Ant intelligence for solving optimal path‐covering problems with multi‐objectives

Conventional methods have difficulties in forming optimal paths when raster data are used and multi‐objectives are involved. This paper presents a new method of using ant colony optimization (ACO) for solving optimal path‐covering problems on unstructured raster surfaces. The novelty of this proposed ACO includes the incorporation of a couple of distinct features which are not present in classical ACO. A new component, the direction function, is used to represent the ‘visibility’ in the path exploration. This function is to guide an ant walking toward the final destination more efficiently. Moreover, a utility function is proposed to reflect the multi‐objectives in planning applications. Experiments have shown that classical ACO cannot be used to solve this type of path optimization problems. The proposed ACO model can generate near optimal solutions by using hypothetical data in which the optimal solutions are known. This model can also find the near optimal solutions for the real data set with a good convergence rate. It can yield much higher utility values compared with other common conventional models.     

Fuzzy inference guided cellular automata urban‐growth modelling using multi‐temporal satellite images

This paper presents a fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on urban development is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. A defuzzification process converts the development potential to the required neighbourhood development level, which is taken by cellular automata as initial approximation for its transition rules. Such approximations are updated through spatial calibration over townships and temporal calibration with multi‐temporal satellite images. Assessment of the modelling results is based on three evaluation measures: fitness and Type I and Type II errors. The approach is applied to model the growth of the city of Indianapolis, Indiana over a period of 30 years from 1973 to 2003. A fitness level of 100 ±20% with 30% average errors can be achieved for 80% of the townships in urban‐growth prediction.     

A flexible multi‐source spatial‐data fusion system for environmental status assessment at continental scale

The monitoring of the environment's status at continental scale involves the integration of information derived by the analysis of multiple, complex, multidisciplinary, and large‐scale phenomena. Thus, there is a need to define synthetic Environmental Indicators (EIs) that concisely represent these phenomena in a manner suitable for decision‐making. This research proposes a flexible system to define EIs based on a soft fusion of contributing environmental factors derived from multi‐source spatial data (mainly Earth Observation data). The flexibility is twofold: the EI can be customized based on the available data, and the system is able to cope with a lack of expert knowledge. The proposal allows a soft quantifier‐guided fusion strategy to be defined, as specified by the user through a linguistic quantifier such as ‘most of’. The linguistic quantifiers are implemented as Ordered Weighted Averaging operators. The proposed approach is applied in a case study to demonstrate the periodical computation of anomaly indicators of the environmental status of Africa, based on a 7‐year time series of dekadal Earth Observation datasets. Different experiments have been carried out on the same data to demonstrate the flexibility and robustness of the proposed method.     

Testing the effects of positional uncertainty on spatial decision‐making

There is now increasing agreement that the uncertainty associated with spatial information should be represented to users in a manner that is comprehensive and unambiguous. To assist with this task, researchers have developed a variety of methods to portray spatial uncertainty. While there has been some testing of the effectiveness of these displays, the possible effects of such representations on decision‐making have not yet been thoroughly investigated. Indeed, studies from the psychological literature indicate that people do not always make the same decisions when presented with the same information, and they can also be sensitive to the effects of presentation, task, and context. This paper examines how the use of four different methods to represent positional uncertainty can affect spatial decision‐making. The authors found that extremely significant differences in participants' responses were exhibited, depending on the manner in which positional uncertainty was displayed, although little difference was observed in the ability of the participants to comprehend the four display methods. In addition, strong preferences were recorded for certain representations over others.     

An integrated TIN and Grid method for constructing multi‐resolution digital terrain models

Multi‐resolution terrain models are an efficient approach to improve the speed of three‐dimensional (3D) visualizations, especially for terrain visualization in Geographical Information Systems (GIS). As a further development to existing algorithms and models, a new model is proposed for the construction of multi‐resolution terrain models in a 3D GIS. The new model represents multi‐resolution terrains using two major methods for terrain representation: Triangulated Irregular Network (TIN) and regular grid (Grid). In this paper, first, the concepts and formal definitions of the new model are presented. Second, the methodology for constructing multi‐resolution terrain models based on the new model is proposed. Third, the error of multi‐resolution terrain models is analysed, and a set of rules is proposed to retain the important features (e.g. boundaries of man‐made objects) within the multi‐resolution terrain models. Finally, several experiments are undertaken to test the performance of the new model. The experimental results demonstrate that the new model can be applied to construct multi‐resolution terrain models with good performance in terms of time cost and maintenance of the important features. Furthermore, a comparison with previous algorithms/models shows that the speed of rendering for 3D walking/flying through has been greatly improved by applying the new model.     

