GIS‐based DSS for priority setting in humanitarian mine‐action

Mine contamination is one of the main obstacles to economic recovery and other types of progress in mine‐affected countries. Therefore, the primary goal of humanitarian demining operations is to clear all suspected minefields and restore them so as to make them available for their previous use. The customary financial shortfall results in the need for priority setting in the mine removal process. This paper describes and investigates a new approach to priority setting within mine action, with the introduction of a hierarchic GIS‐based decision support system (DSS). The proposed DSS is aimed at determining the objective priorities required to reduce the risks stemming from mine contamination. DSS is based on a combination of GIS analysis and a multicriteria method in order to enable efficacious mine action management, namely setting humanitarian demining priorities in order to optimally reduce the risk caused by mines. GIS is outlined as a powerful tool for the generation of aggregated information used in multicriteria analysis, as is the link between hierarchic decision levels in the proposed DSS. The results of a demonstration of the proposed GIS‐based DSS on mine‐affected water resources in Croatia are supplied.     

Performance‐improving techniques in web‐based GIS

WebGIS (also known as web‐based GIS and Internet GIS) denotes a type of Geographic Information System (GIS), whose client is implemented in a Web browser. WebGISs have been developed and used extensively in real‐world applications. However, when such a complex web‐based system involves the dissemination of large volumes of data and/or massive user interactions, its performance can become an issue. In this paper, we first identify several major potential performance problems with WebGIS. Then, we discuss several possible techniques to improve the performance. These techniques include the use of pyramids and hash indices on the server side to handle large images. To resolve server‐side conflicts originating from concurrent massive access and user interactions, we suggest clustering and multithreading techniques. Multithreading is also used to break down the long sequential, layer‐based data access to concurrent data access on the client side. Caching is suggested as a means to enhance concurrent data access for the same datasets on both the server and the client sides. The technique of client‐side dynamic data requests is used to improve data transmission. Compressed binary representation is implemented on both sides to reduce transmission volume. We also compare the performance of a prototype WebGIS with and without these techniques.     

GIS‐based route planning in landslide‐prone areas

Many parts of the world with young mountain chains, such as the Himalayas, are highly susceptible to landslides. Due to general ruggedness and steep slopes, roads provide the only way of transportation and connectivity in such terrains. Generally, landslide hazards are overlooked during route planning. In this study, in a test area in the Himalayas, various thematic layers, viz. landslide distribution, landslide hazard zonation, landuse/landcover, drainage order and lithology are generated and integrated using Remote Sensing–GIS techniques. The integrated data layer in raster form has been called a ‘thematic cost map’ and provides an estimate of the cost of route development and maintenance. The relative cost assignment is based on experts' knowledge. Route planning is based on neighbourhood analysis to find various movement possibilities from a pixel to its immediate neighbours. A number of patterns such as those analogous to movements in chess games have been considered. Two new neighbourhood patterns, named here Knight31 and Knight32, have been conceived in addition to commonly used Rook, Bishop and Knight patterns. The neighbourhood movement cost for moving from one pixel to a connected neighbour has been calculated for a 7×7 pixel window considering distance, gradient cost and thematic cost. Dijkstra's algorithm has been applied to compute the least‐cost route between source and destination points. A few examples are presented to show the utility of this approach for a landslide‐safe automatic route planning for a highly rugged hilly terrain.     

