续加强对大熊猫栖息地的保护,减少人为干扰,促进大熊猫栖息地的恢复,增进各相邻保护区间的沟通交流、数据分享,更准确掌握、了解该区域大熊猫的动态。     

地理信息系统在野生动物研究中的应用

简要地介绍了地理信息系统的功能及其在动物生态学研究、野生动物保护和资源管理中的应用。它在动物迁徙研究、动物栖息地选择研究、动物栖息地利用研究、动物种群数量调查、动物群落研究、动物栖息地状况评估和监测、动物种群生存力分析、建立物种分布数据库等多方面都有极大的应用价值。     

古生物化石遥感监测中02C卫星数据的应用

随着我国科学技术的不断发展和进步,我国国产卫星的研究和发展也已取得了相当令人满意的成果。其中,02C卫星数据作为该项研究工程中新兴的先进技术,现已被广泛应用于遥感监测中。本文主要以关岭地区的古生物化石为研究对象,详细分析了针对该对象进行遥感监测中02C卫星数据的选择、处理以及解译等具体应用,以期为广大古生物化石研究者提供一定的参考意见和建议。     

GPS项圈系统在野生动物管理与监测中的应用

野生动物管理与监测是生物多样性保护工作的重要内容。而监测手段决定了保护工作中收集数据的质量和数量。收集动物活动位点数据是野生动物管理与监测中的一项重要工作,可通过样线法收集动物活动痕迹(实体)位点或采用无线电遥测获取动物的活动位点等,采用这些位点数据可以研究野生动物种群数量、家域、运动、栖息地利用和选择等。通过给野生动物佩戴GPS项圈,利用GPS项圈系统进行定位记录其活动位点,较前述常规方法更为便利,能高效地收集大量高质量位点,这种方法可以为野生动物的管理与生物多样性保护提供更为可靠的数据基础。     

甘肃盐池湾黑颈鹤筑巢栖息地偏好及人为干扰的影响

作为高原旗舰物种, 黑颈鹤(Grus nigricolli)是反映高原生态健康状况的重要参考。为了解黑颈鹤如何在多因素作用下适应人类改造过的栖息地环境, 本研究利用遥感解译、最近邻分析与随机森林模型对繁殖于甘肃盐池湾国家级自然保护区党河湿地的黑颈鹤的筑巢栖息地偏好及人为干扰进行研究。2019年和2020年每年的4-9月在党河湿地内对巢位点等数据进行收集。研究结果表明: 党河湿地内巢址与人为干扰的分布位置明显不同, 两者的主要分布区呈现镶嵌状。距深水沼泽距离、距浅水沼泽距离与距湖泊距离是影响黑颈鹤筑巢栖息地选择最关键的3个环境因子。黑颈鹤筑巢时偏好在距离深水沼泽< 125 m、距离浅水沼泽< 130 m、距离湖泊< 270 m的区域内筑巢。黑颈鹤对沼泽、湖泊等资源的偏好是其巢址分布格局的主要驱动力, 而房屋与公路等人为干扰对栖息地选择的影响很小。黑颈鹤筑巢时强烈偏好的栖息地在湿地内占比低、分布聚集且适宜范围有限, 繁殖区域较狭窄。黑颈鹤巢址间距离的上升表明黑颈鹤栖息地质量可能有所下降, 牲畜数量的增长、冬季牧场的多季节利用以及气候变化可能是主要原因。建议在党河湿地内不新增房屋及公路等人为干扰, 同时继续适当限牧, 并给予牧民充足的经济补偿。     

Integrating field survey and orthophoto information to monitor coastal habitats — A pilot study to develop methods and resolve key issues

Implementation of mapping and monitoring is necessary to supply sufficient information to guide an effective management of species, habitats and landscapes. Coastal ecosystems can be difficult to monitor effectively in the field due to spatially discontinuous and unpredictable processes such as encroachment, erosion and succession, while coverage of large extents is very expensive. Remote sensing-based monitoring provides an alternative, but satellite image data is often too expensive or too coarse in spatial resolution to detect fine-scale habitat structures. Using Danish coastal habitats as a case, a method is presented for monitoring habitat types and fine-scale structures, based on integration of field-acquired habitat characteristics with the habitat information interpreted from sub-meter RGB/NIR aerial imagery and digital elevation model data. Initial pilot studies show good correspondence between field-observed structure elements and structures delineated through object-based image analysis, while initial classifications results suggest possibilities of discriminating between different types of shrubs, herb communities and non-vegetated structures.     