GIS‐based multicriteria decision analysis: a survey of the literature

The integration of GIS and multicriteria decision analysis has attracted significant interest over the last 15 years or so. This paper surveys the GIS‐based multicriteria decision analysis (GIS‐MCDA) approaches using a literature review and classification of articles from 1990 to 2004. An electronic search indicated that over 300 articles appeared in refereed journals. The paper provides taxonomy of those articles and identifies trends and developments in GIS‐MCDA.     

NET‐DBSCAN: clustering the nodes of a dynamic linear network

NET‐DBSCAN, a method for clustering the nodes of a linear network, whose edges may be temporarily inaccessible, is introduced. The new method extends the idea of a well‐known spatial clustering method, named density‐based spatial clustering of applications with noise (DBSCAN). The new algorithm is described in detail and through a series of examples. A prototype system, which implements the algorithm, developed in Java and tested through a series of synthetic networks, is also presented. Finally, the application of NET‐DBSCAN method to support real‐world situations is briefly discussed.     

Evaluating the effects of land‐use development policies on ex‐urban forest cover: An integrated agent‐based GIS approach

We use a GIS‐based agent‐based model (ABM), named dynamic ecological exurban development (DEED), with spatial data in hypothetical scenarios to evaluate the individual and interacting effects of lot‐size zoning and municipal land‐acquisition strategies on possible forest‐cover outcomes in Scio Township, a municipality in Southeastern Michigan. Agent types, characteristics, behavioural methods, and landscape perceptions (i.e. landscape aesthetics) are empirically informed using survey data, spatial analyses, and a USDA methodology for mapping landscape aesthetic quality. Results from our scenario experiments computationally verified literature that show large lot‐size zoning policies lead to greater sprawl, and large lot‐size zoning policies can lead to increased forest cover, although we found this effect to be small relative to municipal land acquisition. The return on land acquisition for forest conservation was strongly affected by the location strategy used to select parcels for conservation. Furthermore, the location strategy for forest conservation land acquisition was more effective at increasing aggregate forest levels than the independent zoning policies, the quantity of area acquired for forest conservation, and any combination of the two. The results using an integrated GIS and ABM framework for evaluating land‐use development policies on forest cover provide additional insight into how these types of policies may act out over time and what aspects of the policies were more influential towards the goal of maximising forest cover.     

GLOBAL sensitivity analysis,GIS and multi‐criteria evaluation for a sustainable planning of a hazardous waste disposal site in Spain

A novel application of Sensitivity Analysis is presented. Useful applications of Global SA (GSA) already exist in the field of numerical modelling. In this paper, we explore the joint use of GSA, Geographical Information Systems (GIS) and Multi‐Criteria Evaluation. In this preliminary case study, 11 factors have been used to find the best place to locate a hazardous waste landfill. Two variance‐based methods (Sobol' and E‐FAST) are used to compute sensitivity indices in order to identify the factors that determine the variance of the model output. The results show that only three factors jointly account for 97% of the output variance. This information is employed to make a simplification of the original model, retaining only these three influential factors. In addition, if the SA is carried out in a pilot area where the spatial properties are similar to those of the whole region, we can infer the results to the whole area. This procedure achieves the goal of the study with an optimized allocation of resources for GIS data acquisition.     

Calibrating a neural network‐based urban change model for two metropolitan areas of the Upper Midwest of the United States

We parameterized neural net‐based models for the Detroit and Twin Cities metropolitan areas in the US and attempted to test whether they were transferable across both metropolitan areas. Three different types of models were developed. First, we trained and tested the neural nets within each region and compared them against observed change. Second, we used the training weights from one area and applied them to the other. Third, we selected a small subset (～1%) of the Twin Cities area where a lot of urban change occurred. Four model performance metrics are reported: (1) Kappa; (2) the scale which correct and paired omission/commission errors exceed 50%; (3) landscape pattern metrics; and (4) percentage of cells in agreement between model simulations. We found that the neural net model in most cases performed well on pattern but not location using Kappa. The model performed well only in one case where the neural net weights from one area were used to simulate the other. We suggest that landscape metrics are good to judge model performance of land use change models but that Kappa might not be reliable for situations where a small percentage of urban areas change.     