A GeoAgent‐based framework for knowledge‐oriented representation: Embracing social rules in GIS

While current Geographic Information Systems (GISs) can represent observational spatial data well, they have limited capabilities in representing some non‐observational social elements and goal‐driven behaviours that can be important factors in a wide range of geographic issues. Such social components may include laws, regulations, polices, plans, culture, and customs, as well as their relations and interactions with the geographic environment at different scales. Getting beyond traditional data‐centred approaches, this research presents a knowledge‐oriented strategy in order to address these issues within a GIS context. We incorporate two major conceptual elements. First, extending from conventional agent notions and their geographic applications, geographic agents (GeoAgents) are considered as a basic representation component to specifically address social rules and goal‐driven behaviours that impact the Earth and environmental systems. Second, in order to incorporate GeoAgents with current space–time representation, a new conceptual representation framework, called ‘fields, objects, time, GeoAgents, and relations’ (FOTAR), is introduced to address the cross‐scale processes of both social and natural interactions. A Java‐based prototype, GeoAgent‐based Knowledge System (GeoAgentKS), is described to implement this framework by integrating agent technologies with multiple data and knowledge representation techniques, such as expert systems, concept maps, mathematical models, and geospatial databases. The application of this prototype in a case study is also presented, investigating scale‐dependent human–environment interactions under different emergency situations for community water systems in Central Pennsylvania, USA. In this case study, a systematic set of methodologies of knowledge acquisition, representation, and confirmation for constructing GeoAgents' knowledge bases by using expert systems were explored to formalize high‐level knowledge and social behaviours in the FOTAR‐based representations. The results show that the proposed conceptual representation framework is achievable at both implementation and application levels, and the prototype tool is demonstrated to be valuable in facilitating knowledge sharing, policymaking, municipal management, and decision‐making, especially for real‐world emergency management.     

Extensions of GAP‐tree and its implementation based on a non‐topological data model

This paper discusses extensions of GAP‐trees from three aspects and its implementation based on non‐topological structure in order to enhance access to large vector data sets. First of all, we apply cartographic generalization rules to build a generalization procedure of the GAP‐tree, which makes coarse representations more consistent with human cognition. Second, we replace the three‐dimensional (pseudo‐) Reactive‐tree index with a 2D R‐tree index and a B‐tree index to improve the system efficiency. Finally, we compress a binary GAP‐tree into multi‐way GAP‐trees in order to reduce data redundancy. The shallower multi‐way GAP‐trees not only eliminate redundant data but also accelerate the system's response time. The extensions have been successfully implemented in PostgreSQL. A test of Beijing's land‐use data at the 1:10 000 scale demonstrates that the extended GAP‐trees are efficient, compact, and easy to implement.     

XML Web Service‐based development model for Internet GIS applications

Most of the current Internet Geographic Information System (GIS) applications cannot be shared and are not interoperable because of their heterogeneous environments. With the growth of Internet GIS, many difficulties have occurred in integrating GIS components because of their diversity. The main objective of this study is to suggest a new development model for dynamic and interoperable Internet GIS applications. The model is based mainly on the dynamic integration of Internet GIS components by applying Extensible Markup Language (XML), XML Web Service, Geography Markup Language (GML), and Scalable Vector Graphics (SVG), etc. The relevant technologies of Internet GIS were reviewed thoroughly, and then a new model was designed. During the design of the new model, typical examples of GIS Web Service components were suggested, together with practical structures for applications using these components. Six examples of components and four types of applications were suggested, and they were experimentally implemented for model validation and improvement. The suggested model and components will enable easier and more rapid development of Internet GIS applications through the dynamic integration of distributed GIS components. Users will be able to avoid redundancy and consequently reduce both cost and time during each GIS project.     

GIS‐based modeling of glacial hazards and their interactions using Landsat‐TM and IKONOS imagery

