Дисертації з теми "Rain measuring"

Simulations based on a month of radar data from Florida, and a summer of radar data from Nelspruit, South Africa, were used to quantify the errors in the measurement of mean areal rainfall which arise simply as a result of the extreme variability of convective rainfall, even with perfect remote sensing instruments. The raingauge network measurement errors were established for random and regular network configurations using daily and monthly radar-rainfall accumulations over large areas. A relationship to predict the measurement error for mean areal rainfall using sparse networks as a function of raining area, number of gauges, and the variability of the rainfield was developed and tested. The manner in which the rainfield probability distribution is transformed under increasing spatial and temporal averaging was investigated from two perspectives. Firstly, an empirical relationship was developed to transform the probability distribution based on some measurement scale, into a distribution based on a standard measurement length. Secondly, a conceptual model based on multiplicative cascades was used to derive a scale independent probability distribution.

Rainfall passing over a given area is a highly dynamic process; it changes constantly in form and intensity. It varies constantly on short spatial and temporal scales that makes real time measurements of the amount of rainfall challenging. Measuring and sensing rain is important to be able to understand and control our urban environment. Traditionally, rainfall analysis for hydrologic modelling use spatial measurements collected at various sparsely spread observation points using rain gauges working on various principles such as weighing type, tipping bucket, capacitive type etc. An accurate representation of spatial model of rainfall is essential for hydrological operational purposes such as forecasting of river flow, flood irrigation planning and modelling of catchment areas. Measurement of drop size distribution are also exploited to investigate microphysics of precipitation and to improve rainfall remote sensing estimation techniques. However, the high initial costs of convectional rain gauges prevent collection of data with high spatial resolution. The research looks at investigating the sensor stack to be a part of an integrated sensor approach to develop a device architecture for the development of low cost integrated rain sensing and measuring the rain. The device architecture consists of three main stacks – energy generation layer, sensing layer, processing layer. The raindrop on impact causes vibration on the device surface. This force exerted by the raindrop causes a deflection and is measured indirectly by the use of a thin film piezo sensor. As part of the work, we find there is a good correlation between the vibrations caused and the size or volume of the raindrop by indirectly measuring the impact force of the raindrop. The working range of the device is between 100hz and 2000hz, which includes the first modal peak of the impact that acts as an amplification to the drop's impact. Using this information, the device is able to calculate the raindrop size distribution and the rain intensity. Calibration of the device is key as we are measuring the impact force of the rain drops and correlating it to the size of the drop. Primary, not all rain drops will fall on the device at terminal velocity (the main assumption for calibration of the device), as the fall velocity of the droplet may also be affected by the wind. Secondly, the spatial variation of the frequency response function in Volts/Newton in decreasing order from the centre of the plate.

Rail track asset sighting distance must be checked regularly to ensure the continued and safe operation of rolling stock. Methods currently used to check asset line-of-sight involve manual labour or laser systems. Video cameras and computer vision techniques provide one possible route for cheaper, automated systems. Three categories of computer vision method are identified for possible application: two-dimensional object recognition, two-dimensional object tracking and three-dimensional scene recovery. However, presented experimentation shows recognition and tracking methods produce less accurate asset line-of-sight results for increasing asset-camera distance. Regarding three-dimensional scene recovery, evidence is presented suggesting a relationship between image feature and recovered scene information. A novel framework which learns these relationships is proposed. Learnt relationships from recovered image features probabilistically limit the search space of future features, improving efficiency. This framework is applied to several scene recovery methods and is shown (on average) to decrease computation by two-thirds for a possible, small decrease in accuracy of recovered scenes. Asset line-of-sight results computed from recovered three-dimensional terrain data are shown to be more accurate than two-dimensional methods, not effected by increasing asset-camera distance. Finally, the analysis of terrain in terms of effect on asset line-of-sight is considered. Terrain elements, segmented using semantic information, are ranked with a metric combining a minimum line-of-sight blocking distance and the growth required to achieve this minimum distance. Since this ranking measure is relative, it is shown how an approximation of the terrain data can be applied, decreasing computation time. Further efficiency increases are found by decomposing the problem into a set of two-dimensional problems and applying binary search techniques. The combination of the research elements presented in this thesis provide efficient methods for automatically analysing asset line-of-sight and the impact of the surrounding terrain, from captured monocular video.

