On the Use of Weighted Linear Combination Method in GIS: Common and Best Practice Approaches

The weighted linear combination (WLC) technique is a decision rule for deriving composite maps using GIS. It is one of the most often used decision models in GIS. The method, however, is frequently applied without full understanding of the assumptions underling this approach. In many case studies, the WLC model has been applied incorrectly and with dubious results because analysts (decision makers) have ignored or been unaware of the assumptions. This paper provides a critical overview of the current practice with respect to GIS/WLC and suggests the best practice approach.     

An Adaptive Method of Non‐stationary Variogram Modeling for DEM Error Surface Simulation

Geostatistical characterization of local DEM error is usually based on the assumption of a stationary variogram model which requires the mean and variance to be finite and constant in the area under investigation. However, in practice this assumption is appropriate only in a restricted spatial location, where the local experimental variograms vary slowly. Therefore, an adaptive method is developed in this article to model non‐stationary variograms, for which the estimator and the indicator for characterization of spatial variation are a Voronoi map and the standard deviation of mean values displayed in the Voronoi map, respectively. For the adaptive method, the global domain is divided into different meshes with various sizes according to the variability of local variograms. The adaptive method of non‐stationary variogram modeling is applied to simulating error surfaces of a LiDAR derived DEM located in Sichuan province, China. Results indicate that the locally adaptive variogram model is more accurate than the global one for capturing the characterization of spatial variation in DEM errors. The adaptive model can be considered as an alternative approach to modeling non‐stationary variograms for DEM error surface simulation.     

城市扩张CA模型的参数敏感性分析

以广州市番禺区为研究区,构建了相应的城市扩张CA模型,从采样、邻域结构和微观元胞尺度等方面研究了CA模型的敏感性。首先通过改变模型采样比例、样本各个类别的比例等研究样本对模型参数的影响。然后分析不同的邻域结构与模型模拟精度的关系,并从微观尺度分析邻域元胞对中心元胞的影响。最后从空间尺度上分析CA模型在各种不同分辨率下的模拟结果,用景观指数剖析模拟结果的形态,同时在元胞摩尔邻域内分析其3×3邻域的城市发展密度变化情况。实验表明:(1)适当提高采样比例,会得到精度较高的权重,但训练样本中城市用地的比例应该与城市用地的转变量在全区的占比相匹配。(2)不论是采用摩尔邻域还是冯诺依曼邻域,模拟精度均随着空间尺度的增加而降低。在同一空间尺度下,采用摩尔邻域的模拟结果略好。相比冯诺依曼4个邻域元胞,摩尔邻域中的角点对中心元胞具有更大的影响。(3)随着空间分辨的降低,模拟结果的斑块数、斑块密度、聚集度和分形维度值在减少,结构变得简单,而且在微观的摩尔邻域中城市发展密度正在减少,即由高密度向低密度转换。     

Modeling global Hammond landform regions from 250‐m elevation data

In 1964, E.H. Hammond proposed criteria for classifying and mapping physiographic regions of the United States. Hammond produced a map entitled “Classes of Land Surface Form in the Forty‐Eight States, USA”, which is regarded as a pioneering and rigorous treatment of regional physiography. Several researchers automated Hammond?s model in GIS. However, these were local or regional in application, and resulted in inadequate characterization of tablelands. We used a global 250 m DEM to produce a new characterization of global Hammond landform regions. The improved algorithm we developed for the regional landform modeling: (1) incorporated a profile parameter for the delineation of tablelands; (2) accommodated negative elevation data values; (3) allowed neighborhood analysis window (NAW) size to vary between parameters; (4) more accurately bounded plains regions; and (5) mapped landform regions as opposed to discrete landform features. The new global Hammond landform regions product builds on an existing global Hammond landform features product developed by the U.S. Geological Survey, which, while globally comprehensive, did not include tablelands, used a fixed NAW size, and essentially classified pixels rather than regions. Our algorithm also permits the disaggregation of “mixed” Hammond types (e.g. plains with high mountains) into their component parts.     

