Geographical Information Science Research Papers (original) (raw)

2025, Transactions in GIS

High‐performance computing (HPC) techniques are still considered an esoteric research branch of GI processing. They are complex to use, deterring both academic modellers and commercial software developers. Yet the use of many environmental models is constrained by computation times. Furthermore, as remote sensing, environmental modelling and GIS converge, so the need for parallel computing becomes more apparent. Several case studies, parallelising the processing of raster, grid and vector‐topology, demonstrate that scope exists for encapsulating the complexity of the parallelism in software frameworks, with strategies of spatial decomposition into sub‐areas maximising the re‐use of code from sequential algorithms. We show that parallel software frameworks can speed both the development and the execution of new applications. Based upon these case studies, the parallelisation of both interpolation and modelling in one software system is considered, with reference to pest infestation m...

2025, Future Internet

The rapid growth of Global Positioning System (GPS) and availability of real-time Geo-located data allow the mobile devices to provide information which leads towards the Location Based Services (LBS). The need for providing suggestions to personals about the activities of their interests, the LBS contributing more effectively to this purpose. Recommendation system (RS) is one of the most effective and efficient features that has been initiated by the LBS. Our proposed system is intended to design a recommendation system that will provide suggestions to the user and also find a suitable place for a group of users and it is according to their preferred type of places. In our work, we propose the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm for clustering the check-in spots of the user’s and user-based Collaborative Filtering (CF) to find similar users as we are considering constructing an interest profile for each user. We also introduced a grid-base...

2025, Visualization in Engineering

This paper explores the potential for using remotely sensed data from a combination of commercial and open-sources, to improve the functionality, accuracy of energy-use calculations and visualisation of carbon emissions. We present a study demonstrating the use of LiDAR (Light Detection And Ranging) data and aerial imagery for a mixed-use inner urban area within the North East of England and how this can improve the quality of input data for modelling standardised energy uses and carbon emissions. We explore the scope of possible input data for both (1) building geometry and (2) building physics models from these sources.We explain the significance of improved data accuracy for the assessment of heat-loss parameters, orientation, and shading and renewable energy micro-generation. We also highlight the limitations around the sole use of remotely sensed data and how these concerns can be partially addressed through combinations with (1) open-source property data, such as age, occupanc...

2025, International Journal of Geographical Information Science

In many African countries where both Government resources and donor aid for the control of tsetse-transmitted trypanosomiasis are declining, there is an increasing need to identify areas where intervention is most likely to be technically, economically, socially and environmentally sustainable. Activities then can be focused so that the maximum bene ts are obtained from limited resources. We describe a decision-support framework based on a geographical information system to identify areas of high priority for the control of tsetse and trypanosomiasis in the common y belt of eastern Zambia. Digital coverages were generated for six environmental variables: (1) cattle density, (2) human density, (3) land designation, (4) relative arable potential, (5) crop-use intensity and (6) proximity to existing control operations. The distribution of tsetse in the area was predicted using a multivariate (maximum likelihood) analysis of areas of known presence and absence and a series of environmental data. Experienced Zambian veterinarians and biologists working in the region established criteria weights for the input variables and the data were integrated in a geographical information system (GIS), using weighted linear combinations to prioritize areas for trypanosomiasis control. The results of this exercise and estimates of the errors involved are discussed.

2025

The curvature of the terrestrial surface enters into the category of primary parameters, directly derived, on the strenght of the altimetric values stored up in the grid type elevation structures. Geomorphological, it indicates the changing rate of the slope or of the orientation per unit lenght, in the XY plan. There are many types of curvatures, but in the more important morphometric analyses they are the following: profile curvature, plan curvature, tangential curvature, longitudinal curvature, transverse curvature, maximum curvature, minimum curvature, medial curvature, general curvature. This article aims at highlighting the differentiations that appear in the qualitative interpretation, in a geomorphologic sense, the results of the processing curvatures’ varieties in a series of GIS type programmes. At the same time, we had as our goal, the identification of the causes for these interpretative disparities, causes that are found in the mathematical apparatus used at the elabora...