Temporal transferability of wildlife habitat models: implications for habitat monitoring

Aim Temporal transferability is an important issue when habitat models are used beyond the time frame corresponding to model development, but has not received enough attention, particularly in the context of habitat monitoring. While the combination of remote sensing technology and habitat modelling provides a useful tool for habitat monitoring, the effect of incorporating remotely sensed data on model transferability is unclear. Therefore, our objectives were to assess how different satellite‐derived variables affect temporal transferability of habitat models and their usefulness for habitat monitoring. Location Wolong Nature Reserve, Sichuan Province, China. Methods We modelled giant panda habitat with the maximum entropy algorithm using panda presence data collected in two time periods and four different sets of predictor variables representing land surface phenology. Each predictor variable set contained either a time series of smoothed wide dynamic range vegetation index (WDRVI) or 11 phenology metrics, both derived from single‐year or multi‐year (i.e. 3‐year) remotely sensed imagery acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS). We evaluated the ability of models obtained with these four variable sets to predict giant panda habitat within and across time periods by using threshold‐independent and threshold‐dependent evaluation methods and five indices of temporal transferability. Results Our results showed that models developed with the four variable sets were all useful for characterizing and monitoring giant panda habitat. However, the models developed using multi‐year data exhibited significantly higher temporal transferability than those developed using single‐year data. In addition, models developed with phenology metrics, especially when using multi‐year data, exhibited significantly higher temporal transferability than those developed with the time series. Main conclusions The integration of land surface phenology, captured by high temporal resolution remotely sensed imagery, with habitat modelling constitutes a suitable tool for characterizing wildlife habitat and monitoring its temporal dynamics. Using multi‐year phenology metrics reduces model complexity, multicollinearity among predictor variables and variability caused by inter‐annual climatic fluctuations, thereby increasing the temporal transferability of models. This study provides useful guidance for habitat monitoring through the integration of remote sensing technology and habitat modelling, which may be useful for the conservation of the giant panda and many other species.     

Predictability of reef fish diversity and abundance using remote sensing data in Diego Garcia (Chagos Archipelago)

The diversity, abundance and distribution of reef fish are related to heterogeneity and physical complexity of benthic habitat. However, the field effort required to evaluate these aspects of the benthos in situ, at the scale of entire reefscapes, is greatly constrained by logistical and resource limitations. With moderate ground truthing, both substratum type and seabed topography are amenable to monitoring using satellite data. Here, remote sensing imagery was used to resolve the bathymetry and benthic character of a reef system in Diego Garcia (British Indian Ocean Territory). Replicate fish counts were made at seven measurement stations across the study area using visual census. Monte Carlo simulation revealed that species richness and abundance of several guilds and size groupings of reef fish appraised in situ were correlated with the satellite-derived seabed parameters over areas of seafloor as large as 5,030 m². The study suggests that satellite remote sensing is capable of predicting habitat complexity at a scale relevant to fish. Furthermore, as larger size classes of fish were better predicted with the satellite habitat complexity data, this technique could be used to predict fish stocks and identify potential sites for marine protected areas where intensive field surveys are not practical.     

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.     

Spatial indicators for nature conservation from European to local scale

The paper presents an overview of the objectives and exemplary results of the FP 5 project “Spatial Indicators for European Nature Conservation” (SPIN). The SPIN project is focused on the development and testing of advanced classification methods and spatial indicators based on multisensor satellite data and GIS to accomplish monitoring and management tasks in the context of Natura 2000 and nature conservation. A representative selection of eight regional test areas covers a pan-European network and allows comparative investigations to provide accepted recommendations for regional and European nature conservation. The selected results of four case studies are presented and discussed. The range of work covers the production of regional and local habitat maps by object-oriented classification, a case-based reasoning method for change detection as a management support tool for planning and regulating local land use, the selection and application of structural indicators for the monitoring of Natura 2000 habitats and the downscaling and disaggregation of soil information. Results and the further implementation of presented methods are discussed in the conclusions.     