This research attempts to estimate the increased value of land in the form of house prices as a result of improved accessibility owing to the construction of Light Rail Transit (LRT) systems. Kelana Jaya Line LRT system is chosen as the case study in this research. Hedonic house price modelling and Geographically Weighted Regression (GWR) are employed to measure the effects of the LRT system on house prices in the Klang Valley, Malaysia (2004 and 2005 transactions). Selling price, structural attributes, land use and socio-economic attributes were collected from the Department of Valuation and Services of Malaysia database, selected maps and reports. Fifty-five factors that are likely to influence house price were identified and used to measure the overall effects of the LRT system on house prices. However, only significant variables were included in the final deliberation and these were identified by using correlation analysis and step-wise procedures. The outcome of this study shows a positive relationship between the existence of the LRT system and house prices. In short, people are willing to pay a higher price in order to live within close proximity to a rail transit station. The hedonic house price model suggests - for houses that are located within two-kilometre radius - prices decrease as the distance increases from the LRT station; for both straight-line-distance and network-distance. However, since hedonic house price models are global, the results produced by the model are applied equally for the entire area, and therefore may hide important local differences in the determinants of house prices. Spatial processes are instead seen to be heterogeneous in which the measurement of a relationship depends in part on where the measurement is taken. The generalisation of the effects of the LRT system on house prices is found to be consistent when it is examined further by employing a GWR model, which reveals that house prices decrease only for majority of houses located in the Petaling Jaya area and high-rise units located in Bangsar and Kerinchi. Yet, the majority of houses located in Wangsa Maju-Maluri area are found to be not affected by the existence of the LRT system. The GWR results indicate a statistical significant improvement over the global model for both straight-linedistance and network-distance models even after taking into account the extra degrees of freedom. The highest significant positive price premiums are found in houses that are located within 1,001-1,500 metres of straight-line-distance and 501-1,000 metres of networkdistance. The findings summarised in the thesis have important implications for policy implementation. Firstly, the research findings provide justification for potential implementation of a Land Value Capture (LVC) policy; a policy that can be implemented in order to provide a funding mechanism for the new transport infrastructure. This is due to the fact that the construction of rail transit systems should not be viewed as a subsidised service for the poor but as an investment that returns a profit through increased land values. Strategies in a LVC policy that may be implemented include property and sales taxes, realestate lease and sales revenues, fare-box revenues, fees on everything from parking to business licenses, join development, tax increment financing, special assessment districts, equity participation and public-private partnership. This approach has become a common practice in some more developed countries such as in the United Kingdom (UK) and United States (US). Finally, having a method to measure the land value premium due to the improvement in transportation service can facilitate alternative options or scenarios to be assessed. For example, different transport schemes for the same route may give rise to different land value capture potential, which may, in turn, help determine which transport scheme to pursue. This study therefore contributes to the growing literature on the positive relationship between the existence of the LRT system and house price by providing more accurate, robust and reliable empirical evidence as shown in the approach and the outcome of this research. In particular, it has produced meaningful results by addressing the nature of spatial process; spatial heterogeneity.

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Includes bibliographical references (leaves 78-81).
This dissertation reports upon the findings of a study undertaken in Cape Town to measure the impacts of park-and-ride facility upgrades on commuting behaviour at selected rail stations. The study analysed data from two sources covering the period before and after park-andride facility upgrades at three affected rail stations (Brackenfell, Kraaifontein and Kuilsrivier) and three control stations. The purpose of including the control group was to assist in assessing whether any utilisation changes observed across the before and after periods were the result of external factors.

