Assessment of risks posed by chemical industries—application of a new computer automated tool -III

The paper describes the application of a new computer automated tool, developed by us, in the risk analysis of a typical chemical industry engaged in the manufacture of linear alkyl benzene. Using the tool—a comprehensive software package ImageURL/B6TGH-3XNT22T-2-12/0?wchp=dGLbVzW-zSkzS" alt="Image" title="Image" style="vertical-align:bottom" border="0" height=11 width="72"/> -III (MAXimum CREDible accident analysis)—nine different scenarios, one for each storage unit, have been studied. It is observed that the accident scenario for chlorine (instantaneous release followed by dispersion) leads to the largest area-under-lethal-impact, while the accident scenario for propylene (CVCE followed by fireball) forecasts the most intense damage per unit area. The accidents involving propylene, benzene, and fuel oil have a high possibility of causing domino/secondary accidents as their destructive impacts (shock waves, heat load) would envelope other storage and process units.Besides demonstrating the utilizability of ImageURL/B6TGH-3XNT22T-2-12/0?wchp=dGLbVzW-zSkzS" alt="Image" title="Image" style="vertical-align:bottom" border="0" height=11 width="72"/> -III, this study also focuses attention on the need to bestow greater effort towards risk assessment/crisis management. The authors hope that the study will highlight the severity of the risk posed by the industry and thus generate safety consciousness among plant managers. The study may also help in developing accident-prevention strategies and the installation of damage control devices.     

A bee in the corridor: centering and wall-following

In an attempt to better understand the mechanism underlying lateral collision avoidance in flying insects, we trained honeybees (Apis mellifera) to fly through a large (95-cm wide) flight tunnel. We found that, depending on the entrance and feeder positions, honeybees would either center along the corridor midline or fly along one wall. Bees kept following one wall even when a major (150-cm long) part of the opposite wall was removed. These findings cannot be accounted for by the “optic flow balance” hypothesis that has been put forward to explain the typical bees’ “centering response” observed in narrower corridors. Both centering and wall-following behaviors are well accounted for, however, by a control scheme called the lateral optic flow regulator, i.e., a feedback system that strives to maintain the unilateral optic flow constant. The power of this control scheme is that it would allow the bee to guide itself visually in a corridor without having to measure its speed or distance from the walls.     

浅谈遥感解译技术在生态环境状况评价中的应用

简述了遥感解译这一新兴学科的技术特点,以及它在生态环境状况监测和评价中所起的重要作用。详细介绍了利用遥感解译手段对影像进行处理的技术流程和方法,提出了用来判定生态环境状况的各类生态指数的计算方法。     

Measuring Plant Cover in Sagebrush Steppe Rangelands: A Comparison of Methods

Methods that are more cost-effective and objective are needed to detect important vegetation change within acceptable error rates. The objective of this research was to compare visual estimation to three new methods for determining vegetation cover in the sagebrush steppe. Fourteen management units at the US Sheep Experiment Station were identified for study. In each unit, 20 data collection points were selected for measuring plant cover using visual estimation, laser-point frame (LPF), 2 m above-ground-level (AGL) digital imagery, and 100-m AGL digital imagery. In 11 of 14 management units, determinations of vegetation cover differed (P < 0.05). However, when combined, overall determinations of vegetation cover did not differ. Standard deviation, corrected sums of squares, coefficient of variation, and standard error for the 100 m AGL method were half as large as for the LPF and less than the 2-m AGL and visual estimate. For the purpose of measuring plant cover, all three new methods are as good as or better than visual estimation for speed, standard deviation, and cost. The acquisition of a permanent image of a location is an important advantage of the 2 and 100 m AGL methods because vegetation can be reanalyzed using improved software or to answer different questions, and changes in vegetation over time can be more accurately determined. The reduction in cost per sample, the increased speed of sampling, and the smaller standard deviation associated with the 100-m AGL digital imagery are compelling arguments for adopting this vegetation sampling method.     

Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than $3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.     