2025, arXiv (Cornell University)

Treasure hunt is the task of finding an inert target by a mobile agent in an unknown environment. We consider treasure hunt in geometric terrains with obstacles. Both the terrain and the obstacles are modeled as polygons and both the agent and the treasure are modeled as points. The agent navigates in the terrain, avoiding obstacles, and finds the treasure when there is a segment of length at most 1 between them, unobstructed by the boundary of the terrain or by the obstacles. The cost of finding the treasure is the length of the trajectory of the agent. We investigate the amount of information that the agent needs a priori in order to find the treasure at cost O(L), where L is the length of a shortest path in the terrain from the initial position of the agent to the treasure, avoiding obstacles. Following the well-established paradigm of algorithms with advice, this information is given to the agent in advance as a binary string, by an oracle cooperating with the agent and knowing the whole environment: in our case, the terrain, the position of the treasure and the initial position of the agent. Advice complexity of treasure hunt is the minimum length of the advice string (up to multiplicative constants) that enables the agent to find the treasure at cost O(L). We first consider treasure hunt in regular terrains which are defined as convex polygons with convex c-fat obstacles, for some constant c > 1. A polygon is c-fat if the ratio of the radius of the smallest disc containing it to the radius of the largest disc contained in it is at most c. For the class of regular terrains, we establish the exact advice complexity of treasure hunt. We then show that advice complexity of treasure hunt for the class of arbitrary terrains (even for non-convex polygons without obstacles, and even for those with only horizontal or vertical sides) is exponentially larger than for regular terrains.

2025

Research overview and Potential Significance: My research explores novel computational techniques for enhancing situational awareness for disaster response, which is a national imperative . Beyond the unquantifiable costs of injury and loss of life from disasters, economic damages from Hurricane Sandy alone in the United States exceeded $60 billion . Disaster response during emergency management includes action taken immediately after a disastrous event with the aim of saving life, protecting property, and dealing with immediate disruption, damage, or other effects caused by the disaster (e.g., hurricanes, earthquakes, terrorist attacks, etc.) . The 2010 Haiti earthquake saw numerous requests for relief including requests for food, water, and medicine. Emergency managers are tasked with making resource allocation decisions based on the locations of the affected population. Figure shows the locations of a subset of various relief requests in Port-au-Prince, Haiti from January to March 2010. An important aspect of disaster response is to understand where people are in a given area (e.g., situational awareness). In other words it is important to be able to summarize people's location on a map and place them into different groups depending on their location. In order to make informed, critical resource allocation decisions given such location information, emergency managers need tools to assist them with situational awareness, which I conceptualize in my work as the spatial network activity summarization problem (SNAS).

2025, International Journal of Geographical Information Science

The Charleston Estuarine System Stock (CESS) of common bottlenose dolphins (Tursiops truncatus) has been the focus of population monitoring for the past 20 years. Photo-id studies have determined abundance and survival estimates for this population, which exhibits high site fidelity in this area. However, fine-scale distribution, utilization patterns, and the driving forces behind these patterns are lacking. Using historical photo-id data and a novel application of geographic information system (GIS) analysis, the present study identified core use areas within Charleston Harbor, as well as patterns specific to sexes and seasons. Photo-id data of 319 dolphins sighted 11 times or more during 2004-2009 were analyzed. Heat maps were developed to examine spatial distributions using kernel density estimates (KDE) and were compared between sexes and seasons. Multiple high-density core use areas were identified for this population, with the most noteworthy near the mouth of the harbor toward the Atlantic Ocean. Fine-scale distribution varied across sexes, as well as seasons. Some areas were identified as more specifically inhabited by one sex, while other areas overlapped between sexes. Females were more tightly concentrated within their distribution while males were more dispersed. Although population distribution varied across seasons, sex distributions remained.

2025, International Journal of Fundamental & Applied Research

The utilization of biofertilizers in sustainable agriculture is essential for reducing chemical dependency and enhancing soil health. This paper explores the current challenges and proposes practical solutions related to the Cyanobacterial biofertilizer ecosystem in Gorakhpur, India. Drawing from field observations, stakeholder interviews, and research studies, it identifies core problems including limited farmer awareness, infrastructural bottlenecks, lack of quality control, ineffective government policy implementation, and logistical issues in biofertilizer production and distribution. The paper emphasizes the need for a holistic, multi-stakeholder approach to improve adoption rates and efficiency. It proposes an integrated action framework that includes strengthening farmer training programs, upgrading production infrastructure, ensuring quality assurance mechanisms, and facilitating robust public-private partnerships. The paper concludes with actionable recommendations aimed at making biofertilizers a mainstream alternative for sustainable agriculture in the region.

