遥感用于森林生物多样性监测的进展

随着物种和栖息地的丧失,全球范围的生物多样性保护已经成为迫切的需要。航空航天技术的迅猛发展使遥感成为能提供跨越不同时空尺度监测陆地生态系统生物多样性的重要工具,这方面的研究在欧美等国已经有了小范围的开展,在国内刚刚起步。国外关于生物多样性遥感探测的方法基本有3种:1.利用遥感数据直接对物种或生境制图,进而估算生物多样性;2 .建立遥感数据的光谱反射率与地面观测物种多样性的关系模型;3.与野外调查数据结合直接在遥感数据上进行生物多样性指数制图。研究表明,物种直接制图法只能应用于较小的范围;生境制图的方法,应用广泛,技术相对成熟,研究范围局限于几百公里的范畴,但不能获取生境内部的多样性信息。光谱模型技术目前正处于探索阶段,对于植被复杂、生物多样性高的地域,具有较大的应用潜力。在遥感数据上直接进行生物多样性制图在加拿大已经得到了应用。     

盖度与冠层水深对沉水植物水盾草光谱特性的影响

遥感技术可应用于大尺度实时监测沉水植物的分布与生长状况。然而沉水植物的光谱特征受其冠层在水下深度的影响,从而影响湖泊和河流中沉水植物的遥感影像解译与信息提取。应用地物光谱仪,通过野外原位测定和室外控制试验,实测了沉水植物水盾草(Cabomba caroliniana)群落冠层在水下不同深度的反射光谱,分析了冠层水深对水盾草反射光谱的影响,并建立了基于光谱反射率和冠层水深的水盾草群落盖度反演模型。研究结果表明(1)不同盖度的水盾草群落光谱反射率的基本特征主要体现在绿光和近红外波段;(2)水盾草群落的光谱反射率与冠层水深基本呈负相关,相同盖度水盾草群落的光谱反射率随冠层水深的增加而减小,在近红外波段尤其明显;(3)水盾草群落冠层水深越小,其盖度与光谱反射率的相关性越强,且水盾草群落盖度越大,其光谱反射率与冠层水深的相关性越显著;(4)水盾草光谱反射率与盖度相关的最佳波段在692—898 nm,与冠层水深相关最佳的波段在710 nm和806 nm附近;(5)在710 nm和806 nm处建立的结合冠层水深的修正模型,无论是回归方程决定系数(R2),还是水盾草群落盖度的反演精度都明显高于仅用光谱反射率反演盖度的简单模型,因此可有效减除冠层水深对反演精度的影响。本研究的结果可为遥感监测沉水植物的分布和动态变化,以及沉水植物生物物理参量反演提供科学依据。     

大型沉水植物苦草的光谱特征识别

地物特征与其光谱特征的关系是解译遥感影像的关键.利用地物光谱仪在实验室和上海“梦清园”人工湿地中,分别实测了不同盖度沉水植物苦草的反射光谱特征.结果表明随着苦草盖度的增加,其光谱反射率也相应增加,不同盖度苦草的光谱反射率差异主要表现在500～650 nm和700～900 nm 波段范围.受水体环境影响,实验室模拟试验与室外控制试验测得的苦草光谱反射率差异主要表现在近红外波段（700～900 nm）.分别将苦草的不同盖度与其在QuickBird多光谱遥感影像4个波段与盖度相关性最大波段处的光谱反射率进行回归分析,得到了较好的线性关系.应用回归分析得到的线性方程,可以根据测定的光谱反射率定量反演水体中的苦草盖度.研究结果可为监测沉水植物的高光谱遥感影像判读和解译分类提供技术支撑,为大尺度遥感监测沉水植物的分布和动态变化提供科学依据.     