Satellite remote sensing in monitoring change of seabirds: use of Spot Image in king penguin population increase at Ile aux Cochons,Crozet Archipelago

The king penguin colony at Ile aux Cochons, Crozet Archipelago (southern Indian Ocean) is the largest in the world. The change in its surface area was investigated by means of satellite remote sensing using spot scene. The satellite picture enabled us to locate the colony and to determine that the surface area occupied by the colony has increased by 56% between 1962 and 1988. The increase in the surface area occupied by the colony was confirmed by a map realised in 1982 (by the Institut Géographique National). The high resolution system available on the spot system which allows at present at 10 m ground resolution, and 5 m in the near future, can thus be a useful tool for monitoring medium to long-term changes in marine bird populations breeding in colonies composed of birds spaced a constant distance from one another. Based on the surface area occupied by the colony and the published data on the population size on Possession Island, as well as information on the breeding frequency of the species, we estimated that the total breeding population is about 1,000,000 pairs for the whole archipelago and that about 70% of birds breed at Ile aux Cochons.     

Object-oriented methods for habitat mapping at multiple scales – Case studies from Northern Germany and Wye Downs, UK

This paper presents an application of object-oriented techniques for habitat classification based on remotely sensed images and ancillary data. The study reports the results of habitat mapping at multiple scales using Earth Observation (EO) data at various spatial resolutions and multi temporal acquisition dates. We investigate the role of object texture and context in classification as well as the value of integrating knowledge from ancillary data sources. Habitat maps were produced at regional and local scales in two case studies; Schleswig-Holstein, Germany and Wye Downs, United Kingdom. At the regional scale, the main task was the development of a consistent object-oriented classification scheme that is transferable to satellite images for other years. This is demonstrated for a time series of Landsat TM/ETM+ scenes. At the local scale, investigations focus on the development of appropriate object-oriented rule networks for the detailed mapping of habitats, e.g. dry grasslands and wetlands using very high resolution satellite and airborne scanner images. The results are evaluated using statistical accuracy assessment and visual comparison with traditional field-based habitat maps. Whereas the application of traditional pixel-based classification result in a pixelised (salt and pepper) representation of land cover, the object-based classification technique result in solid habitat objects allowing easy integration into a vector-GIS for further analysis. The level of detail obtained at the local scale is comparable to that achieved by visual interpretation of aerial photographs or field-based mapping and also retains spatially explicit, fine scale information such as scrub encroachment or ecotone patterns within habitats.     

Spatial patterns of diatom diversity and community structure in ancient Lake Ohrid

For effective lakes’ management, high-frequent water quality data on a synoptic scale are essential. The aim of this study is to test the suitability of the latest generation of satellite sensors to provide information on lake water quality parameters for the five largest Italian subalpine lakes. In situ data of phytoplankton composition, chlorophyll-a (chl-a) concentration and water reflectance were used in synergy with satellite observations to map some algal blooms in 2016. Chl-a concentration maps were derived from satellite data by applying a bio-optical model to satellite data, previously corrected for atmospheric effects. Results were compared with in situ data, showing good agreement. The shape and magnitude of water reflectance from different satellite data were consistent. Output chl-a concentration maps, show the distribution within each lake during blooming events, suggesting a synoptic view is required for these events monitoring. Maps show the dynamic of bloom events with concentration increasing from 2 up to 7 mg m^?3 and dropping again to initial value in less than 20 days. Latest generation sensors were shown to be valuable tools for lakes monitoring, thanks to frequent, free of charge data availability over long time periods.     

Characterization of moorland vegetation and the prediction of bird abundance using remote sensing

Aims To characterize and identify upland vegetation composition and height from a satellite image, and assess whether the resulting vegetation maps are accurate enough for predictions of bird abundance. Location South‐east Scotland, UK. Methods Fine‐taxa vegetation data collected using point samples were used for a supervised classification of a Landsat 7 image, while linear regression was used to model vegetation height over the same image. Generalized linear models describing bird abundance were developed using field‐collected bird and vegetation data. The satellite‐derived vegetation data were substituted into these models and efficacy was examined. Results The accuracy of the classification was tested over both the training and a set of test plots, and showed that more common vegetation types could be predicted accurately. Attempts to estimate the heights of both dwarf shrub and graminoid vegetation from satellite data produced significant, but weak, correlations between observed and predicted height. When these outputs were used in bird abundance–habitat models, bird abundance predicted using satellite‐derived vegetation data was very similar to that obtained when the field‐collected data were used for one bird species, but poor estimates of vegetation height produced from the satellite data resulted in a poor abundance prediction for another. Conclusions This pilot study suggests that it is possible to identify moorland vegetation to a fine‐taxa level using point samples, and that it may be possible to derive information on vegetation height, although more appropriate field‐collected data are needed to examine this further. While remote sensing may have limitations compared with relatively fine‐scale fieldwork, when used at relatively large scales and in conjunction with robust bird abundance–habitat association models, it may facilitate the mapping of moorland bird abundance across large areas.