2025, International Journal of Fundamental & Applied Research

2025, International Journal of Geographical Information Science

Although it is acknowledged that urban inequalities can lead to biases in the production of social media data, there is a lack of studies which make an assessment of the effects of intra-urban movements in real-world urban analytics applications, based on social media. This study investigates the spatial heterogeneity of social media with regard to the regular intra-urban movements of residents by means of a case study of rainfall-related Twitter activity in São Paulo, Brazil. We apply a spatial autoregressive model that uses population and income as covariates and intra-urban mobility flows as spatial weights to explain the spatial distribution of the social response to rainfall events in Twitter vis-à-vis rainfall radar data. Results show high spatial heterogeneity in the response of social media to rainfall events, which is linked to intra-urban inequalities. Our model performance (R 2 ¼ 0:80) provides evidence that urban mobility flows and socio-economic indicators are significant factors to explain the spatial heterogeneity of thematic spatiotemporal patterns extracted from social media. Therefore, urban analytics research and practice should consider not only the influence of socio-economic profile of neighborhoods but also the spatial interaction introduced by intra-urban mobility flows to account for spatial heterogeneity when using social media data.

2025, International Journal of Geographical Information Science

The spatial analysis of social media data has recently emerged as a significant source of knowledge for urban studies. Most of these analyses are based on an areal unit that is chosen without the support of clear criteria to ensure representativeness with regard to an observed phenomenon. Nonetheless, the results and conclusions that can be drawn from a social media analysis to a great extent depend on the areal unit chosen, since they are faced with the wellknown Modifiable Areal Unit Problem. To address this problem, this article adopts a data-driven approach to determine the most suitable areal unit for the analysis of social media data. Our multicriteria optimization framework relies on the Pareto optimality to assess candidate areal units based on a set of user-defined criteria. We examine a case study that is used to investigate rainfall-related tweets and to determine the areal units that optimize spatial autocorrelation patterns through the combined use of indicators of global spatial autocorrelation and the variance of local spatial autocorrelation. The results show that the optimal areal units (30 km 2 and 50 km 2 ) provide more consistent spatial patterns than the other areal units and are thus likely to produce more reliable analytical results.

2025, Journal of Design + Built

Urban planning is a complex process as urban system is the resultant of interactions between its subsystems. Knowing future projection of physical urban development can play a vital role in successful urban planning and development. Therefore, it is important to have a good understanding of the interactions between urban system components to correctly predict future urban growth. This paper proposes the Celullar Automata (CA) model to predict the future of urban development. Due to shortcomings of traditional modeling methods which are generally static, linear and are based on simple systems theory, it is expected that the proposed CA model which is dynamic and nonlinear will provide better understanding of the urban system and provide better prediction of urban growth.

2025, GIS Business

Pradhan Mantri Mudra Yojana is one of the government initiatives under financial inclusion to incorporate the section of the society which still remain untouched or underprivileged. The motive of the scheme is to facilitate funding to unfunded. This is just to cover their credit requisite in due course of time under the aegis of monetary policy and assist small entrepreneurs up to Rs 10 lakh. Government of India has envisaged the idea of funding the micro units which were out of the league by rejuvenating and uplifting the deprived from the critical conditions of financial crisis. This Yojna was declared during the union budget of financial year of 2015-16. This research paper inculcates an overview of PMMY along with state wise performance analysis of financial inclusion till date.

2025, International Journal of Geographical Information Science

Models designed to capture spatially varying processes are now employed extensively in the social and environmental sciences. The main strength of such models is their ability to represent relationships that vary across locations through locally varying parameter estimates. However, local models of spatial processes also provide information on the nature of these spatially varying relationships through the estimation of a 'bandwidth' parameter. This paper examines bandwidth at a conceptual, operational, and empirical level within the framework of geographically weighted regression, one of the more frequently employed local spatial models. We outline how bandwidth relates to three characteristics of spatial processes: variation; dependence; and strength.

2025, Dagstuhl seminar

1 University of Southampton, UK y.kalfoglou@ecs.soton.ac.uk 2 Consejo Superior de Investigaciones Cientıficas, Spain marco@iiia.csic.es 3 The Boeing Company, USA michael.f.uschold@boeing .com 4 University of Georgia, USA amit@cs.uga.edu 5 Universität Koblenz-Landau, Germany staab@uni-koblenz.de ... Semantic interoperability and integration is concerned with the use of explicit semantic descriptions to facilitate information and systems integration. Due to the widespread importance of integration, many disparate communities have tackled this ...

2025

Developed countries have invested considerable efforts in promoting sustainable transportation modes, identifying bicycle use as a more environmentally friendly alternative. Nevertheless, this transition necessitates a deeper understanding of bicycle user behaviour to facilitate the process. This study investigates bike users' route selection behaviour based on real-world data. Data collected over six months from Bologna, Italy, were analysed to understand the flow and choices of bike users in a medium-small historical city. We employed a tessellation algorithm combined with Open Street Map street tags to examine bike users' preferences regarding urban trajectories. The dataset comprises of 290,117 unique trips consisting of 60,414,481 Global Positioning System (GPS) points. The results indicate that bicycles are predominantly used for short-to medium-distance trips. Specifically, in suburban regions, bike users tend to use larger roads leading to the city centre, whereas, in the city centre, they prefer routes that bypass the narrow streets of the historic area. These findings offer insights into route choice factors and can guide improvements to cycling infrastructure for a safer, more efficient urban environment.