遥感反演植被理化参数的光谱和空间尺度效应

植被理化参数是生态系统中碳和养分等物质循环与能量交换的重要指标,利用遥感技术反演是获取区域及全球植被理化参数的重要手段,但光谱和空间尺度效应的存在,限制了源自不同遥感传感器植被理化参数产品的统一应用。阐述了遥感反演植被理化参数光谱尺度效应的概念及其产生原因,主要从光谱波段位置和波段宽度两方面对国内外相关研究进行了介绍和评述。同时,从遥感反演植被理化参数的空间尺度效应产生原因、空间异质性描述方法和空间尺度转换方法等方面对其国内外研究现状进行了归纳和评述。最后,总结了遥感反演植被理化参数光谱和空间尺度效应研究的不足之处和发展趋势,并指出光谱和空间耦合效应的研究将是一大趋势,而在生态学等领域形成的尺度效应研究的理论和方法也值得借鉴参考。     

无人机遥感技术在景观生态学中的应用

野外数据的获取是生态学研究的挑战之一,而通过遥感技术能够实现对地球表面的多面立体观测,获取丰富多样的空间信息数据,开展从微观到宏观不同尺度上的景观单元(包括物种、种群、群落、生态系统等)的空间关系研究。传统卫星遥感影像受空间和时间分辨率的限制,难以满足局域尺度或者时间序列上的景观空间生态学研究需求。无人机遥感技术为生态学研究的野外数据获取提供了一种新方法,以其灵活、高效、简便等特点弥补了传统卫星遥感的空间分辨率低、重访周期长、云雾影响等方面的不足,在景观空间生态学研究中受到越来越多的关注。简要介绍无人机类型及其搭载常见的传感器类型,分别从不同尺度的景观单元,即物种、种群、群落以及生态系统水平上探讨其应用进展,并指出当前无人机技术在景观生态学研究中存在的挑战与困难,同时展望了未来可能的研究热点,以期对今后无人机遥感技术在景观生态学领域的应用研究有所启发。     

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.     

UAVs as remote sensing platforms in plant ecology: review of applications and challenges

无人机遥感在植物生态学中的应用与挑战 无人机为获取高时空分辨率的遥感数据提供了经济灵活的工具,为植物生态学家开展从个体到区域尺度的生态学研究提供了新的机遇和手段。但作为一种新兴的技术手段,当前无人机遥感在植物生态学中的应用仍充满了挑战,植物生态学的科研需求与无人机遥感的生态应用需要更为深入的融合。本文综述了无人机遥感技术在植物生态学中的应用,展望了无人机在植物生态学研究中的应用前景。在所综述的400篇文献中,59%的文章发表于非植物生态学领域的遥感类期刊,遥感学者与生态学者的关注点存在较大差异。当前的研究集中在无人机遥感的技术层面,如数据处理和遥感反演方法等,对生态学问题本身的关注较少。综述的文献中,61%的研究案例集中在群落尺度,可见光(RGB)相机和多光谱相机是最常用的传感器类型(75%)。无人机遥感数据中蕴藏着诸多待挖掘的、有重要意义的生态参数,这些参数有助于我们识别林窗的几何特征,构建林冠的化学组合,更好地了解林冠表面的不规则性和群落的异质性。无人机遥感技术在植物生态学研究中的深入应用,需要集植物生态学家和遥感专家之合 力共同推进。     

崇明东滩盐沼土壤重金属含量的高光谱估算模型

高光谱遥感技术现已被广泛应用于地表矿物成份的识别以及它的含量、植物化学成份的估测,土壤调查等方面的研究。利用地物光谱仪测定了长江口崇明东滩盐沼土壤的光谱信息,根据EO-1卫星Hyperion高光谱仪的波段设置,提取各波段平均波长的光谱反射率,并结合实验室实测的土壤重金属含量,应用偏最小二乘法(PLS),预测盐沼土壤重金属含量。结果表明,盐沼土壤重金属Zn、Cr、Cu预测值与实测值相关系数分别达到0.822**、0.761**和0.775**,均为极显著相关,其实测值与预测值的平均相对误差为4%、3%和4%。研究结果可以为高光谱遥感技术反演盐沼土壤重金属含量,进一步应用空间或航空遥感进行大尺度环境污染遥感、遥测信息提取和反演提供技术支撑。     

