A new species-time method for visual assessment of fishes and its comparison with established methods

Synopsis Relative abundances for 80 species in a fish assemblage were estimated using three visual assessment methods. Results of two species-time methods, the Rapid Visual Census (RVC) of Jones & Thompson (1978) and a new method, the Visual Fast Count (VFC), are compared to the traditional transect method. The VFC is similar to the RVC but it is an attempt to improve: on the quantitative nature of the results. Results from each method were significantly correlated, but important differences between methods were found. With an equal number of replicates both RVC and VFC methods yielded significantly more species than the transect method. Relative abundances estimated by the RVC were significantly different from those determined by either VFC or transect methods, but VFC and transect results were not different. A qualitative similarity index using presence-absence data was calculated and compared among methods. Values ranged from 84.3 to 85.9%, illustrating a consistent level of similarity for the faunas censused regardless of census method. Quantitative similarities (percent similarity), however, ranged from 45.8 to 85.7% and suggest a closer agreement between the transect and the VFC methods than between these methods and the RVC. If transect results are assumed to be the most accurate, the comparison suggests that the VFC method yields more accurate relative abundances than does the RVC. Ranges in percent similarity values calculated within each method (8 replicate samples) were used to compare precision among methods. While transect and RVC scores are slightly more precise (ranges of 3.10% and 2.20% respectively) than the VFC method (range = 4.89%), no method was statistically more precise than another (P<0.001).     

生物土壤结皮对照相法测量植被覆盖度结果的影响

植被覆盖度测度的准确性很大程度上影响着研究结论是否科学合理。在干旱半干旱退化草原区,尤其是受采矿剧烈扰动的矿区,发育的生物土壤结皮(Biological soil crust,BSC)由于其颜色和光谱同绿色植被具有相似性,导致对植被覆盖度的测量存在一定的影响。以伊敏露天矿区为研究区,在西排土场和内排土场采集了含苔藓结皮、地衣结皮和藻结皮的样方相片各四组(每组中包含样方喷水前和喷水后的相片各一张),并采集了一组不含结皮的样方相片作为对照组,运用数码照相法提取植被覆盖度,通过不同的数据处理方法(最大似然分类法及RGB阈值法)进行植被覆盖度提取,设立对比试验,分析BSC对于植被覆盖度测度是否有影响,其影响大小如何,影响程度是否受BSC含水量大小的影响,并对比各常规处理方法的优劣,研究能否通过结合纹理特征与色彩信息剔除BSC对植被覆盖度提取值的影响。研究结论:1)基于照相法的常规数据处理方法提取植被覆盖度时,BSC的存在导致测得的植被覆盖度值偏高,且苔藓结皮、地衣结皮吸水后比吸水前影响更显著,藻结皮相反;2)3个演替阶段的BSC中,尤以含苔藓结皮的样方植被覆盖度高估最为明显,其次为地衣,而含藻结皮样方规律不明显;3)样方内BSC覆盖度越高,植被覆盖度越低,其植被覆盖度测度越不准确,因此在研究草原矿区这类草本植物覆盖度较低、结皮发育的区域时,应当注意BSC的影响;4)试通过应用纹理信息提出改进的提取方法,发现单纯的纹理分类精度极低,而结合了纹理信息与RGB色彩信息的分类精度较高;5)对两种常规分类方法的精度进行比较,RGB阈值法较最大似然分类法更为不准确,对植被覆盖度的高估接近最大似然分类法的2倍。对两种改进的提取方法的精度进行比较,二者都可以有效提高测量精度,基于波段合成的纹理分类方法最佳。四种方法精度由高到低的顺序为:纹理结合RGB法考虑生物土壤结皮的最大似然分类法普通最大似然分类法RGB阈值法。     

