Using structured systems analysis to design an integrated system for transport planning and environmental analysis

This paper applies Yourdon's (1989) structured systems analysis techniques to transport planning, and the environmental analysis of transport plans. It is usual for planners to treat these activities as separate processes or 'systems'. Six serious shortcomings are identified in prevailing approaches to accounting for the environmental impacts of transport plans. The application of systems analysis has elucidated opportunities for overcoming these problems by integrating the two processes. The paper highlights the benefits of using these methods to direct research into, and development of, an integrated transport planning- environmental analysis system. Techniques applied are data flow diagrams, a Venn diagram and an entity-relationship diagram. Significant potential exists for integration within a geographic information system(GIS), although adoption of integrated methods by transport planners is likely to be incremental. Research confirms the usefulness of systems analysis in guiding the development of a GIS application to accommodate integrated transport planning and environmental analysis. Systems analysis also facilitates more careful and effective design of the databases underlying GIS analysis.

ScenicPlanner： planning scenic travel routes leveraging heterogeneous user-generated digital footprints

To facilitate the travel preparation process to a city, a lot of work has been done to recommend a POI or a sequence of POIs automatically to satisfy users＇ needs. How- ever, most of the existing work ignores the issue of planning the detailed travel routes between POIs, leaving the task to online map services or commercial GPS navigators. Such a service or navigator in terms of suggesting the shortest travel distance or time, which cannot meet the diverse requirements of users. For instance, in the case of traveling by driving for leisure purpose, the scenic view along the travel routes would be of great importance to users, and a good planning ser- vice should put the sceneries of the route in higher priority rather than the distance or time taken. To this end, in this paper, we propose a novel framework called ScenicPlanner for route recommendation, leveraging a combination of get- tagged image and check-in digital footprints from location- based social networks （LBSNs）. First, we enrich the road net- work and assign a proper scenic view score to each road seg- ment to model the scenic road network, by extracting relevant information from get-tagged images and check-ins. Then, we apply heuristic algorithms to iteratively add road segment and determine the travelling order of added road segments with the objective of maximizing the total scenic view score while satisfying the user-specified constraints （i.e., origin, desti- nation and the total travel distance）. Finally, to validate the efficiency and effectiveness of the proposed framework, we conduct extensive experiments on three real-world data sets from the Bay Area in the city of San Francisco, which con- tain a road network crawled from OpenStreetMap, more than 31 000 geo-tagged images generated by 1 571 Flickr users in one year, and 110 214 check-ins left by 15 680 Foursquare users in six months.