Hazard interactions in glacial and periglacial environments are of crucial importance due to their potential for causing major catastrophes. Nevertheless, glacial and periglacial hazards have usually been modeled separately to date. In this study, we therefore propose a methodological strategy for modeling and assessing glacial and periglacial hazard interactions on a regional scale, including ice avalanches, lake outbursts and periglacial debris flows. Due to climate‐related rapid changes in glacial and periglacial areas, methods which incorporate monitoring capacities are needed. Hence, the methods presented here are based on remote sensing data, which are particularly powerful for monitoring tasks, and GIS modeling. For ice avalanche and lake‐outburst hazard detection and modeling, we applied recently published methods based on Landsat‐TM imagery, terrain modeling and flow routing. For detection of potential debris‐flow initiation zones in steep debris reservoirs, we present a novel method based on image processing of IKONOS data and terrain modeling, followed by flow modeling. Using this method, we achieve the synthesis of the individual process modeling in order to assess the potential interactions. The modeling is applied to a study region in the central Swiss Alps. The results show that systematic modeling based on remote sensing and GIS is suitable for first‐order assessment of glacial and periglacial hazard interactions as well as assessments of possible consequences, including impacts on traffic routes and other infrastructure. Based on this, critical cases can be detected and analyzed by subsequent detailed studies.     

Mapping transit‐based access: integrating GIS,routes and schedules

Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam sonar mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. Multibeam acoustic data collected across a ～1000 km² area of the Carnarvon Shelf, Western Australia, were used in a predictive modelling approach to map eight seabed sediment parameters. Four machine learning models were used for the predictive modelling: boosted decision tree, random forest decision tree, support vector machine and generalised regression neural network. The results indicate overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness and Mean Grain Size. The study also demonstrates that predictive modelling using the combination of machine learning models has provided the ability to generate prediction uncertainty maps. However, the single models were shown to have overall better prediction performance than the combined models. Another important finding was that choosing an appropriate set of explanatory variables, through a manual feature selection process, was a critical step for optimising model performance. In addition, machine learning models were able to identify important explanatory variables, which are useful in identifying underlying environmental processes and checking predictions against the existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of covariance of physical and biological data for this area.     

GIS‐based multicriteria spatial modeling generic framework

Multicriteria analysis is a set of mathematical tools and methods allowing the comparison of different alternatives according to many criteria, often conflicting, to guide the decision maker towards a judicious choice. Multicriteria methods are used in spatial context to evaluate and compare spatial decision alternatives, often modeled through constraint‐based suitability analysis and represented by point, line, and polygon features or their combination, and evaluated on several space‐related criteria, to select a restricted subset for implementation. Outranking methods, a family of multicriteria methods, may be useful in spatial decision problems, especially when ordinal evaluation criteria are implied. However, it is recognized that these methods, except those devoted to multicriteria classification problems, are subject to computational limitations with respect to the number of alternatives. This paper proposes a framework to facilitate the incorporation and use of outranking methods in geographical information systems (GIS). The framework is composed of two phases. The first phase allows producing a planar subdivision of the study area obtained by combining a set of criteria maps; each represents a particular vision of the decision problem. The result is a set of non‐overlapping spatial units. The second phase allows constructing decision alternatives by combining the spatial units. Point, line and polygon feature‐based decision alternatives are then constructed as an individual, a grouping of linearly adjacent or a grouping of contiguous spatial units. This permits us to reduce considerably the number of alternatives, enabling the use of outranking methods. The framework is illustrated through the development of a prototype and through a step‐by‐step application to a corridor identification problem. This paper includes also a discussion of some conceptual and technical issues related to the framework.     

An adaptive approach to selecting a flow‐partition exponent for a multiple‐flow‐direction algorithm

Most multiple‐flow‐direction algorithms (MFDs) use a flow‐partition coefficient (exponent) to determine the fractions draining to all downslope neighbours. The commonly used MFD often employs a fixed exponent over an entire watershed. The fixed coefficient strategy cannot effectively model the impact of local terrain conditions on the dispersion of local flow. This paper addresses this problem based on the idea that dispersion of local flow varies over space due to the spatial variation of local terrain conditions. Thus, the flow‐partition exponent of an MFD should also vary over space. We present an adaptive approach for determining the flow‐partition exponent based on local topographic attribute which controls local flow partitioning. In our approach, the influence of local terrain on flow partition is modelled by a flow‐partition function which is based on local maximum downslope gradient (we refer to this approach as MFD based on maximum downslope gradient, MFD‐md for short). With this new approach, a steep terrain which induces a convergent flow condition can be modelled using a large value for the flow‐partition exponent. Similarly, a gentle terrain can be modelled using a small value for the flow‐partition exponent. MFD‐md is quantitatively evaluated using four types of mathematical surfaces and their theoretical ‘true’ value of Specific Catchment Area (SCA). The Root Mean Square Error (RMSE) shows that the error of SCA computed by MFD‐md is lower than that of SCA computed by the widely used SFD and MFD algorithms. Application of the new approach using a real DEM of a watershed in Northeast China shows that the flow accumulation computed by MFD‐md is better adapted to terrain conditions based on visual judgement.     