基于GIS的OWA方法在城市防灾规划中的应用

作为一个多准则评价的相对较新概念,基于GIS的OWA方法可以通过权重计算产生多种决策策略。分析了OWA方法与布尔决策和权重线性叠加（WLC）等多准则评价方法在决策策略上的区别,介绍了依据次序重要性来计算次序权重和应用层次分析程序（AHP）构建比较矩阵来计算准则权重的方法,并应用于唐山市防灾规划,计算了唐山市地质灾害影响下的土地利用适宜度。在分析计算结果的基础上,为唐山市土地资源的合理开发提出了建议。     

A Genetic Algorithm for Tributary Selection with Consideration of Multiple Factors

Drainage systems are important components in cartography and Geographic Information Systems (GIS), and achieve different drainage patterns based on the form and texture of their network of stream channels and tributaries due to local topography and subsurface geology. The drainage pattern can reflect the geographical characteristics of a river network to a certain extent. To preserve the drainage pattern during the generalization process, this article proposes a solution to deal with many factors, such as the tributary length and the order in river tributary selection. This leads to a multi‐objective optimization problem solved with a Genetic Algorithm. In the multi‐objective model, different weights are used to aggregate all objective functions into a fitness function. The method is applied on a case study to evaluate the importance of each factor for different types of drainage and results are compared with a manually generalized network. The result can be controlled by assigning different weights to the factors. From this work, different weight settings according to drainage patterns are proposed for the river network generalization.     

“All the World's a Stage”: A GIS Framework for Recreating Personal Time‐Space from Qualitative and Quantitative Sources

This article presents a methodological model for the study of the space‐time patterns of everyday life. The framework utilizes a wide range of qualitative and quantitative sources to create two environmental stages, social and built, which place and contextualize the daily mobilities of individuals as they traverse urban environments. Additionally, this study outlines a procedure to fully integrate narrative sources in a GIS. By placing qualitative sources, such as narratives, within a stage‐based GIS, researchers can begin to tell rich spatial stories about the lived experiences of segregation, social interaction, and environmental exposure. The article concludes with a case study utilizing the diary of a postal clerk to outline the wide applicability of this model for space‐time GIS research.     

Site Suitability Analysis for Urban Development Using GIS Based Multicriteria Evaluation Technique

Identification of suitable site for urban development in hilly areas is one of the critical issues of planning. Site suitability analysis has become inevitable for delineating appropriate site for various developmental initiatives, especially in the undulating terrain of the hills. The study illustrates the use of geographic information system (GIS) and multicriteria evaluation (MCE) technique for selection of suitable sites for urban development in Mussoorie municipal area, Dehradun district, Uttarakhand. For this purpose Toposheet and IKONOS satellite data were used to generate various thematic layers using ArcGIS software. Criteria using five parameters, i.e. slope, road proximity, land use/land cover, land values and geological formation were used for site suitability analysis following land evaluation. The generated thematic maps of these criteria were standardized using pairwise comparison matrix known as analytical hierarchy process (AHP). A weight for each criterion was generated by comparing them with each other according to their importance. With the help of these weights and criteria, final site suitability map was prepared.     

The Influence of Urban Street Characteristics on Pedestrian Heat Comfort Levels in Philadelphia

This article demonstrates a way to model the urban microclimate using a combination of statistical analysis and a geographic information system (GIS). Field measurements of ambient temperature and relative humidity were collected in various urban settings at ground level over two surface materials and at two different times of the day. A panel autoregressive (PAR) model was created to conduct a regression analysis capable of accounting for the spatial autocorrelation. With the PAR analyses, selected urban street characteristics showed varying effects over the different surface materials and at different times of the day. The overall influences were consistent with previous findings. PAR models were then applied in GIS to create thermal prediction maps for the study area to determine the hot and cool spots. Since GIS is the most commonly used technology among a wide range of researchers and professionals, this article provides a means to improve the synthesis, integration, and sharing of information to understand the relationship between the heat‐vulnerable population and heat stress within the urban environment. This methodology will be useful in the effort to reduce the heat‐related morbidity and mortality, which are expected to increase with projected global warming.     

Appreciative GIS and Strength‐Based Community Change

Problem‐solving is embedded deeply in the digital DNA of GIS. Most projects involving GIS 1.0 and 2.0 raise community weaknesses, failures and other problems and use them to motivate change. The projects often create a future that does not differ greatly from the past or last long. Although looking into community problems is important and sometimes necessary, the steps of problem‐solving do not always leave people feeling happy. To inspire communities to create change based on their strengths and achievements, and to provide better participant experience, this article develops the concept of a new form of GIS called Appreciative GIS (AGIS). AGIS are grounded in the affirmative premise that every community, however challenged, is gifted with certain assets, potentials and strengths which, when effectively exploited, can take that community to a better and sustainable future. Based on Earth's internal structure, the article develops a useful layered community model where crust, mantle and core strata represent the community's body, life‐draining and life‐giving elements in that order. The model helps explain the different views of the community from current GIS and AGIS perspectives. A Total GIS (TGIS) cube is also developed and used to indicate that current GIS commonly focus on elements of the mantle or what we do not have, what we cannot do and what makes us weak. AGIS, on the other hand, dig up the core and cultivate what we have, what we can possibly do and what makes us strong. In a significant departure from the linear approach of problem‐solving, the article suggests implementing AGIS through a 7G cyclical method. The article contends that although AGIS may not be the whole enchilada, they can serve as a beacon of hope and a powerful source of inspiration especially for individuals and groups who are perceived or made to perceive themselves as dysfunctional, weak or poor.     

