Use of SPOT 5 for mapping seagrasses: An application to Posidonia oceanica

The SPOT 5 satellite was launched in May 2002; it provides multispectral imagery with a spatial resolution of 10 m and fused imagery with a spatial resolution of 2.5 m. These types of satellite imagery were used for mapping beds of Posidonia oceanica in the Mediterranean Sea, where it is a dominant species forming monospecific beds in a structurally simple environment (four classes: sand, photophilous algae on rock, patchy seagrass beds and continuous seagrass beds). Supervised classifications by depth range were made of both types of image. A direct comparison of overall accuracy between SPOT 2.5 m and SPOT 10 m revealed that this tool provided accurate mapping in both cases (between 73 and 96% accuracy). Although SPOT 2.5 m provides lower overall accuracy than SPOT 10 m, it is a very useful tool for the mapping of P. oceanica, as it allows the patchiness of the formations to be better taken into account. The opportunity to use a reliability scale, which takes into account the effects of extrinsic factors on the processing of the images, confirmed the usefulness of the option of using a reduced pixel size in order to obtain an improved match between the results from mapping and field observations.     

Damage to seagrass and seaweed beds in Matsushima Bay,Japan, caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011

Damage to seagrass and seaweed beds caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011 was investigated in Matsushima Bay, Miyagi Prefecture, Japan, by comparing satellite images taken before the tsunami in November 2009 and after the tsunami in May 2011. The results showed that the tsunami destroyed 220 ha of seagrass and seaweed beds, from 320 ha in 2009 to 100 ha just after the tsunami. Zostera marina beds on the sandy and muddy bottom were rather severely damaged compared with brown seaweed beds of Sargassum horneri on the rocky substrate. Substrates of the beds and directions of the tsunami seem to be responsible for the magnitude of the damage to the beds. Maps of the spatial distributions of the beds before and after the tsunami can provide information for the restoration of seagrass and seaweed beds as natural infrastructures of coastal fisheries resources.     

Technical Note. Mapping seagrass beds using IKONOS satellite image and side scan sonar measurements: a Japanese case study

In this study, we mapped seagrass beds in Japanese coastal areas by using a newly developed combination method of satellite and side‐scan sonar images. Traditionally, sea‐truth data used for satellite‐image analysis are collected through direct observations requiring scuba divers or by aquatic video‐camera observation. The method proposed here used side‐scan sonar measurements for collecting accurate sea‐truth data and succeeded in efficiently obtaining precise information about seagrass distribution. Side‐scan sonar images also enabled us to assess the reliability of satellite‐image results from an area perspective and not only from a traditional point data one. The IKONOS image was analysed in two different ways. First, mapping was realized without any reference to bottom depth. Second, mapping was processed with consideration for depth gradients. Results were compared using error matrices and showed that the method proposed here is suitable to map several specific areas efficiently.     

Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia)

Understanding, monitoring and modelling attributes of seagrass biodiversity, such as species composition, richness, abundance, spatial patterns, and disturbance dynamics, requires spatial information. This work assessed the accuracy of commonly available airborne hyper-spectral and satellite multi-spectral image data sets for mapping seagrass species composition, horizontal horizontal-projected foliage cover and above-ground dry-weight biomass. The work was carried out on the Eastern Banks in Moreton Bay, Australia, an area of shallow and clear coastal waters, containing a range of seagrass species, cover and biomass levels. Two types of satellite image data were used: Quickbird-2 multi-spectral and Landsat-5 Thematic Mapper multi-spectral. Airborne hyper-spectral image data were acquired from a CASI-2 sensor using a pixel size of 4.0 m. The mapping was constrained to depths shallower than 3.0 m, based on past modelling of the separability of seagrass reflectance signatures at increasing water depths. Our results demonstrated that mapping of seagrass cover, species and biomass to high accuracy levels (> 80%) was not possible across all image types. For each parameter mapped, airborne hyper-spectral data produced the highest overall accuracies (46%), followed by Quickbird-2 and then Landsat-5 Thematic Mapper. The low accuracy levels were attributed to the mapping methods and difficulties in matching locations on image and field data sets. Accurate mapping of seagrass cover, species composition and biomass, using simple approaches, requires further work using high-spatial resolution (< 5 m) and/or hyper-spectral image data. Further work is required to determine if and how the seagrass maps produced in this work are suitable for measuring attributes of seagrass biodiversity, and using these data for modelling floral and fauna biodiversity properties of seagrass environments, and for scaling-up seagrass ecosystem models.     