多尺度遥感综合监测我国北方典型草原区植被盖度

利用多尺度遥感影像综合进行全球和区域尺度的土地利用/覆盖变化(LUCC)研究是最近全球变化研究的重要方向之一。本文综合利用野外群落样方、数字相机、ETM+影像、NOAA/AVHRR影像,在遥感、GIS和GPS支持下,对我国北方典型草原区植被盖度进行了综合监测、模拟与分析。结果表明:(1) 利用经处理后的数字相机影像测量盖度的结果准确性较高,可以作为植被盖度测量的标准结果,反映真实的覆盖特征,并用以验证利用其它方法测量结果的精度。(2) 利用野外1 m2样方网格法目视估测的植被盖度结果变化较大,不稳定。本次实验中,与数字相机测量结果相比,样方估测的盖度普遍偏高,平均偏差为9.92%;但两者相关性较好(r2=0.89)。(3) 采用Gutman模型ETM+影像、NOAA/AVHRR影像反演植被盖度的结果与数字相机测量结果偏差分别为7.03%、7.83%,ETM+像元分解NOAA像元后得到的植被盖度与数字相机测量结果偏差5.68%。三者与数字相机测量结果的相关系数r2分别为0.78、0.61和0.76。(4)利用野外实测植被盖度数据直接与NOAA-NDVI影像建立统计模型估算植被盖度的精度较低(r2=0.65),而通过空间分辨率介于两者之间的ETM+影像进行转换后,该精度得到一定的提高(r2=0.80)。利用像元分解的方法提高了大尺度植被盖度监测的精度,是利用遥感数据进行尺     

多尺度遥感综合监测我国北方典型草原区植被盖度

利用多尺度遥感影像综合进行全球和区域尺度的土地利用/覆盖变化(LUCC)研究是最近全球变化研究的重要方向之一.本文综合利用野外群落样方、数字相机、ETM+影像、NOAA/AVHRR影像,在遥感、GIS和GPS支持下,对我国北方典型草原区植被盖度进行了综合监测、模拟与分析.结果表明:(1)利用经处理后的数字相机影像测量盖度的结果准确性较高,可以作为植被盖度测量的标准结果,反映真实的覆盖特征,并用以验证利用其它方法测量结果的精度.(2)利用野外1 m2样方网格法目视估测的植被盖度结果变化较大,不稳定.本次实验中,与数字相机测量结果相比,样方估测的盖度普遍偏高,平均偏差为9.92%;但两者相关性较好(r2=0.89).(3)采用Gutman模型ETM+影像、NOAA/AVHRR影像反演植被盖度的结果与数字相机测量结果偏差分别为7.03%、7.83%,ETM+像元分解NOAA像元后得到的植被盖度与数字相机测量结果偏差5.68%.三者与数字相机测量结果的相关系数r2分别为0.78、0.6l和0.76.(4)利用野外实测植被盖度数据直接与NOAA-NDVI影像建立统计模型估算植被盖度的精度较低(r2=0.65),而通过空间分辨率介于两者之间的ETM+影像进行转换后,该精度得到一定的提高(r2=0.80).利用像元分解的方法提高了大尺度植被盖度监测的精度,是利用遥感数据进行尺度转换研究的重要实践.多尺度遥感影像的综合对地观测对大区域上反演植被盖度有很好的促进作用.     

Digitized photographs in vegetation analysis ‐ a comparison of cover estimates

Abstract. The use of digital images in measuring plant species cover and species number in boreal forest vegetation was studied. Plant cover was estimated by manual delineation on photographs and subsequent digitized measurement of the areas. This value was regarded as the reference and compared with cover obtained by visual estimate, point frequency and automatic image analysis methods. The automatic image analysis was based on scanned photographs. Supervised image classification with ERDAS software was then used to distinguish between the covers of different plant species. When comparing the ability of the methods to detect species, the visual estimate method gave values similar to the reference. The study material was collected from three sites along a heavy‐metal pollution transect in western Finland. All four methods detected, in a similar manner, differences between the plant species abundances along the transect. Compared with the reference, the digital images underestimated the cover of the lichens Cladina spp. and Cetraria islandica, but gave similar estimates for the dwarf shrubs Empetrum nigrum and Vaccinium vitis‐idaea. The point frequency method overestimated the cover of all the species studied. The visual estimates of lichens were close to the reference, while the dwarf shrub covers were overestimated. The number of species detected using supervised image analysis and the point frequency method was lower than that with visual estimation. Visual estimation was faster, and the estimate closer to the reference cover values than the others. Digital images may be useful in detecting changes in some selected species in vegetation with a simple vertical structure but with taller, multilayered vegetation and a higher species number, the reliability of the cover estimates is lower.     