2025, International Journal of Geographical Information Science

Nowadays, a huge quantity of information is stored in digital format. A great portion of this information is constituted by textual and unstructured documents, where geographical references are usually given by means of place names. A common problem with textual information retrieval is represented by polysemous words, that is, words can have more than one sense. This problem is present also in the geographical domain: place names may refer to different locations in the world. In this paper we investigate the use of our word sense disambiguation technique in the geographical domain, with the aim of resolving ambiguous place names. Our technique is based on WordNet conceptual density. Due to the lack of a reference corpus tagged with WordNet senses, we carried out the experiments over a set of 1,210 place names extracted from the SemCor corpus that we named GeoSemCor and made publicly available. We compared our method with the most-frequent baseline and the enhanced-Lesk method, which previously has not been tested in large contexts. The results show that a better precision can be achieved by using a small context (phrase level), whereas a greater coverage can be obtained by using large contexts (document level). The proposed method should be tested with other corpora, due to the fact that our experiments evidenced the excessive bias towards the most-frequent sense of the GeoSemCor.

2025, International Journal of Economics, Management and Accounting

The application of m-commerce activities among smartphone users in Malaysia has become one of the major challenges for companies involved in m-commerce. The present study aims at identifying the factors influencing m-commerce use in Malaysia. An extended Technology Acceptance Model (TAM) is employed. A total of 350 questionnaires were distributed among smartphone users in the Klang Valley area of Malaysia. Two-stage Structural Equation Modelling (SEM) was employed to test the model of the study. The findings of the study reveal that behavioral intention has a significant positive influence on m-commerce use. The findings further reveal that perceived usefulness, perceived enjoyment, and privacy and security have significant positive influence on behavioral intention. These findings will benefit stakeholders involved in m-commerce activities such as providers, retailers, brands, and consumers. In addition, academicians and students can also benefit from this study in the context of m...

2025

The complex development of geomorphometric theory has led to various concepts of land surface curvature (LSC), whose compatibility has not yet been systematically investigated. The definition, terminology and interpretation of LSCs show significant confusion and gaps reflected in various applications in geoscience modelling and prediction. Here we discuss the present situation, specify basic problems, and make initial suggestions for their solution.

2025, Proceedings of UK e-Science All Hands conference. EPSRC

The GENSS project has developed a flexible generic brokerage framework based on the use of plug-in components that are themselves web services. The focus in GENSS has been on mathematical web services, but the broker itself is domain independent and it is the plug-ins that act as sources of domain-specific knowledge. A range of plug-ins has been developed that offer a variety of matching technologies including ontological reasoning, mathematical reasoning, reputation modelling, and textual analysis. The ranking ...

2025, International Journal of Geographical Information Science

The book 'Open source GIS: a GRASS GIS approach 3rd ed.' by Markus Neteler and Helena Mitasova is a primer on GIS concepts, Open Source GIS (OS GIS) software and the popular GRASS GIS package. This third edition, published in 2008, features various new sections and most chapters have been revised or completely rewritten to reflect the changes in GRASS version 6.3 (July 2007), as well as the latest trends and developments in OS GIS and web mapping. All examples have been enhanced and updated for a new, modern North Carolina (NC) dataset that is available from the book's website. The book starts with an introduction to GIS concepts, effectively and succinctly covering the GIS and basic mapping knowledge required to follow the rest of the book, then quickly moves on to introducing the reader to GRASS. The way the information is structured and explained in these first chapters, and which continues throughout the book, hints to the expertise of the authors and the quality of the editing. All chapters focus on a particular topic and are further structured with several levels of subheadings, making the book very useful as a primer or reference. Most concepts and techniques explained in the text contain examples, practical applications, code listings or references for further reading. The sample code is well formatted and not too fragmented by explanations, benefiting the experienced reader just looking for code, but also concise and sufficiently commented to be suitable to nonexpert readers. Although no previous GIS knowledge is required to replicate the examples, basic Information Systems or programming skills or, at the least, advanced computer knowledge are strongly recommended as the samples make frequent use of the Linux command line interface (CLI) and data query languages such as SQL. The large amount of code listings might initially intimidate someone with little or no CLI experience but this should not be a deterrent. The authors make no assumptions about previous exposure to GRASS, and thus guide the reader through easy to follow step-by-step instructions. The steps are very detailed and include screenshots where necessary. The examples throughout the book use the same NC sample dataset. The dataset's files are available in their original formats, therefore representing a realistic real-world scenario, where data of greatly differing sources, formats and projections have to be converted and re-projected before being ready for use. The GRASS data model and data exchange chapter provides detailed instructions and examples for dealing with most common forms of GIS Raster and Vector data, for example, remote sensing imagery, scanned maps, GPS traces, CAD files, ASCII, WFS, PostGIS and many more. Although this edition was published a long time ago in software years, it is still up to date, due to the inclusion of formats such as SVG and KML that have only really gained importance with the success and surge in popularity of web mapping and Google Maps/Earth-based applications and mashups in more recent years. The main parts of the book are the two chapters on working with raster and vector data. These chapters are very hands-on with code listings taking up approximately half of the pages. The examples vary greatly across many disciplines, datasets and real-world GIS modelling scenarios and problems, from simple data queries and thematic mapping, over raster map algebra and statistical analysis using R, to complex landscape process modelling