基于机器学习的车道线检测系统仿真与优化

真实的道路行驶环境是复杂多变的,会对车辆识别算法造成较大干扰。为准确识别车道线,提高车道线检测算法的实时性和鲁棒性,进行了多方面的改进。首先对采集到的图像进行预处理,包括图像灰度化、45°sobel算子边缘检测和二值化处理等,获得高质量图片。其次采用改进的Hough变换进行车道线识别和优化,提高检测结果的准确性,促进检测有序进行。最后通过最小二乘法对结果进一步优化,以期得出更加精确的车道线。实验结果表明:改进后的算法可以较为准确的识别车道线,具有较强的实时性、鲁棒性和准确率。     

Posidonia oceanica genetic and biometry mapping through high-resolution satellite spectral vegetation indices and sea-truth calibration

In the framework of Posidonia oceanica (PO) preservation activities, a small-scale restoration pilot project was implemented in 2005 at a Santa Marinella site to replace the loss of this important species of seagrass in this zone of the central Tyrrhenian coast via an innovative transplantation approach. In this context, taking into account the recent advances in the fields of high-resolution (HR) satellite/airborne remote-sensing and genetics laboratory analysis techniques, we propose this integrated methodology for monitoring changes in transplanted meadows in regard to perspective to provide support in the assessment of the entire local PO and seagrass population dynamic. According to specific information requirements in terms of radiometric and spectral/spatial resolution, the multispectral data currently available from the QuickBird polar satellite’s four-band (red, green, blue visible and near-infrared) HR sensor were exploited for methodology implementation using a practical ‘image-based’ approach to account for atmospheric and water column turbidity typical of this mid-coastal Mediterranean region. First, the extents and types of seagrass cover were suitably mapped, and then also the distributions of specific vegetation parameters related to PO dynamics and health were assessed by exploiting the remotely sensed satellite-derived radiance signals and point sea-truth calibration measurements of the bio-genetic parameters. In particular, we implemented maps of leaf area index, genetic similarity, and density Giraud indices corresponding to distributions of PO patches using multivariate and data-mining models (artificial neural network) based on appropriately preprocessed radiometric and auxiliary (bathymetry) input variables.     

Analysis of reflectance spectra of tropical seagrass species and their value for mapping using multispectral satellite images

ABSTRACT

Mapping of the distribution of individual seagrass species is essential for any attempts to manage seagrass ecosystems. It is therefore important to understand how the spectra of different seagrass species vary, in order to establish their unique absorption features and how these can be utilised for mapping by making use of remote-sensing images. This paper presents measurements of the reflectance spectra between 400 and 900 nm for nine tropical species of seagrass. Continuum removal and multispectral resampling procedures were applied to the spectra. Dendrogram analysis was carried out to identify species clustering as the basis for a mapping scheme. Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) approaches were employed for the classification of seagrass species using WorldView-2 images and measured spectra as the input endmember. Classification Tree Analysis (CTA) and an image segmentation approach using CTA (Object-Based Image Analysis – OBIA) were performed as a means of comparison. The results indicate that the absorption features and overall shape of the spectra for all seagrass species are relatively similar, and implied that the major differences are attributable to the absolute reflectance values. Consequently, SAM and SID produced results of low accuracy (<30%), whereas, CTA and OBIA delivered results exhibiting higher accuracy (60–92%). The use of a spectral-based classification algorithm was ineffective for the classification and mapping of seagrass species using multispectral images. The utilisation of absolute reflectance values was beneficial for the classification of seagrass species having similar spectral shape.     