Local‐government data sharing: Evaluating the foundations of spatial data infrastructures

This paper presents a typology of local‐government data sharing arrangements in the US at a time when spatial data infrastructures (SDI) are moving into a second generation. In the first generation, the US National Spatial Data Infrastructure (NSDI) theoretically involved a pyramid of data integration resting on local‐government data sharing. Availability of local‐government data is the foundation for all SDI‐related data sharing in this model. However, first‐generation SDI data‐sharing activities and principles have gained only a tenuous hold in local governments. Some formalized data sharing occurs, but only infrequently in response to SDI programmes and policies. Previous research suggests that local‐government data sharing aligns with immediate organizational and practical concerns rather than state or national policies and programmes. We present research findings echoing extending these findings to show that local‐government data sharing is largely informal in nature and is undertaken to support existing governmental activities. NSDI principles remain simply irrelevant for the majority of surveyed local governments. The typology we present distinguishes four distinct types of local‐government data sharing arrangements that reflect institutional, political, and economic factors. The effectiveness of second generation, client‐service‐based SDI will be seriously constrained if the problems of local government take‐up fail to be addressed.     

Computation of the third‐order partial derivatives from a digital elevation model

Loci of extreme curvature of the topographic surface may be defined by the derivation function (T) depending on the first‐, second‐, and third‐order partial derivatives of elevation. The loci may partially describe ridge and thalweg lines. The first‐ and second‐order partial derivatives are commonly calculated from a digital elevation model (DEM) by fitting the second‐order polynomial to a 3×3 window. This approach cannot be used to compute the third‐order partial derivatives and T. We deduced formulae to estimate the first‐, second‐, and third‐order partial derivatives from a DEM fitting the third‐order polynomial to a 5×5 window. The polynomial is approximated to elevation values of the window. This leads to a local denoising that may enhance calculations. Under the same grid size of a DEM and root mean square error (RMSE) of elevation, calculation of the second‐order partial derivatives by the method developed results in significantly lower RMSE of the derivatives than that using the second‐order polynomial and the 3×3 window. An RMSE expression for the derivation function is deduced. The method proposed can be applied to derive any local topographic variable, such as slope gradient, aspect, curvatures, and T. Treatment of a DEM by the method developed demonstrated that T mapping may not substitute regional logistic algorithms to detect ridge/thalweg networks. However, the third‐order partial derivatives of elevation can be used in digital terrain analysis, particularly, in landform classifications.     

Multi‐visibility maps of triangulated terrains

Visibility computation on terrain models is an important research topic with many applications in Geographical Information Systems. A multi‐visibility map is the subdivision of the domain of a terrain into regions that, according to different criteria, encodes the visibility with respect to a set of view elements. We present an approach for visualising approximated multi‐visibility maps of a triangulated terrain corresponding to a set of view elements by using graphics hardware. Our method supports heterogeneous sets of view elements containing points, segments, polygonal chains and polygons and works for weak and strong visibility. Moreover, we are also able to efficiently solve approximated point and polygonal region multi‐visibility queries. To illustrate the usefulness of our approach we present results obtained with an implementation of the proposed algorithms.     

The role of sub‐national government and the private sector in future spatial data infrastructures

A Spatial Data Infrastructure (SDI) facilitates and coordinates the exchange and sharing of spatial data between stakeholders in the spatial data community. With this objective in mind, countries throughout the world are developing SDIs to manage and utilize their spatial data assets more effectively. These countries are developing SDIs to assist in various kinds of decision‐making at different levels of government jurisdictions that have an important impact within their national boundaries. However, current research shows that SDI is understood and described differently by stakeholders from different disciplines and different jurisdictional levels. Therefore, in many cases, SDI initiatives remain very much an innovation, even among practitioners. There are still uncertainties regarding the benefits and identities of SDIs, particularly in connection with how they evolve over time to meet user needs. This paper reviews and assesses the development of SDIs throughout the world over the past 15 years and the leadership role of national governments in SDI creation. This assessment is based on the SDI activities of various jurisdictions including Asia‐Pacific, Australia, North America, and Europe, and research into the worldwide effects of spatial information clearing houses. This assessment includes a discussion on emerging trends in SDI development, with particular reference to the increasingly important role played by sub‐national governments and the private sector within the framework of SDI development. The paper concludes with a discussion of the implications for future SDI development, including the delivery of a virtual world that has a particular focus on facilitating decision‐making at a community level within a national context.     