2025, GIS Business

This study investigates the effect of organisational culture dimensions on employee performance in Nigerian fast food restaurants using cross-sectional survey. Forty fast food restaurants were selected using simple random sampling. Nine hundred and twenty five employees were surveyed. Sample size of two hundred and seventy two was ascertained with Krejcie and Morgan. Method for data collection is questionnaire. Two hundred and thirty nine copies of questionnaire were retrieved out of two hundred and seventy two copies administered. Simple linear regression was used to analyse the hypotheses with the aid of IBM SPSS 20.0. This study found that organisational culture dimensions predicted with clan culture and market culture has a positive significant effect on employee performance. It concludes that organisational culture dimensions measured in terms of clan culture and market culture engenders employee performance through effectiveness and efficiency. One of the practical implication...

2025, International Journal of Geographical Information Science

Optimal zoning of protected natural areas is important for conserving ecosystems. It is an NP-hard problem which is difficult to solve by using common geographic information system (GIS) functions. Another problem is that existing optimization methods ignore potential land-use dynamics in formulating optimal patterns. This article has developed a new method for solving complicated zoning problems by using ant colony optimization (ACO) techniques. Significant modifications have been made, so that traditional ACO can be extended to the solution of area optimization problems. Two strategies, the singleyear coupling strategy and the merging-year coupling strategy, have been proposed to couple urban cellular automata with ACO for zoning protected natural areas under a changing landscape. This proposed method has been tested in the metropolitan region of Guangzhou, China, by using Geographical Simulation and Optimization System (GeoSOS) software. The experiments indicate that the modified ACO can effectively solve this optimization problem without getting stuck in local optima. This method has better performances compared to other traditional methods, such as simulated annealing (SA), iterative relaxation (IR), and density slicing (DS). The use of the best coupling strategy can improve the accumulative utility value of the zoning by 4.3%. Moreover, it is also found that the adoption of the best protection pattern could significantly promote the compactness of future urban forms in the study area.

2025, International Journal of Digital Earth

2025, International Journal of Geographical Information Science

XML/GML/SVG-based approaches are promising for building Web-based geographic information systems (WebGIS). However, current XML/GML/SVG-based WebGISs are lacking in spatial analysis. Some of them are designed for web mapping only. Others adopt a server-side solution for spatial analysis, which suffers from the 'bottleneck' problem and results in a high network transmission load. Load-balancing spatial analysis between server side and browser side can be used to solve the above problems. This article focuses on one of the key building blocks of load-balancing spatial analysis, that is, SVG-based spatial analysis which enables spatial querying and analysis directly on SVG (on the browser side). After analyzing the workflow of spatial analysis, we identify and focus on two key issues in providing spatial analysis on SVG: SVG-based spatial information representation and SVG-based spatial extended structured query language (SSESQL). For the first issue, a theoretical foundation is set up to develop an SVG-based spatial information representation model. Some spatial operators are designed and integrated into an SSESQL to support spatial querying on SVG. Finally, we design and implement two case studies. The results of these case studies show that the proposed method is feasible and operable in supporting spatial analysis directly on SVG on the browser side. The proposed method can be easily incorporated with some existing methods (e.g., GML-based spatial analysis on the server side) to provide load-balancing spatial analysis (load balancing between server side and browser side) in XML/GML/ SVG-based WebGIS. As a result, users can access high-performance spatial analysis simply via a web browser (such as Internet Explorer and Firefox).