Abundance estimation of rocky shore invertebrates at small spatial scale by high-resolution digital photography and digital image analysis

We have tested both the usefulness of high-resolution digital photography for data acquisition and digital image analysis, by non-supervised classification and high pass filter, for recognition and abundance estimation of benthic intertidal organisms. These digital tools were compared with visual scan and photo quadrat conventional methods. The comparison was done using 40 quadrats (10×5 cm) randomly selected along a 5-m transect on the rocky shore of the Pemaquid Point, Maine, USA. ANOVA for repeated measures was used to test differences among methods. Monte Carlo simulation analysis was used to explore differences among methods over a large set of data (n=100, 500, 1000 quadrats). Differences among methods were observed when 40 quadrats were used. Tukey multiple comparison test showed that abundance estimation from visual scan, photo quadrat and digital image analysis by high pass filter do not differ significantly among them but differ from non-supervised classification results. Due to its accurate estimation, high pass filter (Prewitt) method was chosen as the most reliable digital method to estimate species abundance. Monte Carlo simulation of visual scan, photo quadrat and high pass filter results showed significant differences when the number of quadrats was larger. These results showed that the combined use of digital photography and digital image analysis techniques for the acquisition and analysis of recorded data is a powerful method for the study of intertidal benthic organisms. Results produced using these techniques were similar than those produced by conventional methods but were obtained in a much-reduced time.     

Abstract processes in texture discrimination.

In this study some experiments on texture segmentation are reported using the local Gabor power spectrum. The techniques applied are: (1) supervised pixel classification; (2) boundary detection by spectral dissimilarity estimation; (3) region-based segmentation based on Gaussian spectral estimation; and (4) the same as (3) but based on central moments of the local spectrum. It is shown that very-acceptable-to-excellent results can be obtained. It is argued, however, that the shortcomings of region-based and boundary-based approaches require that both processes should act in parallel, not only in digital image processing but also in the modelling of visual perception.     

基于遥感图像不同辐射校正水平的植被覆盖度估算模型

选用南京市SPOT 5 HRG图像的地物反射率(PAC)、表观反射率(TOA)和灰度值（DN）影像,提取了4种植被指数（VI）,即归一化植被指数（NDVI）、转换植被指数（TVI）、土壤调节植被指数（SAVI）和修正的土壤调节植被指数（MSAVI）,与地面实测的植被覆盖度进行了回归分析,并建立了36个VI-VFC关系模型.结果表明：在所有模型中,基于PAC级影像提取的NDVI和TVI的3次多项式模型最优;其次为基于DN级影像提取的SAVI和MSAVI的3次多项式模型,在VFC>0.8时其精度略高于前两种模型.这4个模型在植被中等密集区域（VFC＝0.4～0.8）的精度高于植被稀疏区域（VFC=0～0.4）.所建模型可通过中间模型的联结,进行推广使用.在基于VI-VFC关系建模过程中,基于遥感影像不同辐射校正水平提取植被指数,有利于充分挖掘遥感影像信息,进而提高VFC估算的精度.     

高原鼠兔洞穴区次生斑块面积的测定方法

利用数码相机快速获得高原鼠兔挖掘活动形成的次生斑块图像,运用地理信息系统软件（Arcview） 计算其面积。运用该方法对草地内高原鼠兔洞穴区次生斑块的面积进行了实地测量,结果显示该方法可以快速、准确测量出不同形状次生斑块的面积,具有良好的实用性和可操作性。     

Traceable Calibration,Performance Metrics,and Uncertainty Estimates of Minirhizotron Digital Imagery for Fine-Root Measurements