Developments in remote sensing, dynamic modelling and GIS applications for integrated coastal zone management

The International Institute for Aerospace Survey and Earth Sciences (ITC) has a research programme that should result in an integrated environmental coastal zone management system through three subprojects. The programme aims to develop methodologies and tools for assessing coastal zone changes, and for the evaluation of scenarios for coastal zone management, based on a spatio-temporal Geographical Information System (GIS) working platform which integrates remote sensing data, physical-morphodynamic and eco-hydrologic modelling, and a decision support system. The first subproject develops methodologies for the generation of optimum Remote Sensing (RS) data sets, leading to better interpretation and complementary use of conventional and new remote sensing imagery. It also integrates RS, GIS, and modelling through hypothesis generation, parameter estimation, evaluation and validation. The second subproject facilitates qualitative and quantitative analysis and prediction of the physical aspects of coastal landscape development under the influence of natural processes and human impacts. This subproject is based on the application of remote sensing and dynamic modelling. The third subproject leads to a spatio-temporal working platform which supports data integration of RS and in-situ measurements, and qualitative and quantitative analysis for the prediction of coastal landscape development. Both support decision making in Integrated Coastal Zone Management.     

Diagnosis of sewer pipe defects on image recognition of multi-features and support vector machine in a southern Chinese city

An image-recognition-based diagnosis system of pipe defect types was established. 1043 practical pipe images were gathered by CCTV robot in a southern Chinese city. The overall accuracy of the system is 84% and the highest accuracy is 99.3%. The accuracy shows positive correlation to the number of training samples. Closed circuit television (CCTV) systems are widely used to inspect sewer pipe conditions. During the diagnosis process, the manual diagnosis of defects is time consuming, labor intensive and error prone. To assist inspectors in diagnosing sewer pipe defects on CCTV inspection images, this paper presents an image recognition algorithm that applies features extraction and machine learning approaches. An algorithm of image recognition techniques, including Hu invariant moment, texture features, lateral Fourier transform and Daubechies (DBn) wavelet transform, was used to describe the features of defects, and support vector machines were used to classify sewer pipe defects. According to the inspection results, seven defects were defined; the diagnostic system was applied to a sewer pipe system in a southern city of China, and 28,760 m of sewer pipes were inspected. The results revealed that the classification accuracies of the different defects ranged from 51.6% to 99.3%. The overall accuracy reached 84.1%. The diagnosing accuracy depended on the number of the training samples, and four fitting curves were applied to fit the data. According to this paper, the logarithmic fitting curve presents the highest coefficient of determination of 0.882, and more than 200 images need to be used for training samples to guarantee the accuracy higher than 85%.     

Whale Wars and the Axiomatization of Image Events on the Public Screen

The essay interrogates Animal Planet's television show Whale Wars, and the use of footage from that show in a commercial for one of the network's other shows, How Stuff Works, to examine the way these texts interact within the public screen. I argue that the (re)presentation of whale kill footage further instantiates an image event as a commodity and rhetorically reconciles the image event into a capitalist ideology counter to the social movement message constructed on Whale Wars—and by proxy allows the image event to play out only via a profit-motive tied to the death of the whale.     

图像型火灾火焰探测原理

根据火灾火焰的颜色特性、闪烁频率特性、形态变化特性及其发生发展在图像上所表现出来的趋势特征,设计分析了图像型火灾火焰的序列帧识别原理,并结合工程应用的分类特性,论述了图像型火灾火焰的干扰及其使用图像的小块分割算法和外形判断的干扰排除方法.     

Use of remote sensing for the characterization of the Mediterranean coastal environment—the case ofPosidonia oceanica

The beds ofPosidonia oceanica, a marine vascular plant species endemic to the Mediterranean, form a major Mediterranean marine ecosystem. These beds are well-developed along the sandy east coast of Corsica, where the continental shelf is wide and extends for ca. 100 km. The upper limit of this ecosystem has been mapped by means of a computer image processing technique using 1/20 000 colour photographs. One of the major problems for image processing in the marine environment is the impact of the water layer (of variable thickness and quality), which can result in variations of the spectral signature for a particular vegetation or bottom type. In an attempt to reduce the impact of this artefact, a processing technique that takes into account bathymetric factors has been tested. Cartographical data obtained for an area extending from Bastia to Solenzara are presented. In the vicinity of the mouths of coastal rivers, a systematic indentation of the upper limit of the seagrass beds has been revealed. On the basis of these results, local variations in the quality of the marine environment can be detected, in particular with regard to salinity, turbidity and/or the impact of sedimentation. The overall surface area of thePosidonia oceanica beds has also been calculated.