A data‐mining approach for assessing consistency between multiple representations in spatial databases

When different spatial databases are combined, an important issue is the identification of inconsistencies between data. Quite often, representations of the same geographical entities in databases are different and reflect different points of view. In order to fully take advantage of these differences when object instances are associated, a key issue is to determine whether the differences are normal, i.e. explained by the database specifications, or if they are due to erroneous or outdated data in one database. In this paper, we propose a knowledge‐based approach to partially automate the consistency assessment between multiple representations of data. The inconsistency detection is viewed as a knowledge‐acquisition problem, the source of knowledge being the data. The consistency assessment is carried out by applying a proposed method called MECO. This method is itself parameterized by some domain knowledge obtained from a second method called MACO. MACO supports two approaches (direct or indirect) to perform the knowledge acquisition using data‐mining techniques. In particular, a supervised learning approach is defined to automate the knowledge acquisition so as to drastically reduce the human‐domain expert's work. Thanks to this approach, the knowledge‐acquisition process is sped up and less expert‐dependent. Training examples are obtained automatically upon completion of the spatial data matching. Knowledge extraction from data following this bottom‐up approach is particularly useful, since the database specifications are generally complex, difficult to analyse, and manually encoded. Such a data‐driven process also sheds some light on the gap between textual specifications and those actually used to produce the data. The methodology is illustrated and experimentally validated by comparing geometrical representations and attribute values of different vector spatial databases. The advantages and limits of such partially automatic approaches are discussed, and some future works are suggested.     

Terrain complexity and uncertainties in grid‐based digital terrain analysis

The objective of this research is to study the relationship between terrain complexity and terrain analysis results from grid‐based digital elevation models (DEMs). The impact of terrain complexity represented by terrain steepness and orientation on derived parameters such as slope and aspect has been analysed. Experiments have been conducted to quantify the uncertainties created by digital terrain analysis algorithms. The test results show that (a) the RMSE of derived slope and aspect is negatively correlated with slope steepness; (b) the RMSE of derived aspect is more sensitive to terrain complexity than that of derived slope; and (c) the uncertainties in derived slope and aspect tend to be found in flatter areas, and decrease with increasing terrain complexity. The study shows that although primary surface parameters can be well defined mathematically, the implementation of those mathematical models in a GIS environment may generate considerable uncertainties related to terrain complexity. In general, when terrain is rugged with steep slopes, the uncertainty of derived parameters is quite minimal. While in flatter areas, the DEM‐based derivatives, particularly the aspect, may contain a great amount of uncertainty, causing significant limitation in applying the analytical results.     

A chironomid‐based model for inferring late‐summer hypolimnetic oxygen in southeastern Ontario lakes