Even though fine-root turnover is a highly studied topic, it is often poorly understood as a result of uncertainties inherent in its sampling, e.g., quantifying spatial and temporal variability. While many methods exist to quantify fine-root turnover, use of minirhizotrons has increased over the last two decades, making sensor errors another source of uncertainty. Currently, no standardized methodology exists to test and compare minirhizotron camera capability, imagery, and performance. This paper presents a reproducible, laboratory-based method by which minirhizotron cameras can be tested and validated in a traceable manner. The performance of camera characteristics was identified and test criteria were developed: we quantified the precision of camera location for successive images, estimated the trueness and precision of each camera''s ability to quantify root diameter and root color, and also assessed the influence of heat dissipation introduced by the minirhizotron cameras and electrical components. We report detailed and defensible metrology analyses that examine the performance of two commercially available minirhizotron cameras. These cameras performed differently with regard to the various test criteria and uncertainty analyses. We recommend a defensible metrology approach to quantify the performance of minirhizotron camera characteristics and determine sensor-related measurement uncertainties prior to field use. This approach is also extensible to other digital imagery technologies. In turn, these approaches facilitate a greater understanding of measurement uncertainties (signal-to-noise ratio) inherent in the camera performance and allow such uncertainties to be quantified and mitigated so that estimates of fine-root turnover can be more confidently quantified.     

Precision and accuracy in quantifying herbivory

1. Tissue removal by herbivores (i.e. herbivory) is a dominant interaction in most communities which has important impacts on natural and managed ecosystems. Despite the importance of herbivory, we lack a quantitative comparison of the efficacy of the most commonly used methods used to quantify herbivore damage. 2. We examined the factors that affect the precision and accuracy of visual and digital methods commonly used to quantify damage to leaves. 3. We created 224 digital leaves from four plant species. In a fully factorial design we manipulated leaf morphology and species, the location of damage (marginal or internal), estimation method (exact percentage or 25% bins), observer experience and expectancy bias (i.e., bias due to an expected result). Using 583 adult observers, we estimated the precision and accuracy of individuals' ability to visually estimate known levels of damage. In a third smaller experiment, we performed similar analyses using a digital scanner. 4. Across the first two experiments, individuals estimated damage with high precision (R² = 0.75 and 0.80) and accuracy (slope_{actual vs estimated} = 0.88 and 0.86). However, the precision and accuracy of estimates were influenced by plant species, the location of damage, and estimation method. Inexperienced individuals also overestimated low levels of damage, and this bias decreased with experience. Digital methods were precise (R² = 0.98) whereas accuracy was statistically indistinguishable from visual methods (slope = 0.91). 5. Visual estimates of damage provide the fastest and most cost‐effective method for quantifying herbivory, and our results show they can be precise and accurate. We use our results to provide specific recommendations for future research.     

Wound Area Measurement with Digital Planimetry: Improved Accuracy and Precision with Calibration Based on 2 Rulers

Introduction

In the treatment of chronic wounds the wound surface area change over time is useful parameter in assessment of the applied therapy plan. The more precise the method of wound area measurement the earlier may be identified and changed inappropriate treatment plan. Digital planimetry may be used in wound area measurement and therapy assessment when it is properly used, but the common problem is the camera lens orientation during the taking of a picture. The camera lens axis should be perpendicular to the wound plane, and if it is not, the measured area differ from the true area.

Results

Current study shows that the use of 2 rulers placed in parallel below and above the wound for the calibration increases on average 3.8 times the precision of area measurement in comparison to the measurement with one ruler used for calibration. The proposed procedure of calibration increases also 4 times accuracy of area measurement. It was also showed that wound area range and camera type do not influence the precision of area measurement with digital planimetry based on two ruler calibration, however the measurements based on smartphone camera were significantly less accurate than these based on D-SLR or compact cameras. Area measurement on flat surface was more precise with the digital planimetry with 2 rulers than performed with the Visitrak device, the Silhouette Mobile device or the AreaMe software-based method.

Conclusion

The calibration in digital planimetry with using 2 rulers remarkably increases precision and accuracy of measurement and therefore should be recommended instead of calibration based on single ruler.     

Developing a classifier for the Habitats Directive grassland types in Denmark using species lists for prediction

Abstract. This paper describes the use of supervised methods for the classification of vegetation. The difference between supervised classification and clustering is outlined, with reference to their current use in vegetation science. In the paper we describe the classification of Danish grasslands according to the Habitats Directive of the European Union, and demonstrate how a supervised classification can be used to achieve a standardized and statistical interpretation within a local flora. We thereby offer a statistical solution to the legal problem of protection of certain selected habitat types. The Habitats Directive protects three types of Danish grassland habitats, whereas two remaining types fall outside protection. A classification model is developed, using available Danish grassland data, for the discrimination of these five types based on their species composition. This new Habitats Directive classification is compared to a previously published unsupervised classification of Danish grassland vegetation. An indicator species analysis is used to find significant indicator species for the three protected habitat types in Denmark, and these are compared to the characteristic species mentioned in the interpretation manual of the Habitats Directive. Eventually, we discuss the pros and cons of supervised and unsupervised classification and conclude that supervised methods deserve more attention in vegetation science.     