This work deals with construction of an experimental measuring stand. This stand will be used for research focused on wheel flange lubrication improvement. The construction is based on wheel flange lubrication system Tribotec OK-02. First part treats of rail vehicle dynamics and wheel flange lubrication problematics, second part describes construction itself.

碩士
國立中央大學
太空科學研究所
83
The main purpose of this paper is to do the comparison of recipitation and other atomspheric parmeters obtained from thehung-Li VHF Radar and Pan-Chiaou raiwinsonde station.The expri-ent conducted at 17:00 through 24;00 LT on Feb.21 . 1995 showome good correlation between the following parameterws, such echo power and terminal velocity of the precipitation, terminal veloc-ty and spectral width from precipitation, horizontal wind speed and turbulend echo power ,horizontal wind turlent spectral widthWhile no correlation between horizontal wind speed and spectral width from precupitation be capable of being observed . This isorthwhile to that the drift velocity (about 1~2m/s) of rain cellan be measure by useing SAD (spaced antenna drift) method . Weonclude that the precipitation observation are quite successfult Chung-Li radar station.

Error characteristics associated with satellite-derived precipitation products are important for atmospheric and hydrological model data assimilation, forecasting, and climate diagnostic applications. This information also aids in the refinement of physical assumptions within algorithms by identifying geographical regions and seasons where existing algorithm physics may be incorrect or incomplete. Examination of relative errors between independent estimates derived from satellite microwave data is particularly important over regions with limited surface-based equipments for measuring rain rate such as the global oceans and tropical continents. In this context, analysis of microwave based satellite datasets from the Tropical Rainfall Measuring Mission (TRMM) enables to not only provide information regarding the inherent uncertainty within the current TRMM products, but also serves as an opportunity to prototype error characterization methodologies for the TRMM follow-on program, the Global Precipitation Measurement (GPM) . Most of the TRMM uncertainty evaluation studies focus on the accuracy of rainfall accumulated over time (e.g., season/year). Evaluation of instantaneous rainfall intensities from TRMM orbital data products is relatively rare. These instantaneous products are known to potentially cause large uncertainties during real time flood forecasting studies at the watershed scale. This is more so over land regions, where the highly varying land surface emissivity offers a myriad of complications, hindering accurate rainfall estimation. The error components of orbital data products also tend to interact nonlinearly with hydrologic modeling uncertainty. Keeping these in mind, the present thesis fosters the development of uncertainty analysis using instantaneous satellite orbital data products (latest version 7 of 1B11, 2A25, 2A23, 2B31, 2A12) derived from the passive and active microwave sensors onboard TRMM satellite, namely TRMM Microwave Imager (TMI) and precipitation radar (PR). The study utilizes 11 years of orbital data from 2002 to 2012 over the Indian subcontinent and examines the influence of various error sources on the convective and stratiform precipitation types. Two approaches are taken up to examine uncertainty. While the first approach analyses independent contribution of error from these orbital data products, the second approach examines their combined effect. Based on the first approach, analysis conducted over the land regions of Mahanadi basin, India investigates three sources of uncertainty in detail. These include 1) errors due to improper delineation of rainfall signature within microwave footprint (rain/no rain classification), 2) uncertainty offered by the transfer function linking rainfall with TMI low frequency channels and 3) sampling errors owing to the narrow swath and infrequent visits of TRMM sensors. The second approach is hinged on evaluating the performance of rainfall estimates from each of these orbital data products by accumulating them within a spatial domain and using error decomposition methodologies. Microwave radiometers have taken unprecedented satellite images of earth’s weather, proving to be a valuable tool for quantitative estimation of precipitation from space. However, as mentioned earlier, with the widespread acceptance of microwave based precipitation products, it has also been recognized that they contain large uncertainties. One such source of uncertainty is contributed by improper detection of rainfall signature within radiometer footprints. To date, the most-advanced passive microwave retrieval algorithms make use of databases constructed by cloud or numerical weather model simulations that associate calculated microwave brightness temperature to physically plausible sample rain events. Delineation of rainfall signature from microwave footprints, also known as rain/norain classification (RNC) is an essential step without which the succeeding retrieval technique (using the database) gets corrupted easily. Although tremendous advances have been made to catapult RNC algorithms from simple empirical relations formulated for computational expedience to elaborate computer intensive schemes which effectively discriminate rainfall, a number of challenges remain to be addressed. Most of the algorithms that are globally developed for land, ocean and coastal regions may not perform well for regional catchments of small areal extent. Motivated by this fact, the present work develops a regional rainfall detection algorithm based on scattering index methodology for the land regions of study area. Performance evaluation of this algorithm, developed using low frequency channels (of 19 GHz, 22 GHz), are statistically tested for individual case study events during 2011 and 2012 Indian