基于实地调查和高光谱数据的浑善达克沙地中部植物alpha多样性遥感估测

植物群落物种多样性的快速无损估测一直是近几十年生态学领域的热点研究问题。相对于大尺度的卫星遥感数据,高光谱遥感数据具有光谱和空间分辨率高的优势。采用ASD HH2便携式高光谱仪,收集浑善达克沙地中部120个样方的高光谱数据,并对样方的alpha多样性指数进行同步测定。对高光谱遥感数据进行预处理,采用相关性分析、主成分分析和经验波段筛选法,从数百个波段中选择敏感波段。采用90个样方的高光谱数据作为训练样本,对筛选的敏感波段进行多元线性逐步回归分析,获得12个回归模型。采用另外30个样方的高光谱数据作为验证样本,对回归模型的拟合效果进行检验。结果发现,采用主成分分析法提取敏感波段的回归模型拟合效果最好,Pielou指数、Shannon-Wiener指数和Simpson指数拟合均达到显著水平。对我国植物物种多样性微尺度的快速评估和高光谱遥感具有一定参考意义,并对未来植物多样性高光谱遥感研究提出了建议。     

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。     

Remote sensing‐based landscape indicators for the evaluation of threatened‐bird habitats in a tropical forest

Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space‐borne optical (Landsat), ALOS‐PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest—agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature (IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR‐derived forest structure and Landsat‐derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the avian species. This work also provides insight that retention of forest patches, including degraded and isolated forest patches in addition to large contiguous forest patches, can facilitate bird species retention within tropical agricultural landscapes. It also demonstrates the effective use of RS data in distinguishing between forests that have undergone varying levels of degradation and identifying the habitat preferences of different bird species. Practical conservation management planning endeavors can use such data for both landscape scale monitoring and habitat mapping.     

A review and a framework for the integration of biodiversity monitoring at the habitat level

The monitoring of biodiversity at the level of habitats is becoming widespread in Europe and elsewhere as countries establish national habitat monitoring systems and various organisations initiate regional and local schemes. Parallel to this growth, it is increasingly important to address biodiversity changes on large spatial (e.g. continental) and temporal (e.g. decade-long) scales, which requires the integration of currently ongoing monitoring efforts. Here we review habitat monitoring and develop a framework for integrating data or activities across habitat monitoring schemes. We first identify three basic properties of monitoring activities: spatial aspect (explicitly spatial vs. non-spatial), documentation of spatial variation (field mapping vs. remote sensing) and coverage of habitats (all habitats or specific habitats in an area), and six classes of monitoring schemes based on these properties. Then we explore tasks essential for integrating schemes both within and across the major classes. Finally, we evaluate the need and potential for integration of currently existing schemes by drawing on data collected on European habitat monitoring in the EuMon project. Our results suggest a dire need for integration if we are to measure biodiversity changes across large spatial and temporal scales regarding the 2010 target and beyond. We also make recommendations for an integrated pan-European habitat monitoring scheme. Such a scheme should be based on remote sensing to record changes in land cover and habitat types over large scales, with complementary field mapping using unified methodology to provide ground truthing and to monitor small-scale changes, at least in habitat types of conservation importance.     