Evaluating the complementarity of acoustic and satellite remote sensing for seagrass landscape mapping

Accurate maps representing seagrass spatial distribution are essential components for effective monitoring and management of coastal vegetated habitats. Satellite and acoustic remote sensing provide valuable spatial data for seagrass mapping, though few studies have evaluated the complementarity of these methods. In this study, the complementarity of seagrass mapping was assessed through comparison of acoustic and satellite remote-sensing data sets. QuickBird^® satellite imagery representing the seagrass landscape of the Richibucto estuary, New Brunswick, Canada, was classified through an object-based procedure and evaluated against a single-beam sonar data set. Acoustic percentage cover values were classified into binary presence/absence format through the application of a decision threshold, allowing comparison with satellite data using the error matrix and derived metrics. Though the binary satellite classification resulted in relatively high accuracy compared with independent ground reference data, agreement between satellite and acoustic data sets was limited. Local differences in seagrass prevalence and patchiness affected classification accuracy, highlighting the potential for under- or overestimating seagrass cover when applying bay-scale classification to areas with different landscape structure. These results emphasize the importance of landscape context in seagrass mapping. Satellite and acoustic remote sensing were seen to fundamentally differ in their depiction of the landscape. Comparison of multiple remote-sensing methods allowed for assessment of complementarity as well as ecologically relevant insight to seagrass spatial dynamics, with implications for mapping and monitoring of seagrass habitats.     

Transportation with hospital beds

Transporting patients in hospital beds is a common task in acute hospital wards. The aim of the study was to explore the influence of different bed wheel arrangements on the effort and difficulties experienced by personnel when transporting patients. Four test beds were used and tested in four common transport situations. Nineteen registered and enrolled nurses participated in the tests. The perception of effort was rated on Borg's category ratio scale, CR-10 and the perceived level of difficulty on the visual analogue scale. ANOVA and Bonferroni post hoc multiple comparisons were conducted to measure which pairs of beds differed significantly. The results show that the wheel arrangements of the beds have a major influence on the effort and difficulties perceived by the personnel. Standard small diameter castor wheels made the bed easier to manoeuvre in limited spaces, while larger wheels on fixed axles made the beds more comfortable to handle during long distance transportation.     

浅谈以就业为导向的高职计算机教学评价

为科学地、准确地、发展地评价高职计算机学生的“就业能力”进行有益的尝试。本文在以就业为导向的高职计算机教学评价这个方面进行一些有益的尝试。希望本文的研究为高职计算机专业的发展进行一些有益的探素。     

基于蚁群算法的最短路径问题的研究和应用

求解交通路网中两点间的最短路径是智能交通系统中一个重要的功能,为了更为准确快速的找到最优解,本文尝试采用带有方向引导信息的蚁群算法来实现此功能。实验结果表明,该方法能较为准确的找到交通路网中两点间最短路径的最优解,搜索效率高、搜索最优解的能力强,对于智能交通系统中最短路径搜索的功能实现问题有一定的参考价值和实际意义。     

基于数字图像处理的路面裂缝自动识别与评价系统

公路是完成交通运输和沟通各地区之间联系的重要经络,但是受到自然因素和外力的作用,会对公路的质量造成一定程度的影响,很容易造成路面裂缝,这就提出了一种基于数字图像处理的路面裂缝自动识别与评价系统,以便能够更加快速和准确的确定出路面裂缝的程度,并制定出适当的处理方法。以下,将对此项技术的结构、原理,以及提高系统处理质量和水平的关键技术进行简要的分析。     

Grouped comparisons of sleep quality for new and personal bedding systems

The purpose of this study was to compare sleep comfort and quality between personal and new bedding systems. A convenience sample (women, n=33; men, n=29) with no clinical history of disturbed sleep participated in the study. Subjects recorded back and shoulder pain, sleep quality, comfort, and efficiency for 28 days each in their personal beds (pre) and in new medium-firm bedding systems (post). Repeated measures ANOVAs revealed significant improvement between pre- and post-test means for all dependent variables. Furthermore, reduction of pain and stiffness and improvement of sleep comfort and quality became more prominent over time. No significant differences were found for the groupings of age, weight, height, or body mass index. It was found that for the cheapest category of beds, lower back pain was significantly (p<0.01) more prominent than for the medium and higher priced beds. Average bed age was 9.5yrs. It was concluded that new bedding systems can significantly improve selected sleep variables and that continuous sleep quality may be dependent on timely replacement of bedding systems.     