summer monsoonal months. Contingency table statistics and performance diagram show superior performance of the algorithm for land regions of the study region with accurate rain detection observed in 95% of the case studies. However, an important limitation of this approach is comparatively poor detection of low intensity stratiform rainfall. The second source of uncertainty which is addressed by the present thesis, involves prediction of overland rainfall using TMI low frequency channels. Land, being a radiometrically warm and highly variable background, offers a myriad of complications for overland rain retrieval using microwave radiometer (like TMI). Hence, land rainfall algorithms of TRMM TMI have traditionally incorporated empirical relations of microwave brightness temperature (Tb) with rain rate, rather than relying on physically based radiative transfer modeling of rainfall (as implemented in TMI ocean algorithm). In the present study, sensitivity analysis is conducted using spearman rank correlation coefficient as the indicator, to estimate the best combination of TMI low frequency channels that are highly sensitive to near surface rainfall rate (NSR) from PR. Results indicate that, the TMI channel combinations not only contain information about rainfall wherein liquid water drops are the dominant hydrometeors, but also aids in surface noise reduction over a predominantly vegetative land surface background. Further, the variations of rainfall signature in these channel combinations were seldom assessed properly due to their inherent uncertainties and highly non linear relationship with rainfall. Copula theory is a powerful tool to characterize dependency between complex hydrological variables as well as aid in uncertainty modeling by ensemble generation. Hence, this work proposes a regional model using Archimedean copulas, to study dependency of TMI channel combinations with respect to precipitation, over the land regions of Mahanadi basin, India, using version 7 orbital data from TMI and PR. Studies conducted for different rainfall regimes over the study area show suitability of Clayton and Gumbel copula for modeling convective and stratiform rainfall types for majority of the intraseasonal months. Further, large ensembles of TMI Tb (from the highly sensitive TMI channel combination) were generated conditional on various quantiles (25th, 50th, 75th, 95th) of both convective and stratiform rainfall types. Comparatively greater ambiguity was observed in modeling extreme values of convective rain type. Finally, the efficiency of the proposed model was tested by comparing the results with traditionally employed linear and quadratic models. Results reveal superior performance of the proposed copula based technique. Another persistent source of uncertainty inherent in low earth orbiting satellites like TRMM arise due to sampling errors of non negligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. This study investigates sampling uncertainty of seasonal rainfall estimates from PR, based on 11 years of PR 2A25 data product over the Indian subcontinent. A statistical bootstrap technique is employed to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall was found to exhibit seasonal variations. To give a practical demonstration of the implications of bootstrap technique, PR relative sampling errors over the sub tropical river basin of Mahanadi, India were examined. Results revealed that bootstrap technique incurred relative sampling errors of <30% (for 20 grid), <35% (for 10 grid), <40% (for 0.50 grid) and <50% (for 0.250 grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. In order to study the effect of sampling type on relative sampling uncertainty, the study compares the resulting error estimates with those obtained from latin hypercube sampling. Based on this study, it may be concluded that bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in in-situ validation data. One of the important goals of TRMM Ground Validation Program has been to estimate the random and systematic uncertainty associated with TRMM rainfall estimates. Disentangling uncertainty in seasonal rainfall offered by independent observations of TMI and PR enables to identify errors and inconsistencies in the measurements by these instruments. Motivated by this thought, the present work examines the spatial error structure of daily precipitation derived from the version 7 TRMM instantaneous orbital data products through comparison with the APHRODITE data over a subtropical region namely Mahanadi river basin of the Indian subcontinent for the seasonal rainfall of 6 years from June 2002 to September 2007. The instantaneous products examined include TMI and PR data products of 2A12, 2A25 and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products was quantified based on the performance metrics derived from the contingency table. For the seasonal daily precipitation over 10x10 grids, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition technique, performed to disentangle systematic and random errors, testified that the multiplicative error model representing rainfall from 2A12 algorithm, successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results indicate that even though the radiometer derived 2A12 is known to suffer from many sources of uncertainties, spatial and temporal analysis over the case study region testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered. These findings clearly document that proper characterization of error structure offered by TMI and PR has wider implications in decision making, prior to incorporating the resulting orbital products for basin scale hydrologic modeling. The current missions of GPM envision a constellation of microwave sensors that can provide instantaneous products with a relatively negligible sampling error at daily or higher time scales. This study due to its simplicity and physical approach offers the ideal basis for future improvements in uncertainty modeling in precipitation.