Error,Power, and Blind Sentinels: The Statistics of Seagrass Monitoring

We derive statistical properties of standard methods for monitoring of habitat cover worldwide, and criticize them in the context of mandated seagrass monitoring programs, as exemplified by Posidonia oceanica in the Mediterranean Sea. We report the novel result that cartographic methods with non-trivial classification errors are generally incapable of reliably detecting habitat cover losses less than about 30 to 50%, and the field labor required to increase their precision can be orders of magnitude higher than that required to estimate habitat loss directly in a field campaign. We derive a universal utility threshold of classification error in habitat maps that represents the minimum habitat map accuracy above which direct methods are superior. Widespread government reliance on blind-sentinel methods for monitoring seafloor can obscure the gradual and currently ongoing losses of benthic resources until the time has long passed for meaningful management intervention. We find two classes of methods with very high statistical power for detecting small habitat cover losses: 1) fixed-plot direct methods, which are over 100 times as efficient as direct random-plot methods in a variable habitat mosaic; and 2) remote methods with very low classification error such as geospatial underwater videography, which is an emerging, low-cost, non-destructive method for documenting small changes at millimeter visual resolution. General adoption of these methods and their further development will require a fundamental cultural change in conservation and management bodies towards the recognition and promotion of requirements of minimal statistical power and precision in the development of international goals for monitoring these valuable resources and the ecological services they provide.     

Satellite remote sensing of wetlands

To conserve and manage wetland resources, it is important to inventoryand monitor wetlands and their adjacent uplands. Satellite remote sensing hasseveral advantages for monitoring wetland resources, especially for largegeographic areas. This review summarizes the literature on satellite remotesensing of wetlands, including what classification techniques were mostsuccessful in identifying wetlands and separating them from other land covertypes. All types of wetlands have been studied with satellite remote sensing.Landsat MSS, Landsat TM, and SPOT are the major satellite systems that have beenused to study wetlands; other systems are NOAA AVHRR, IRS-1B LISS-II and radarsystems, including JERS-1, ERS-1 and RADARSAT. Early work with satellite imageryused visual interpretation for classification. The most commonly used computerclassification method to map wetlands is unsupervised classification orclustering. Maximum likelihood is the most common supervised classificationmethod. Wetland classification is difficult because of spectral confusion withother landcover classes and among different types of wetlands. However,multi-temporal data usually improves the classification of wetlands, as doesancillary data such as soil data, elevation or topography data. Classifiedsatellite imagery and maps derived from aerial photography have been comparedwith the conclusion that they offer different but complimentary information.Change detection studies have taken advantage of the repeat coverage andarchival data available with satellite remote sensing. Detailed wetland maps canbe updated using satellite imagery. Given the spatial resolution of satelliteremote sensing systems, fuzzy classification, subpixel classification, spectralmixture analysis, and mixtures estimation may provide more detailed informationon wetlands. A layered, hybrid or rule-based approach may give better resultsthan more traditional methods. The combination of radar and optical data providethe most promise for improving wetland classification.     

Can digital image classification be used as a standardised method for surveying peatland vegetation cover?

The ability to carry out systematic, accurate and repeatable vegetation surveys is an essential part of long-term scientific studies into ecosystem biodiversity and functioning. However, current widely used traditional survey techniques such as destructive harvests, pin frame quadrats and visual cover estimates can be very time consuming and are prone to subjective variations. We investigated the use of digital image techniques as an alternative way of recording vegetation cover to plant functional type level on a peatland ecosystem. Using an established plant manipulation experimental site at Moor House NNR (an Environmental Change Network site), we compared visual cover estimates of peatland vegetation with cover estimates using digital image classification methods, from 0.5 m × 0.5 m field plots. Our results show that digital image classification of photographs taken with a standard digital camera can be used successfully to estimate dwarf-shrub and graminoid vegetation cover at a comparable level to field visual cover estimates, although the methods were less effective for lower plants such as mosses and lichens. Our study illustrates the novel application of digital image techniques to provide a new way of measuring and monitoring peatland vegetation to the plant functional group level, which is less vulnerable to surveyor bias than are visual field surveys. Furthermore, as such digital techniques are highly repeatable, we suggest that they have potential for use in long-term monitoring studies, at both plot and landscape scales.     