The potential for the use of Open Source Software and Open Specifications in creating Web‐based cross‐border health spatial information systems

Globalization is contributing to the blurring of borders making irrelevant the distinctions between domestic and international health problems. Cross‐border and global health spatial information systems (CBHSIS) are required to address the new global health challenges. There is a need to build and document alternatives for addressing the technological, economic, and sociocultural–political challenges encountered in the creation and deployment of these systems. This paper documents the building of a prototype Web‐based multimedia GIS system for use in a public health context using Open Source Software and Open Specifications and its deployment across the US–Mexico border. These technologies offer advantages in addressing several of the challenges previously mentioned. We highlight the technological and sociocultural–political issues important in successful collaboration across borders and cultures and in the creation of interoperable CBHSIS.     

A comparative analysis of DEM‐based models to estimate the solar radiation in mountainous terrain

Daily solar radiation estimates of four up‐to‐date solar radiation models (Solar Analyst, r.sun, SRAD and Solei‐32), based on a digital elevation model (DEM), have been evaluated and compared in a Mediterranean environment characterized by a complex topography. The models' estimates were evaluated against 40 days of radiometric data collected in 14 stations. Analyzed sky conditions ranged from completely overcast conditions to clear skies. Additionally, the role of the spatial resolution of the DEM has been evaluated through the use of two different resolutions: 20 and 100 m. Results showed that, under clear‐sky conditions, the daily solar radiation variability in the study area may be reasonably estimated with mean bias errors under 10% and root mean square error values of around 15%. On the other hand, results proved that the reliability of the estimates substantially decreases under overcast conditions for some of the solar radiation models. Regarding the role of the DEM spatial resolution, results suggested that the reliability of the estimates for complex topography areas under clear‐sky conditions improves using a higher spatial resolution.     

Image‐based quality assessment of road databasesX

In this paper an approach to the automatic quality assessment of existing geo‐spatial data is presented. The necessary reference information is derived automatically from up‐to‐date digital remotely sensed images using image analysis methods. The focus is on the quality assessment of roads as these are among the most frequently changing objects in the landscape. In contrast to existing approaches for quality control of road data, the data to be assessed and the objects extracted from the images are modelled and processed together. A geometric‐topologic relationship model for the roads and their surroundings is defined. Context objects such as rows of trees support the quality assessment of road vector data as they may explain gaps in road extraction. The extraction and explicit incorporation of these objects in the assessment of a given road database give stronger support for or against its correctness.

During the assessment existing relations between road objects from the database and extracted objects are compared to the modelled relations. The certainty measures of the objects are integrated into this comparison. Normally, more than one extracted object gives evidence for a road database object; therefore, a reasoning algorithm which combines evidence given by the extracted objects is used. If the majority of the total evidence argues for the database object and if a certain amount of this database object is covered by extracted objects, the database object is assumed to be correct, i.e. it is accepted, otherwise it is rejected. The procedure is embedded into a two‐stage graph‐based approach which exploits the connectivity of roads and results in a reduction of false alarms. The algorithms may be incorporated into a semi‐automatic environment, where a human operator only checks those objects that have been rejected.

The experimental results confirm the importance of the employed advanced statistical modelling. The overall approach can reliably assess the roads from the given database, using road and context objects which have been automatically extracted from remotely sensed imagery. Sensitivity analysis shows that in most cases the chosen two‐stage graph‐approach reduces the number of false decisions. Approximately 66% of the road objects have been accepted by the developed approach in an extended test area, 1% has been accepted though incorrect. Those false decisions are mainly related to the lack of modelling road junction areas.     

An environmental decision‐support system for the management of water pollution in a tidal river network

This paper is about the development of a decision‐support system for water‐pollution management and environmental planning. More specifically, the paper first presents the overall concept and the system architecture of a generic environmental decision‐support system (EDSS) and then develops an EDSS especially for analysing the tidal flow pattern and water quality of China's Pearl River Delta. The EDSS developed here employs the object‐oriented approach to design the environmental database and utilizes the system integration technology to develop the overall user‐friendly system that operates in the Windows environment. Furthermore, the system can be expanded to facilitate automated model selection and analysis. The EDSS should be of value for managing water quality of river networks with complicated flow patterns, such as that found in the Pearl River Delta.