Review of coral reef ecosystem remote sensing

Coral reef communities face unprecedented pressures at local, regional and global scales as a consequence of climate change and anthropogenic disturbance. Remote sensing, from satellites or aircraft, is possibly the only means to measure the effects of such stresses at appropriately large spatial scales. In the past 30 years, remote sensing of coral reefs has made rapid progress. However, the current technology is still not mature enough to monitor complicated coral reef ecosystems. Compared with foreign research in this field, our work lags far behind. There are still deficiencies in many aspects, such as basic data collection, theoretical research and platform construction. In our nation, it is even unclear how coral reefs disperse and where they may be unhealthy. In this paper, general characteristics of coral reef ecosystems and spectral features of different reef benthos have been summarized, based initially on a review of relevant literature in recent years. Based on the spectral separability of different reef types or benthos, remote sensing can be used to monitor two aspects of coral reefs: (1) Measurement of the ecological properties of reefs. (2) Health assessment of the coral reef ecosystem. In the first part, optical remote sensing methods are widely used to map reef geomorphology and habitats or biotopes. The investigation of geomorphologic zonation has proven to be one of the most successful applications, as different geomorphologic zones are associated with characteristic benthic community structures and occur at spatial scales of tens to hundreds of meters, they are amenable to remote detection by moderate to high resolution sensors. With more and more attention on the ecological problems of coral reefs, a number of studies have used high resolution sensors to map reef communities. The number of classes distinguishable depends on many factors, including the platforms, resolution (spectral, spatial and temporal resolution) and environmental conditions (water depth, water clarity, surface roughness, etc.). Compared with deep water color remote sensing, or terrestrial remote sensing, three techniques for the measurement of reef ecological properties are examined in this paper: (1) Coral reef classification system using remote sensing. (2) Techniques of sea surface correction and water column correction. (3) Techniques of coral reef information extraction from images. In terms of the complexity of coral reef ecosystems, the current techniques still need further improvement or optimization. In the health assessment of coral reef ecosystems, there are two ways to carry out the monitoring using remote sensing: (1) Monitoring the pigment or symbiotic zooxanthellae contents in corals. (2) Measuring the environmental properties of reefs. The first way is theoretically feasible, but difficult to achieve in practice. Currently, most reef health assessments are carried out by measuring environmental parameters, including sea surface temperature, solar radiation, ultraviolet radiation, water color, wind speed and direction, rainfall, ocean acidification, sea level, etc., of which sea surface temperature has been routinely measured by NOAA to monitor coral bleaching. In addition to the contents above, this article puts forward five main prospects for development in the future: (1) Establishment of a coral reef classification system using remote sensing. (2) Satellite launch for monitoring coral reefs. (3) Theoretical and methodological development. (4) Establishment of a spectral database for different reef benthos. (5) Integrated application of multi-source remote sensing data. It is hoped that the information provided here will be a reference for subsequent similar studies.     

生境破碎化对动物种群存活的影响

生境破碎是生物多样性下降的主要原因之一。通常以岛屿生物地理学、异质种群生物学和景观生态学的理论来解释不同空间尺度中生境破碎化的生态学效应。生境破碎化引起面积效应、隔离效应和边缘效应。这些效应通过影响动物种群的绝灭阈值、分布和多度、种间关系以及生态系统过程,最终影响动物种群的存活。野外研究表明,破碎化对动物的影响,因物种、生境类型和地理区域不同而有所变化,因此,预测物种在破碎生境中的存活比较困难。研究热点集中于：确定生境面积损失和生境斑块的空间格局对破碎景观中物种绝灭的相对影响,破碎景观中物种的适宜生境比例和绝灭阈值,异质种群动态以及生态系统的生态过程。随着3S技术的发展,生境破碎化模型趋于复杂,而发展有效的模型和验证模型将成为一项富有挑战性的任务。     

Po'ouli landscape bioinformatics models predict energetics, behavior, diets, and distribution on Maui

This study uses a spatially explicit microclimate/biophysicalapproach to examine the potential distribution of the Po'oulion Maui to find either new habitats to search for existenceor refine search efforts in previously occupied areas. We usedspecific physiological and behavioral ecology bird data, andPo'ouli morphological and spectral data obtained from museumspecimens to address ecological and conservation-related questionsabout the Po'ouli that are otherwise very difficult to quantify.Laboratory and field tested microclimate and biophysical—behavioralanimal computer models were integrated with remote sensing technologies.To show that the generic microclimate and endotherm models canpredict metabolic and water loss requirements of Hawaiian Honeycreepers,we used the 2 species with known physiological properties, theHawaiian Amakihi, Hemignathus virens, and the Hawaiian Anianiau,Hemignathus parvus. Predictions were within experimental measurementerror of the laboratory measurements. Then using field ratherthan laboratory conditions as input data, we predict the fielddistribution of the Amakihi on Maui as the first spatial testof the models applied to birds. Results are consistent withAmakihi field distribution data. Fossils show that the Po'oulionce lived on Maui at low elevations in dry/mesic habitats ona likely diet of native tree snails and insects. The arrivalof lethal mosquito-borne avian malaria in Hawaii exterminatedlow elevation Po'ouli forcing a population shift to mountainrainforests and possibly a snail diet instead of insects. Toexplore the maximum consequences of such a diet shift we assumedexclusive diets of snails versus insects at both low and highelevations. Snail diets require     