Landsat 8 OLI satellite data for mapping of the Posidonia oceanica and benthic habitats of coastal ecosystems

The benthic seabeds and seagrass ecosystems, in particular the vulnerable Posidonia oceanica (PO), are increasingly threatened by climate change and other anthropogenic pressures. Along the 8000 km coastline of Italy, they are often poorly mapped and monitored to properly evaluate their health status. Thus to support these monitoring needs, the improved capabilities of the Landsat 8 Operational Land Imager (OLI) Earth Observation (EO) satellite system were tested for PO mapping by coupling its atmospherically corrected multispectral data with near-synchronous sea truth information. Two different approaches for the necessary atmospheric correction were exploited focusing on the Aerosol Optical Depth (AOD) and adjacency noise effects, which typically occur at land–sea interfaces. The general achievements demonstrated the effectiveness of High Resolution (HR) spectral responses captured by OLI sensor, for monitoring seagrass and sea beds in the optically complex Tyrrhenian shallow waters, with performance level dependent on the type of applied atmospheric pre-processing. The distribution of the PO leaf area index (LAI) on different substrates has been most effectively modelled using on purpose developed spectral indices. They were based on the coastal and blue-green OLI bands, atmospherically corrected using a recently introduced method for AOD retrieval, based on the Short Wave Infrared (SWIR) reflectance. The alternative correction method including a less effective AOD assessment but the removal of adjacency effects has proven its efficacy for improving the thematic discriminability of the seabed types characterized by different PO cover–substrate combinations.     

Object-based image classification for burned area mapping of Creus Cape, Spain, using NOAA-AVHRR imagery

Due to the ability of the NOAA-AVHRR sensor to cover a wide area and its high temporal frequency, it is possible to quickly obtain a general overview of the prevailing situation over a large area of terrain and, more specifically, quickly assess the damage caused by a recent large forest fire by mapping the extent of the burned area. The aim of this work was to map a large forest fire that recently took place on the Spanish Mediterranean coast using innovative image classification techniques and low spatial resolution imagery. The methodology involved developing an object-based classification model using spectral as well as contextual object information. The burned area map resulting from the image classification was compared with the fire perimeter provided by the Catalan Environmental Department in terms of spatial overlap and size in order to determine to what extent they were compatible. Results of the comparison indicated a high degree (≈90%) of spatial agreement. The total burned area of the classified image was found to be 6900 ha, compared to a fire perimeter of 6000 ha produced by the Catalan Environmental Department. It was concluded that, although the object-oriented classification approach was capable of affording very promising results when mapping a recent burn on the Spanish Mediterranean coast, the method in question required further assessment to ascertain its ability to map other burned areas in the Mediterranean.     

An ergonomic garment design for elderly Turkish men

This paper presents an ergonomic garment design for elderly Turkish men. The purpose of this study was to determine elderly men's demands, needs and problems in regard to clothing and to design an ergonomic garment in the light of this knowledge. The sample consisted of 120 elderly men living in Ankara, the capital city of Turkey, and its province. A questionnaire was prepared and given to these people in order to determine their clothing demands and needs. It was established that most of our subjects need functional garments. An ergonomic garment has been designed using the obtained data. It was found that the design of clothing for the elderly requires attention to bodily changes from aging in order to facilitate and raise the quality of life. Specific suggestions are made to elderly people and to the ready-to-wear sector.     