碩士
明道大學
產業創新與經營學系碩士班
100
When measuring performance for rail transport, most previous studies paid attention only to technical efficiency by using physical input and output data such as the number of employees, number of cars, etc. In this study we adopts data envelopment analysis (DEA) to evaluate both cost efficiency and revenue efficiency for some selected 20 railways over 2007 to 2009. We choose the number of cars, the number of employees, and their prices as inputs, and select passenger-kilometers, ton-kilometers and their prices as outputs. The results show that the average cost efficiency and revenue efficiency are 0.499 and 0.389, respectively. Based on the results, a performance matrix is established in which each railway’s cost and revenue efficiencies are indicated. Finally, strategies for ameliorating the operation of less cost efficiency and/or less revenue efficiency railways are proposed.

碩士
高雄餐旅學院
旅遊管理研究所
98
Since the official operation of the Taiwan High Speed Rail (THSR) in the west region of Taiwan, it has provided an alternative transportation option for medium and long distance passengers, and also intensified the competition between THSR and Taiwan Railways (TRA). Various marketing studies have indicated that developing customer-based brand equity is essential for companies in carrying out the defensive marketing strategies. It ensures that the customers will maintain the brand loyalty continuously for a particular brand. This study focuses on frequent passengers of THSR or TRA Tze-Chiang Express for medium or long distance travel, in order to explore the context of repurchase motivation. The repurchase motivation of a particular brand is an abstract and intangible value. This study applied Rasch Model for data analysis, which has been commonly used in psychological measurement and educational testing to measure certain latent traits of subjects. The empirical results indicate that the attributes that hinder the repurchase service of THSR are listed in the following order: “reasonable price”, “convenience of station locations” and “ease of transfer and frequency of connection service”; the attributes that increase the repurchase service of THSR are: “operating speed”, “cleanliness of the carriage” and “clean and green environment inside the stations”. On the other hand, the attributes that hinder the repurchase service of TRA Tze-Chiang Express are: “trains on schedule”, “design for the barrier-free environment” and “clarity of train information and frequency of the timetable change”; the attributes that increase the repurchase service are: “convenience of station locations”, “ease of transfer and frequency of connection service” and “reasonable price”. The management implications are summarized as follows. THSR should: (1) offer promotions while improving service quality; (2) establish well-connected transit networks for joint transportation; (3) set up response standard process to achieve total quality management; (4) reduce machinery breakdowns and improve maintenance quality to ensure road safety. As for TRA Tze-Chiang Express, it should (1) improve the train on-time rate and minimize the perceived waiting time for passengers; (2) modify business strategies, educate the staffs, and streamline the equipments; (3) formulate marketing strategies in order to preserve frequent customers traveling in mid-to-long distance. In addition, in order to keep perpetual operation, it is recommended that the two companies should analyze the target customers and precisely stimulate the critical service attributes, cooperate to develop intermodal trasportation and continuously exceed customers’ expectations.