A GIS-based Investigation of Gaming Venue Catchments

Globally, the growth of the gambling industry in recent decades has raised questions about the potential for community costs associated with gambling development. In order to minimise the harms and maximise the gains for local, state and national economies, in many jurisdictions the industry is heavily regulated. Regulators rely upon a wide range of information sources to assist in decision making and are often concerned with issues that have socio‐spatial characteristics. Despite this, there have been few applications of geographical information systems (GIS) to gambling behaviour. This paper trials the use of a GIS‐based approach to investigate one aspect of gambling regulation, namely the spatial characteristics of gaming venue catchments. The research was conducted in a suburban region of Canberra, Australia. The results from the study show that the catchment areas of gaming venues can vary considerably and are more complex than previous studies have suggested. The regulatory implications of the findings are discussed as well as possible avenues for further GIS‐based research into gambling.     

Using GIS to improve public health emergency response in rural areas during the COVID-19 crisis: A case study of South Carolina,US

Geographic information systems (GIS) have become essential tools in the public health domain, especially when it comes to monitoring and surveillance of disease. The purpose of this article is to describe and explore the benefits of using GIS to improve public health emergency response during a global pandemic and, in particular, how to effectively optimize the allocation of public health resources in a rural setting using a data-driven approach that considers the multifactorial demand for new COVID-19 testing sites. Herein, the authors present their interprofessional project as an example of such efforts to inform applications for practice. The team developed a GIS-based multicriteria decision analysis model for use by decision-makers and public health experts in similar future planning and response scenarios. Focus is placed on rural characteristics (e.g., accessibility), vulnerable populations, and daily changing conditions (e.g., COVID-19 daily case fluctuations) that create additional challenges for public health agencies and policymakers.     

An open source GIS‐based Planning Support System: Application to the land use plan of La Troncal,Ecuador

Planning Support Systems (PSS) comprise a wide variety of geo‐technological tools related to GIS and spatial modeling aimed at addressing land planning processes. This article describes the OpenRules system, a PSS based on a previous system called RULES. Among OpenRules new features are its architecture, based exclusively on free and open source software, and its applicability to all land use types, including rural and urban uses. In addition, OpenRules incorporates an unlimited number of land evaluation factors and a new objective in land use spatial allocation. OpenRules has been programmed in Java and implemented as a module of the free GIS software gvSIG, with full integration between the GIS and the decision support tools. Decision support tools include multicriteria evaluation, multiobjective linear programming and heuristic techniques, which support three basic stages of land use planning processes, namely land suitability evaluation, land use area optimization and land use spatial allocation. The application of OpenRules to the region of La Troncal, Ecuador, demonstrates its capability to generate alternative and coherent solutions through a scientific and justified procedure at low cost in terms of time and resources.     

Optimal Stopping Location of a High Speed Train using GIS and Multicriteria Decision‐making

This article develops a methodology using a Geographical Information System (GIS) to evaluate the best location to stop a high speed passenger train when faced with an undesired event. The proposed method is based on multicriteria decision‐making where different stretches of line which could be chosen as the stopping point are ranked depending on the characteristics of the line, the surrounding area and its accessibility for equipment. The method was integrated into the GIS to develop an expert support system for decision makers faced with different kinds of undesired events. It has been applied to a case study on the high speed line between Valladolid and Madrid (Spain). The proposed method is new and has not previously been applied to high speed railway networks and could be adapted to other case studies. The speed of the algorithm provides an almost instantaneous reply within seconds of an emergency situation occurring. The method can therefore be part of an overall support system for decision making in undesired rail events.     

Landslide Susceptibility Analysis of Shiv-Khola Watershed, Darjiling: A Remote Sensing & GIS Based Analytical Hierarchy Process (AHP)

