Historical collaborative geocoding

The latest developments in digital have provided large data sets that can increasingly easily be accessed and used. These data sets often contain indirect localisation information, such as historical addresses. Historical geocoding is the process of transforming the indirect localisation information to direct localisation that can be placed on a map, which enables spatial analysis and cross-referencing. Many efficient geocoders exist for current addresses, but they do not deal with the temporal aspect and are based on a strict hierarchy (..., city, street, house number) that is hard or impossible to use with historical data. Indeed historical data are full of uncertainties (temporal aspect, semantic aspect, spatial precision, confidence in historical source, ...) that can not be resolved, as there is no way to go back in time to check. We propose an open source, open data, extensible solution for geocoding that is based on the building of gazetteers composed of geohistorical objects extracted from historical topographical maps. Once the gazetteers are available, geocoding an historical address is a matter of finding the geohistorical object in the gazetteers that is the best match to the historical address. The matching criteriae are customisable and include several dimensions (fuzzy semantic, fuzzy temporal, scale, spatial precision ...). As the goal is to facilitate historical work, we also propose web-based user interfaces that help geocode (one address or batch mode) and display over current or historical topographical maps, so that they can be checked and collaboratively edited. The system is tested on Paris city for the 19-20th centuries, shows high returns rate and is fast enough to be used interactively.Comment: WORKING PAPE

Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Municipal solid-waste collection and disposal management using geospatial techniques in Maseru City, Lesotho

The use of geospatial techniques plays a crucial role in solid waste management. Collection and transportation of solid waste must be done in an efficient manner to avoid negative environmental impacts. At the time of study, there are no collection and routing system in Maseru City, leading to haphazard collection and disposal of Municipal Solid Waste (MSW). The aims of the study are: (i) To get an understanding and address the challenges faced by relevant stakeholders in solid waste management for Maseru City, (ii) To minimize adverse environmental impacts due to unscientific location of a disposal site and (iii) To minimize transportation costs and time during collection. The objectives of this study are summarized in the following: assess the current solid waste management, model suitable disposal/dump sites, determine MSW collection points and develop an optimal route for MSW collection and disposal in Maseru City. To assess the current solid waste management, 130 households, 73 community waste pickers, 15 Maseru City Council (MCC) management staff and 3 drivers were interviewed, and relevant data collected. Both primary and secondary data collection methods were used. Primary data collection methods included interviews, questionnaires and observations and creating feature classes in a geo database. Secondary data collection was done from relevant government repositories, digitization, and internet web sites. Simple random, area, cluster, and convenience sampling techniques were applied. Geographical Information Systems (GIS) and Remote sensing techniques were used to carry out suitability and network analysis, and location of MSW collection points. The study found out that the dump site (Ts'osane) was used by MCC and was not suitably located, hence more suitable alternative dump sites have been proposed. However, Ts'osane dump site was adopted in the analysis as it is the one used by MCC at the time of study. The researcher also found out that there were no designated MSW collection points and optimal routes, and that solid waste collection was done by both MCC and CBOs. In this regard, 334 collection points have been determined based on population and generated solid waste per Constituency and were randomly located in the study area. However, due to the policy that within 25m from the road no development could take place, only collection points which fell v within 25m from the road were selected and used in the routing analysis. One truck was used in the analysis, although more trucks could be used as it was at the time of study. For future research, there is a need to research on policy so that criteria for locating solid waste disposal and location of collection points is explicitly specified in the law to be able to conduct scientific analyses. A multi modal network analysis that would include all the vehicles used by MCC and the CBOs to develop a comprehensive network analysis that would also include necessary attributes such as road names, type, class, and length is needed

Optimisation of speed camera locations using genetic algorithm and pattern search

Road traffic accidents continue to be a public health problem and are a global issue due to the huge financial burden they place on families and society as a whole. Speed has been identified as a major contributor to the severity of traffic accidents and there is the need for better speed management if road traffic accidents are to be reduced. Over the years various measures have been implemented to manage vehicle speeds. The use of speed cameras and vehicle activated signs in recent times has contributed to the reduction of vehicle speeds to various extents. Speed cameras use punitive measures whereas vehicle activated signs do not so their use depends on various factors. Engineers, planners and decision makers responsible for determining the best place to mount a speed camera or vehicle activated sign along a road have based their decision on experience, site characteristics and available guidelines (Department for Transport, 2007; Department for Transport, 2006; Department for Transport, 2003). These decisions can be subjective and indications are that a more formal and directed approach aimed at bringing these available guidelines together in a model will be beneficial in making the right decision as to where to place a speed camera or vehicle activated sign is to be made. The use of optimisation techniques have been applied in other areas of research but this has been clearly absent in the Transport Safety sector. This research aims to contribute to speed reduction by developing a model to help decision makers determine the optimum location for a speed control device. In order to achieve this, the first study involved the development of an Empirical Bayes Negative Binomial regression accident prediction model to predict the number of fatal and serious accidents combined and the number of slight accidents. The accident prediction model that was used explored the effect of certain geometric and traffic characteristics on the effect of the severity of road traffic accident numbers on selected A-roads within the Nottinghamshire and Leicestershire regions of United Kingdom. On A-roads some model variables (n=10) were found to be statistically significant for slight accidents and (n=6) for fatal and serious accidents. The next study used the accident prediction model developed in two optimisation techniques to help predict the optimal location for speed cameras or vehicle activated signs. Pattern Search and Genetic Algorithms were the two main types of optimisation techniques utilised in this thesis. The results show that the two methods did produce similar results in some instances but different in others. Optimised results were compared to some existing sites with speed cameras some of the results obtained from the optimisation techniques used were within proximity of about 160m. A validation method was applied to the genetic algorithm and pattern search optimisation methods. The pattern search method was found to be more consistent than the genetic algorithm method. Genetic algorithm results produced slightly different results at validation in comparison with the initial results. T-test results show a significant difference in the function values for the validated genetic algorithm (M= 607649.34, SD= 1055520.75) and the validated pattern search function values (M= 2.06, SD= 1.17) under the condition t (79) = 5.15, p=0.000. There is a role that optimisation techniques can play in helping to determine the optimum location for a speed camera or vehicle activated sign based on a set of objectives and specified constraints. The research findings as a whole show that speed cameras and vehicle activated signs are an effective speed management tool. Their deployment however needs to be carefully considered by engineers, planners and decision makers so as to achieve the required level of effectiveness. The use of optimisation techniques which has been generally absent in the Transport Safety sector has been shown in this thesis to have the potential to contribute to improve speed management. There is however no doubt that this research will stimulate interest in this rather new but high potential area of Transport Safety