2025, International Journal of Geographical Information Science

With large amounts of digital map archives becoming available, automatically extracting information from scanned historical maps is needed for many domains that require long-term historical geographic data. Convolutional Neural Networks (CNN) are powerful techniques that can be used for extracting locations of geographic features from scanned maps if sufficient representative training data are available. Existing spatial data can provide the approximate locations of corresponding geographic features in historical maps and thus be useful to annotate training data automatically. However, the feature representations, publication date, production scales, and spatial reference systems of contemporary vector data are typically very different from those of historical maps. Hence, such auxiliary data cannot be directly used for annotation of the precise locations of the features of interest in the scanned historical maps. This research introduces an automatic vector-to-raster alignment algorithm based on reinforcement learning to annotate precise locations of geographic features on scanned maps. This paper models the alignment problem using the reinforcement learning framework, which enables informed, efficient searches for matching features without pre-processing steps, such as extracting specific feature signatures (e.g. road intersections). The experimental results show that our algorithm can be applied to various features (roads, water lines, and railroads) and achieve high accuracy.

2025, International Journal of Geographical Information Science

The problem of identifying the shortest path along a road network is a fundamental problem in network analysis, ranging from route guidance in a navigation system to solving spatial allocation problems. Since this type of problem is solved so frequently, it is important to craft an approach that is as efficient as possible. Based upon past research it is generally accepted that several efficient implementations of the Dijkstra algorithm are the fastest at optimally solving the 'one-to-one' shortest path problem . We show that the most efficient, state-of-the-art implementations of Dijkstra can be improved by taking advantage of network properties associated with GIS-sourced data. The results of this paper, derived from tests of different algorithmic approaches on real road networks, will be extremely valuable for application developers and researchers in the GIS community.

2025

Many solution techniques for discrete location-allocation problems make use of a sorted distance strings data structure in order to speed processing time. Such data structures are commonly used, for example, within interchange heuristics and lagrangian relaxation codes. The primary drawback to distance strings is that in a standard computer architecture they require approximately 50% additional memory storage in comparison to a standard distance matrix. This is due to the fact that distance strings must store not only distances, but also the order of the nodes sorted by increasing distance. To reduce the additional memory requirements of distance strings, researchers such as Hillsman [1980] and Densham and Rushton [1992a] have proposed a strategy for cutting the distance strings to include only sets of relatively close neighbor nodes. This has become an important implementation issue for solving relatively large locationallocation problems. In fact, the new Location-Allocation module of the ARC/Info GIS system uses a distance string structure and a string cutoff option to save storage and processing time. The danger in employing only partial distance strings is that if too few distance entries are stored in the distance strings, heuristic or algorithmic performance may be compromised in that the quality of the solutions generated may be less than desirable. This paper tests the effects on solution quality of imposing different distance string definitions and sizes. The goal is to establish guidelines concerning the degree to which the distance strings data structure may be reduced for memory savings without adversely affecting solution quality. The paper proposes and compares two alternative methods to that of Hillsman and of Densham and Rushton for the selection of nodes to be included within the distance strings data structure. We show that the two new alternative methods for defining distance strings appear to outperform the earlier approach. The results of this paper can be used to aid users in determining the extent that distance string cutoffs should be employed in application as well as aid in the development of location modeling software.

2025

2025, International Journal of Geographical Information Science

Spatially coincident land cover information frequently varies due to technological and political variations. This is especially problematic for time-series analyses. We present an approach using expert expressions of how the semantics of different datasets relate to integrating temporal time series land cover information where the classification classes have fundamentally changed. We use LCMGB and LCM2000 as example data sets because of the extensive object based meta-data in the LCM2000. Inconsistencies between the two datasets can arise from random, gross and systematic error and from an actual change in land cover. Locales of possible land cover change are inferred by comparing characterisations derived from the semantic relations and meta-data. Field visits showed errors of omission to be 21% and errors of commission to be 28%, despite the accuracy limitations of the land cover information when compared to the field survey component of the Countryside Survey 2000. 1.

2025, International Journal of Geographical Information Science

Understanding human dynamics after a major disaster is important to the region's sustainable development. This study utilized land cover data to examine how Hurricane Katrina has affected the urban growth pattern in the Mississippi Delta in Louisiana. The study analyzed land cover changes from non-urban to urban in three metropolitan areas, Baton Rouge, New Orleans-Metairie, and Hammond, for two time periods, pre- Katrina (2001-2006) and post-Katrina (2006-2010). The study first applied a focal filter to extract continuous urban areas from the scattered urban pixels in the original remote sensing images. Statistical analyses were applied to develop initial functions between urban growth probability and several driving factors. A genetic algorithm was then used to calibrate the transition function, and cellular automata simulation based on the transition function was conducted to evaluate future urban growth patterns with and without the impact of Hurricane Katrina. The results show that elevation has become a much more important factor after Hurricane Katrina, and urban growth has shifted to higher elevation regions. The elevation most probable for new urban growth increased from 10.84 to 11.90 meters. Moreover, simulated future urban growth in this region indicates a decentralized trend, with more growth occurring in more distant regions with higher elevation. In the New Orleans metropolitan area, urban growth will continue to spill across Lake Pontchartrain to the satellite towns that are more than 50 minutes away by driving from the city center.

