Suchith Anand

Automated Production of Schematic Maps for Mobile Applications

The advent of high-end miniature technology, together with the increasing availability of large scale digital geographic data products, has created a demand for techniques and methodologies that assist in the automated generation of maps specifically tailored to mobile GIS applications. This paper concerns itself with the problem of automatic generation of schematic maps. Schematic maps are diagrammatic representations based on linear abstractions of networks. In the context of mobile mapping they are seen as being a particularly useful means of displaying transportation networks. This paper describes an algorithm that automates the production of schematic maps. The algorithm makes use of the simulated annealing optimisation technique. An implementation of the algorithm is also presented, together with experimental results.

Automated schematization for web service applications

For the purposes of this paper, a schematic map is a diagrammatic representation based on linear abstractions of networks. With the advent of technologies for web-based delivery of geospatial services it is essential to develop map generalization applications tailored for the same. This paper is concerned with the problem of producing automated schematic maps for web map applications. The paper looks at how previous solutions to the spatial conflict reduction can be adapted and applied to production of automated schematic maps for web services.

Geological hazards: From early warning systems to public health toolkits

Extreme geological events, such as earthquakes, are a significant global concern and sometimes their consequences can be devastating. Geographic information plays a critical role in health protection regarding hazards, and there are a range of initiatives using geographic information to communicate risk as well as to support early warning systems operated by geologists. Nevertheless we consider there to remain shortfalls in translating information on extreme geological events into health protection tools, and suggest that social scientists have an important role to play in aiding the development of a new generation of toolkits aimed at public health practitioners. This viewpoint piece reviews the state of the art in this domain and proposes potential contributions different stakeholder groups, including social scientists, could bring to the development of new toolkits.

Spatially clustered associations in health related geospatial data

Overlaying maps using a desktop GIS is often the first step of a multivariate spatial analysis. The potential of this operation has increased considerably as data sources an dWeb services to manipulate them are becoming widely available via the Internet. Standards from the OGC enable such geospatial ‘mashups’ to be seamless and user driven, involving discovery of thematic data. The user is naturally inclined to look for spatial clusters and ‘correlation’ of outcomes. Using classical cluster detection scan methods to identify multivariate associations can be problematic in this context, because of a lack of control on or knowledge about background populations. For public health and epidemiological mapping, this limiting factor can be critical but often the focus is on spatial identification of risk factors associated with health or clinical status. In this article we point out that this association itself can ensure some control on underlying populations, and develop an exploratory scan statistic framework for multivariate associations. Inference using statistical map methodologies can be used to test the clustered associations. The approach is illustrated with a hypothetical data example and an epidemiological study on community MRSA. Scenarios of potential use for online mashups are introduced but full implementation is left for further research.

Development of a Digital Accident Hotspot Map for ADAS Applications Using Geospatial Methods in GIS

Digital maps have a large potential to support safety-related Advanced Driver Assistance Systems (ADAS) by providing detailed road and environment information. However, one critical attribute – road accident hotspot – is not available from existing digital maps, and is also difficult to derive from practical surveying. This paper provides a Geographical Information Systems (GIS)-based approach for the production of digital hotspot maps, based on a historical accident dataset and geospatial methods in a GIS. In this approach, firstly the Kernel Density Estimation (KDE) method was used to identify hotspot distribution; secondly the Percent Volume Contour (PVC) method was coupled with KDE to extract hotspot patterns; and finally the map layers of hotspot patterns were integrated with classical navigation maps. Following a description for geospatial hotspot production, the derivation of hotspot property data is also discussed. In order to prove this approach, a small-area case study was carried out in the City Centre of Nottingham. The presented results demonstrate that this approach is useful and effective for solving the hotspot creation problem for ADAS, but other future works will be required to improve data effectiveness.