基于基准样地法和国产高分数据的湖南省森林植被碳储量估测

为推广国产高分数据在大尺度范围碳储量估测计量的应用,采用覆盖湖南省的206景高分辨率遥感影像,将估测的最小单元固定为由多个像元组合成的面积为0.06 hm²的正方格,通过解译标志的建立和提纯,在森林信息提取上,利用基于像元法和面向对象分类法进行比较;在乔木林碳储量估测上,利用稳健估计、偏最小二乘法和基准样地法(k-NN)估计进行比较,最后实现了对湖南省森林的碳储量估测,并生成了全省的碳密度等级分布图.结果表明: 基于样地自动提取的解译标志在经过提纯后,能进一步增加乔木林提取精度;对于大尺度范围森林植被碳储量估测,无论是在森林信息提取还是乔木林碳储量建模方面,k-NN算法都体现了较大优势,是最佳估测方法;206景影像的平均分类总精度为76.8%,平均均方根误差为8.95 t·hm^-2,平均相对均方根误差为19.1%,湖南省碳储量总量为22.28 Mt.本研究结果为省级及国家级尺度的森林植被碳储量估测计量与监测提供了有效参考.     

基于能量属性的植物功能群划分方法探索——以内蒙古锡林河流域草原植物群落为例

植物功能群(plant functional groups, PFGs) 是具有确定的植物功能特征的一系列植物的组合,是生态学家为研究植被对气候变化和干扰的响应而引入的生态学概念.目前功能群研究中最核心的问题仍在于决定植物功能群划分的植物特征的选择上.以内蒙古锡林河流域草原植物群落为例,选取3个草原类型(羊草草原、大针茅草原和羊草草甸草原)及其退化梯度系列(未退化、轻度退化、中度退化、重度退化),在对植物热值进行分析测定的基础上,依据植物的能量属性-单位重量干物质在完全燃烧后所释放出来的热量值,采用人为分段的方法对草原植物进行了能量功能群的划分(高能值植物功能群、中能值植物功能群和低能值植物功能群).并探讨了这种能量功能群划分方法在草原植被动态研究中的客观性与可行性.     

基于可见光植被指数的面向对象湿地水生植被提取方法

利用ESP分割工具确定最佳分割尺度,通过多尺度分割算法创建最优分割影像,基于微型无人机影像数据生成可见光植被指数,从一系列可见光植被指数中选取一组最优植被指数,建立决策树规则,利用隶属度函数对研究区自动分类,生成水生植被分布图.结果表明: 监督分类法的总体精度为53.7%,面向对象分类法总体精度为91.7%,与基于像元的监督分类法相比,面向对象分类法显著改善了影像分类结果,并大大提高了水生植被提取精度,监督分类法的Kappa系数为0.4,而面向对象分类法的Kappa系数为0.9.这表明利用微型无人机数据生成的可见光植被指数结合面向对象分类方法提取水生植被在该研究区是可行的,并能够应用到其他类似区域.     

Blind source separation,wavelet denoising and discriminant analysis for EEG artefacts and noise cancelling

This paper proposes an automatic method for artefact removal and noise elimination from scalp electroencephalogram recordings (EEG). The method is based on blind source separation (BSS) and supervised classification and proposes a combination of classical and news features and classes to improve artefact elimination (ocular, high frequency muscle and ECG artefacts). The role of a supplementary step of wavelet denoising (WD) is explored and the interactions between BSS, denoising and classification are analyzed. The results are validated on simulated signals by quantitative evaluation criteria and on real EEG by medical expertise. The proposed methodology successfully rejected a good percentage of artefacts and noise, while preserving almost all the cerebral activity. The “denoised artefact-free” EEG presents a very good improvement compared with recorded raw EEG: 96% of the EEGs are easier to interpret.