2025, GIS Business

The development of a modern competitive environment and those of information technology through globalization has encouraged companies to focus more on the context of Service quality. These service qualitiesshould be especially oriented toward customer satisfaction and that of the aspects associated with those of customer loyalty, its effect on increasing the revenue. In the era of customers,they are in search of the companies who provide good service, this is one of the most important strategies for their organizational success and satisfies the urge of survival in today's competitive environment. The methodology of critical value analysis is put into use for the setting of the customer service according to their priorities. Furthermore, an approach is being undertaken to evaluate the importance of the customers is also adopted. This research paper ends with an appropriate conclusion that discusses the relevant findings of the survey and proposes a way to conduct more research ...

2025, International Journal of Geographical Information Science

Voronoi tessellation, and its dual the Delaunay triangulation, provide a cohesive framework for the study and interpretation of phenomena of geographical space in two and three dimensions. The planar and spherical solutions introduce errors in the positional accuracy of both Voronoi vertices and Voronoi edges due to errors in distance computations and the path connecting two locations with planar lines or great circle arcs instead of geodesics. For most geospatial applications the introduction of the above errors is insignificant or tolerable. However, for applications where the accuracy is of utmost importance, the ellipsoidal model of the Earth must be used. Characteristically, the introduction of any positional error in the delimitation of maritime zones and boundaries results in increased maritime space for one state at the expense of another. This is a situation that may, among others, have a serious impact on the financial activities and the relations of the states concerned. In the context of previous work on maritime delimitation we show that the Voronoi diagram constitutes the ideal solution for the development of an automated methodology addressing the problem in its entirety. Due to lack of a vector methodology for the generation of Voronoi diagram on the ellipsoid, the aforementioned solution was constrained by the accuracy of existing approaches. In order to fill this gap, in this paper we deal with the inherent attributes of the ellipsoidal model of the Earth, e.g. the fact that geodesics are open lines, and we elaborate on a methodology for the generation of the Voronoi diagram on the ellipsoid for a set of points in vector format. The resulting Voronoi diagram consists of vertices with positional accuracy that is only bounded by the user needs and edges that are comprised of geodesics densified with vertices equidistant to their generators. Finally, we present the implementation of the proposed algorithm in the Python programming language and the results of two case studies, one on the formation of closest service areas and one on maritime boundaries delimitation, with the positional accuracy set to 1 cm.

2025, International Journal of Geographical Information Science

The geographical distribution of a species is limited by factors such as climate, resources, disturbances and species interactions. Environmental niche models attempt to encapsulate these limits and represent them spatially but do not always incorporate disturbance factors. We constructed MaxEnt models derived from a remotely sensed vegetation classification with, and without, an agricultural modification variable. Including agricultural modification improved model performance and led to more sites with native vegetation and fewer sites with exotic or degraded native vegetation being predicted suitable for A. parapulchella. Analysis of a relatively well-surveyed sub-area indicated that including agricultural modification led to slightly higher omission rates but markedly fewer likely false positives. Expert assessment of the model based on mapped habitat also suggested that including agricultural modification improved predictions. We estimate that agricultural modification has led to the destruction or decline of approximately 30-35% of the most suitable habitat in the sub-area studied and approximately 20-25% of suitable habitat across the entire study area, located in the Australian Capital Territory, Australia. Environmental niche models for a range of species, particularly habitat specialists, are likely to benefit from incorporating agricultural modification. Our findings are therefore relevant to threatened species planning and management, particularly at finer spatial scales.

2025

Fields associated with design and physical planning are appropriate domains for the use of multicriteria decision methods. Various methods are compared and "weighted summation" technique is put forward as the most suitable method for the needs of design and planning. The case of city planning is used to illustrate the methodology. The phases of "design of alternatives", "determination of objectives and criteria" and "evaluation" are described with the help of examples. The paper concludes with principles and problems in the use of multicriteria decision methods in design and planning.