Geospatial binding for transdisciplinary research in crop science: the GRASPgfs initiative

The paper retraces the GRASPgfs endeavor (Geospatial Resource for Agricultural Species and Pests with integrated workflow modelling to support Global Food Security) between multiple disciplines around a common objective of facilitating research and model simulations for sustainable food security. Within this endeavor, the geospatial media has been the enabler for multidisciplinary research in crop modelling. Geospatial genetic-trait variations and associations with environmental forecasting were the main focus of the GRASPgfs. Designing the platform achieving this objective generated a transdisciplinary vision of modelling and forecasting for sustainable agriculture. Based on interoperability principles, seamless access as well as sharing for data, metadata and processing models, the design is described in this paper. This geospatial binding facilitates and supports new types of hypotheses and analysis as illustrated in the paper with a landscape genetic case study (bambara groundnut) and a crop disease modelling (eyespot disease). The approach and the eGRASP platform are generic enough to accommodate further complexity into the integrated modelling that this geospatial binding enables.

Automated Schematic Mapping for MobileGIS: Technical developments and Human Factors requirements

This paper looks at how human factors requirements can be considered in the context of graphic conflict reduction for mobile GIS applications. Currently this reduction is achieved by using schematic mapping techniques. With the advent of high-end miniature technology as well as digital geographic data products like OSMasterMap and OSCAR, it is essential to devise proper methodologies for map generalization specifically tailored for MobileGIS applications. This paper is concerned with the problem of producing schematic maps suitable for rendering on mobile display devices (e.g. PDAs). The application of schematic mapping can be thought of as a data reduction technique for large scale datasets to make it suitable for rendering in mobile applications. These techniques have been based on computation and have not incorporated any understanding of how the simplification affects the ease of use of the maps. It is therefore desirable to devise suitable generalization techniques incorporating human factors considerations for generating schematic maps from large scale datasets for display on small display devices to be used for MobileGIS applications

Schematic maps in MobileGIS environments: an automated simulated annealing based case study

BackgroundMobileGIS refers to the use of geographic data in the field on mobile devices like networked personal digital assistant (PDA). The main components for MobileGIS are global positioning system (GPS), mobile device i.e. mobile phone, and communication network with GIS acting as the backbone. Map generalization is the process by which small scale maps are to be derived from large scale maps. This requires the appropriate use of map generalization operations to be performed subsequent to scale reduction to reduce the graphic conflict.MethodThis paper looks at how human factors requirements can be considered in the context of graphic conflict reduction for MobileGIS applications. Currently, this reduction is achieved by using schematic mapping techniques. The application of schematic mapping can be thought of as a data reduction technique for large scale datasets to make it suitable for rendering in mobile applications. This work makes use of simulated annealing (SA) based technique. At the start of the optimization process SA is presented with an initial approximate solution (or state). In the case of the schematic map problem, this will be the initial network (line features with travel time, each made up of constituent vertices). The initial state is then evaluated using a cost function C; this function assigns to the input state a score that reflects how well it measures up against a set of given constraints (topological, angle, minimum edge length, clearance). If the initial cost is greater than some user defined threshold (i.e. the constraints are not met adequately) then the algorithm steps into its optimization phase. This part of the process is iterative. At each iteration, the current state (i.e. the current network) is modified to make a new, alternative, approximate solution. The current and new states are said to be neighbours. The neighbours of any given state are generated usually in an application-specific way. The iterative process continues until stopping criteria are met (e.g. a suitably good solution is found or a certain amount of time has passed).ResultsPrototype software for producing schematic maps tailored for MobileGIS has been developed. The software makes use of the simulated annealing optimization technique. The software is currently implemented as a VBA script within ArcGIS. This technique has been used previously to control operations of displacement, deletion, reduction and enlargement of multiple map objects to help resolve spatial conflict arising due to scale reduction. These maps are subsequently displayed within the ArcPad application on a HP iPAQ PDA and tests have been carried out using different datasets. The results of applying simulated annealing based approach for automated schematic map generation is promising and further work will be done in enhancing the software with more functionality.ConclusionsDevelopment of automated schematic map generation techniques and cartographic specification for large scale digital geographic datasets suitable for MobileGIS applications was done and various tests carried out. Spatial conflict between feature classes at the specified scale ranges are to be dealt with by applying simulated annealing metaheuristic optimization technique.