In the present study, Remote Sensing Technique and GIS tools were used to prepare landslide susceptibility map of Shiv-khola watershed, one of the landslide prone part of Darjiling Himalaya, based on 9 landslide inducing parameters like lithology, slope gradient, slope aspect, slope curvature, drainage density, upslope contributing area, land use and land cover, road contributing area and settlement density applying Analytical Hierarchy Approach (AHA). In this approach, quantification of the factors was executed on priority basis by pair-wise comparison of the factors. Couple comparing matrix of the factors were being made with reasonable consistency for understanding relative dominance of the factors as well as for assigning weighted mean/prioritized factor rating value for each landslide triggering factors through arithmetic mean method using MATLAB Software. The factor maps/thematic data layers were generated with the help of SOI Topo-sheet, LIIS-III Satellite Image (IRS P6/Sensor-LISS-III, Path-107, Row-052, date-18/03/2010) by using Erdas Imagine 8.5, PCI Geomatica, Arc View and ARC GIS Software. Landslide frequency (%) for each class of all the thematic data layers was calculated to assign the class weight value/rank value. Then, weighted linear combination (WLC) model was implied to determine the landslide susceptibility coefficient value (LSCV or ??M??) integrating factors weight and assigned class weight on GIS platform. Greater the value of M, higher is the propensity of landslide susceptibility over the space. Then Shivkhola watershed was classified into seven landslide susceptibility zones and the result was verified by ground truth assessment of existing landslide location where the classification accuracy was 92.86 and overall Kappa statistics was 0.8919.     

A Microsoft Excel Application for Automatically Building Historical Geography GIS Maps

The ability to visualize location and time information on satellite‐generated maps using geographic information systems (GIS) such as Google Earth has enabled researchers with limited mapping expertise to use GIS for a wide range of applications. GIS holds special benefits for research in historical geography involving visualization of events and time‐based changes in geographical information. This article describes a Microsoft Excel VBA application which automatically converts information contained in a Microsoft Excel workbook into a.kml (Keyhole Markup Language) file suitable for display by mapping systems such as Google Earth. The application requires no knowledge of KML or Excel VBA. An example illustrates how the application can be used to trace the Mongol invasion of Eastern Europe.     

Weighted distances and distance transforms on the triangular tiling

Digital geometry is a field in the intersection of discrete mathematics and geometry having various applications including geographical information systems (GIS). In digital spaces, in grids, distances can be defined based on steps in paths in somewhat similarly as in graph theory. However, the grids have more definite structures, thus one may obtain more concrete results, for example, close formulae, than on arbitrary graphs. In this article, the weighted (also called chamfer) distances, and based on them, the distance transform are investigated on the regular triangular grid. Three types of neighborhood relations are used on the grid, and therefore, three weights are used to define a distance function. Natural conditions are used on the weights such as they are positive and a larger step (in the usual and also in the Euclidean sense) cannot have a smaller weight than a smaller one. Some properties of the weighted distances are discussed; for example, they are proven to be metrics. We also give algorithms and formulae that compute the weighted distance of any point pair on a triangular grid. Algorithm for weighted distance transform is provided based on wave-front propagation. Therefore, these new distance functions are ready for further applications in GIS, in image processing tasks, in computer vision, in graphics, in networking, and also in other applied fields.     

Learning in neural spatial interaction models: A statistical perspective

 In this paper we view learning as an unconstrained non-linear minimization problem in which the objective function is defined by the negative log-likelihood function and the search space by the parameter space of an origin constrained product unit neural spatial interaction model. We consider Alopex based global search, as opposed to local search based upon backpropagation of gradient descents, each in combination with the bootstrapping pairs approach to solve the maximum likelihood learning problem. Interregional telecommunication traffic flow data from Austria are used as test bed for comparing the performance of the two learning procedures. The study illustrates the superiority of Alopex based global search, measured in terms of Kullback and Leibler's information criterion. Received: December 2001 / Accepted: August 2002 The author gratefully thanks Martin Reismann (Department of Economic Geography & Geoinformatics) for his valuable research assistance.     

Using GIS and K = 3 Central Place Lattices for Efficient Solutions to the Location Set‐Covering Problem in a Bounded Plane

One of the simplest location models in terms of its constraint structure in location‐allocation modeling is the location set‐covering problem (LSCP). Although there have been a variety of geographic applications of the set‐covering problem (SCP), the use of the SCP as a facility location model is one of the most common. In the early applications of the LSCP, both potential facility sites as well as demand were represented by points discretely located in geographic space. The advent of geographic information systems (GIS), however, has made possible a greater range of object representations that can reduce representation error. The purpose of this article is to outline a methodology using GIS and K = 3 central place lattices to solve the LSCP when demand is continuously distributed over a bounded area and potential facility sites have not been defined a priori. Although, demand is assumed to exist over an area, it is shown how area coverage can be accomplished by the coverage of a point pattern. Potential facility site distributions based on spacings that are powers of one‐third the coverage distance are also shown to provide more efficient coverage than arbitrarily chosen spacings. Using GIS to make interactive adjustments to an incomplete coverage also provides an efficient alternative to smaller spacings between potential facility sites for reducing the number of facilities necessary for complete coverage.