Capability of TM data for evaluation of soil and land resources in the Malwa Plateau (Chambal and Mahi catchment) in Madhya Pradesh,India

Abstract

Owing 10 the advent of the Thematic Mapper with higher resolution, it has now become much easier to map various natural resources efficiently and accurately in a shorter period of time. In the work described in this paper an attempt has been made to prepare various soil and land resources maps by visual interpretation of a false colour composite from the Thematic Mapper at the average scale of 1:250 000 in conjunction with field checks covering an area of 340000 ha in the Malwa Plateau. The soil map was prepared in association with subgroup level and a total of nine soil mapping untits were established. Four physiographic units, seven land-use units and three waste-land mapping units were found to occur in the area during preparation of the respective map.     

适用于迭代型去模糊算法粗精检测相结合的自适应终止机制

由于缺乏合适的去模糊图像质量度量方法,迭代型去模糊算法通常将其迭代次数简单地设置为固定值,无法在执行效率和去模糊质量之间获得最优的平衡点。为此,提出一种粗精检测相结合的迭代终止机制并将其应用到迭代型去模糊算法中以自适应地确定它们最佳的迭代次数。具体地,在每一步迭代过程中利用伪PSNR值细粒度地判断去模糊图像质量是否趋于稳定,另一方面每隔若干步利用从反向卷积残差图像中提取的统计特征值粗粒度准确地判定图像质量是否达到最佳,将两种去模糊图像质量度量方法有机结合以实现一种效率高且准确的迭代终止判定机制。评估结果显示,将所提出的粗精相结合的终止机制应用于NCSR、GSR和ADMM共三种主流去模糊算法后,执行效率可提高50%左右,而去模糊图像质量也得到了最佳保证。实验结果表明,提出的检测机制能够有效地解决各种迭代型去模糊算法因采用固定迭代次数而存在的无益迭代和过迭代问题,非常具有普适性。     

Comparison of bathymetry and seagrass mapping with hyperspectral imagery and airborne bathymetric lidar in a shallow estuarine environment

We compared hyperspectral imagery and single-wavelength airborne bathymetric light detection and ranging (lidar) for shallow water (<2 m) bathymetry and seagrass mapping. Both the bathymetric results from hyperspectral imagery and airborne bathymetric lidar reveal that the presence of a strongly reflecting benthic layer under seagrass affects the elevation estimates towards the bottom depth instead of the top of seagrass canopy. Full waveform lidar was also investigated for bathymetry and similar performance to discrete lidar was observed. A provisional classification was performed with limited ground reference samples and four supervised classifiers were applied in the study to investigate the capability of airborne bathymetric lidar and hyperspectral imagery to identify seagrass genera. The overall classification accuracy is highly variable and strongly dependent on the classification strategy used. Features from bathymetric lidar alone are not sufficient for substrate classification, while hyperspectral imagery alone showed significant capability for substrate classification with over 95% overall accuracy. The fusion of hyperspectral imagery and bathymetric lidar only marginally improved the overall accuracy of seagrass classification.     

Mapping coastal marine habitats and delineating the deep limits of the Neptune’s seagrass meadows using very high resolution Earth observation data

ABSTRACT

Seagrass meadows are one of the most important coastal habitats across the globe. These are mainly constituted by the marine plants of the genus Posidonia and Thalassia. In the Mediterranean Sea, Posidonia oceanica is the dominant endemic plant that affects physical, biogeochemical, and biological processes. The decline in the spatial distribution has been attributed to excessive anthropic pressures and other large-scale environmental changes. The monitoring of the spatial distribution requires an update and accurate seagrass meadows delineation, i.e. meadow edge marking with a replicable method. The present study aims to present an approach to support the coastal marine habitat mapping, under the scheme of the Natura 2000 network using very high resolution Earth observation data and to prove that satellite images can be used for the mapping of the deep limits of the seagrass meadows. Pixel-based classification and object-oriented image analysis have been implemented for the image classification. Pixel-based Support Vector Machines and object-based Nearest Neighbor classifiers provided the best results with an overall accuracy of more than 90%, while deep limits have been successfully identified and separated from the deep waters.