Indices of bird-habitat preference from field surveys of birds and remote sensing of land cover: a study of south-eastern England with wider implications for conservation and biodiversity assessment

Aim This paper describes the development of novel indices of bird‐habitat preference to examine bird species’ use of habitats and their distributions relative to habitats. It assesses the implications for bird conservation regionally and the scope for biodiversity assessments generally. Location A 200 km by 400 km area of farmland with seminatural and urban areas, covering south‐eastern England. Methods Cluster analysis was used to link birds to landscapes. Cluster centroid coordinate values were processed to derive indices of bird‐habitat preference. Further developments assessed the relative values of individual habitats for birds. Results Clustering objectively linked birds to landscapes. Maps of the clusters showed strong regional patterns associated with distinctive habitat assemblages. Derived indices related bird species directly to individual habitats and habitats to birds. Even rare species and scarce habitats showed successful linkages, often to each other. Objective corroboration strongly supported the associations of coastal, wetland, urban and woodland birds and habitats; but, it suggested that farmland birds, whose numbers have nearly halved since 1977, may prefer alternative habitats. Main conclusions Land cover maps from remote sensing provide an effective way to link birds to habitats and vice versa. Thus, generalized habitat maps might be used to extrapolate localized or sample‐based bird observations or the results of autecological studies, helping to predict and understand bird distributions in the wider countryside. The weak links between farmland birds and farmland habitats in a region dominated by farming, suggests that reasons for the decline in farmland birds may be deep seated and thus hard to reverse. The procedures described are repeatable elsewhere and applicable more generally to evaluate landscapes and biodiversity. It is suggested that remote sensing could rarely be bettered as a means of assessing habitats, comprehensively, over wide areas, in most parts of the world.     

Assessing ecological habitat structure from local to landscape scales using synthetic aperture radar

Ecological studies need accurate environmental data such as vegetation characterization, landscape structure and organization, to predict and explain the spatial distribution of biodiversity. Few ecological studies use remote sensing data to assess the biophysical or structural properties of vegetation to understand species distribution. To date, synthetic aperture radar (SAR) data have seldom been used for ecological applications. However, these sensors provide data allowing access to the inner structure of vegetation which is a key information in ecology. The objective of this article is to compare the predictive power of ecological habitat structure variables derived from a TerraSAR-X image, an aerial photograph and a SPOT-5 image for species distribution. The test was run with a hedgerow network in Brittany and assessed the spatial distribution of the forest ground carabid beetles which inhabit these hedgerows. The results confirmed that radar and optical images can be indifferently used to extract hedgerow network and derived landscape metrics (hedgerow density, network grain) useful to explain the spatial distribution of forest carabid beetles. In comparison with passive optical remotely sensed data, VHSR SAR images provide new data to characterize vegetation structure and more particularly hedgerow canopy cover, a variable known to explain the spatial distribution of carabid beetles in an agricultural landscape, but not yet quantified at a fine scale. The hedgerow canopy cover derived from the SAR image is a strong predictor of the abundance of forest carabid beetles at two scales i.e., a local scale and a landscape scale.     

用间接遥感方法探测大熊猫栖息地竹林分布

竹子是野生大熊猫赖以生存的唯一食物。探测大熊猫栖息地内的竹林分布状况,有助于深入了解大熊猫及其栖息地的空间分布格局与特点,并为评估其栖息地适宜性、破碎化程度和生态承载力提供科学依据。由于大熊猫的主食竹大都生长于林下,直接通过遥感影像解译的方法很难实现对其分布密度的探测。以佛坪自然保护区的两大优势竹种——巴山木竹和秦岭箭竹为例,在运用遥感和GIS方法获取空间连续的环境变量时,引入了林上和林下的光照条件,通过分析不同竹种与各环境要素之间的关系,建立竹子密度的预测模型,最后在GIS空间分析技术的支持下实现了对林下竹子密度的绘制。研究结果显示:该方法能够比较准确地预测出林下竹子的分布状态,对两种竹子的密度预测精度均可达到70%以上。