Hypolimnetic oxygen depletion has been accelerated in many lakes due to cultural eutrophication. However, the extent and magnitude of environmental change is difficult to ascertain due to the lack of historical records. Larval Chironomidae (Diptera) are useful proxy indicators of oxygen, as they show a wide range of tolerances to oxygen conditions and their chitinous head capsules preserve well in lake sediments. Using paleolimnological techniques, chironomid assemblages from the surface sediments of 42 southeastern Ontario lakes were related to environmental conditions. Hypolimnetic oxygen conditions, measured as the average endofsummer hypolimnetic dissolved oxygen (AvgDO_(Summ)), explained the most variation in the chironomid assemblages, whereas dissolved inorganic carbon, the Anoxic Factor, max. depth and total phosphorus concentrations were also correlated with assemblage composition. Based on the relative abundances of 45 chironomid taxa, a robust, partial least squares (PLS) regression transfer function for AvgDO_(Summ) was constructed (r² = 0.74, r² _(jack) = 0.58, n = 40). This new transfer function should allow paleolimnologists to directly track past trends in hypolimnetic oxygen levels.     

Ecological footprint analysis based on RS and GIS in arid land

Sustainable development has become a primary objective for many countries and regions throughout the world now. The ecological footprint (EF) is a kind of concise method of quantifiably measuring the natural capital consumption and it can reflect the goal of sustainability. In this paper, the concept, the theory and method of ecological footprint are introduced. On this basis, the study brings forward the method of ecological footprint and capacity prediction. The method is employed for the ecological footprint prediction combining consumption model with population model and the technique is adopted for the ecological capacity (EC) prediction uniting the Geographical Cellular Automata (Geo CA) and Geographic Information System (GIS). The above models and methods are employed to calculate EF and EC in 1995 and 2000 and predict them in 2005 in Hexi Corridor. The result shows that EF is continually increasing, and EC ascended in the anterior 5 years and will descend in the posterior 5 years. This suit of method is of the character of accuracy and speediness.     

A combinatorial data model for representing topological relations among 3D geographical features in micro‐spatial environments

This research is motivated by the need for 3D GIS data models that allow for 3D spatial query, analysis and visualization of the subunits and internal network structure of ‘micro‐spatial environments’ (the 3D spatial structure within buildings). It explores a new way of representing the topological relationships among 3D geographical features such as buildings and their internal partitions or subunits. The 3D topological data model is called the combinatorial data model (CDM). It is a logical data model that simplifies and abstracts the complex topological relationships among 3D features through a hierarchical network structure called the node‐relation structure (NRS). This logical network structure is abstracted by using the property of Poincaré duality. It is modelled and presented in the paper using graph‐theoretic formalisms. The model was implemented with real data for evaluating its effectiveness for performing 3D spatial queries and visualization.     

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.     

OpenCIS—Open Source GIS‐based web community information system

Geographic Information System (GIS) technology has many applications and plays a vital role in the majority of the daily operations by government and public administration. However, due to its technical complexity and cost, communities lacking the expertise and resources cannot benefit from this technology. The OpenCIS project, a user‐friendly free Open Source GIS‐based Web Community Information System, seeks to address this issue by bridging the gap between a simple map viewer and full GIS, representing one of the first steps towards the goal of grassroots empowerment through GIS technology.     

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.     

Street networks in relation to landforms：Implications for fast-growing cities

In addition to socio-economic factors,major landforms may affect the city structure and urban form. Here we show that landforms have significant effects on the city shape and street patterns of the fast-growing Iranian cities of Dezful (a river) and Khorramabad (mountains and valleys),but no clear effects on the cities of Yazd and Nain. Also,where the street orientation is peaked,the Gibbs/Shannon entropy (a measure of dispersion or spread) is low,but increases as the distribution becomes more uniform because of landform constraints. The streets in the old inner parts of all the cities are,on average,shorter and denser (more streets per unit area) than the streets of the newer outer parts. The entropies of the outer parts are also greater than those of the inner parts,implying that the street-length distribution gradually becomes more dispersed or spread as the city expands. All these cities have been fast growing in the past decades,with the newer outer parts expanding rapidly. As shown here,the rapidly formed outer parts (with greater dispersion in street patterns) have significantly different textures from those of the older inner parts,indicating different functionality and growth processes. These quantitative methods for street-network analysis can be used worldwide,particularly for analysing the effects of landforms on city shape and texture.