2025

Over the last decades, the use of the Space-Time Cube (STC) has seen an increase. The STC is considered as one of the most suitable representations for the visual analysis of movement data since it allows a view from spatial and temporal perspectives simultaneously. However, at the same time, an increase in size and complexity of the movement data can be witnessed. Is the STC still suitable under such circumstances, and what role does the cartographic design play? STC usability studies done before do not take into account the aspects of cartographic design. Therefore, this paper reports on the outcomes of an empirical evaluation of the use of visual variables (color hue, saturation, value, size and orientation) and depth cues (shading, transparency) as well as their perceptual properties to define their effectiveness and efficiency in depicting the STC content.

2025, International Journal of Geographical Information Science

This paper reports the results of an empirical usability experiment on the performance of the space-time cube in a GeoVisual analytics environment. It was developed to explore movement data based on the requirements of human geographers. The interactive environment consists of multiple coordinated views incorporating three graphical representations. For the experiment, two groups of the user, domain experts and non-domain experts, had to execute several map-use tasks to answers specific question. The data collected during the experiment were analysis resulting in a set of usability metrics related to the effectiveness, efficiency and user satisfaction of developed application. The comparison of both groups showed that domain experts were able to operate the visual analytical environment more effectively and efficiently due to their interest to explore their data. The user feedback derived from the analysis of both experiments was further processed for the improvement of the application.

2024

Wireless sensor networks consist of many wireless sensor nodes that enable the collection of sensor data from the physical world. A key requirement to interpreting the data is to determine the locations of the sensor nodes. The localization techniques developed can be divided into two categories: range-free and range-based. Range-free localization usually assumes isotropic networks where the hop count between two nodes is proportional to their distance. However, anisotropic networks are more realistic due to the presence of various anisotropic factors in practice, e.g. irregular radio propagation, low sensor density, anisotropic terrain condition, and obstacles which can detour the shortest path between two nodes. The previous anisotropy-tolerating solutions focused on only one anisotropic factor -the obstacles. We will propose a pattern-driven localization scheme to tolerate multiple anisotropic factors. Range-based localization assumes that the inter-node distances can be accurately measured by special ranging hardware. There are two important issues: (1) the ranging noise which affects the localization accuracy; (2) the collinearity of critical node sets which may produce unanticipated flip ambiguities and harm the localization robustness. However, the previous research does not fully address these two issues, i especially for patch merging, a powerful tool to localize sparse sensor networks. We will present our inflexible body merging algorithm to address these two issues for both patch merging and multilateration. Our algorithm can also improve the percentage of localizable nodes by nearly two times in sparse networks as compared with stateof-the-art work. Another critical issue for range-based localization is the existence of outliers in raw data (i.e. distance measurements and anchor positions) which strongly deviate from their true values. These outliers can severely degrade localization accuracy and need to be rejected. Previous studies have two inadequacies of (1) focusing on adding an outlier rejection ability to multilateration but neglecting patch merging; (2) rejecting only the outlier distances but neglecting outlier anchors which are more difficult to remove, because outlier anchors may collude by declaring positions in the same coordinate frame. We will present an algorithm to reject both outlier distances and colluding outlier anchors, in both dense networks and sparse networks. This work would not have been possible without the support of my colleagues, friends, and mentors. Specifically, I would like to thank my supervisor, Bin Xiao, who has given me all the support and guidance I needed as a doctoral student. He is not only a good researcher with broad knowledge but also a nice friend and kind person. I am very grateful to have had his trust in my ability, and I have often benefitted from his insight and advice. I am also thankful to Jiannong Cao, my co-supervisor, for his many suggestions and constant support during this research. He has sharp intuition, and grand insight about research, and taught me a lot about how to be a good researcher. This thesis was also made possible by collaboration and consultation with many colleagues. I would like to thank

2024, International Journal of Geographical Information Science

The international standard CityGML defines five levels of detail (LODs) for 3D city models, but only the highest of these (LOD4) supports modelling the indoor geometry of a building, which must be acquired in correspondingly high detail and therefore at a high cost. Whereas simple 3D city models of the exterior of buildings (e.g. CityGML LOD2) can be generated largely automatically, and are thus now widely available and have a great variety of applications, similarly simple models containing their indoor geometries are rare. In this paper we present two contributions: (i) the definition of a level of detail LOD2+, which extends the CityGML LOD2 specification with indoor building geometries of comparable complexity to their exterior geometries in LOD2; and more importantly (ii) a method for automatically generating such indoor geometries based on existing CityGML LOD2 exterior geometries. We validate our method by generating LOD2+ models for a subset of the Rotterdam 3D data set and visually comparing these models to their real counterparts in building blueprints and imagery from Google Street View and Bing Maps. Furthermore, we use the LOD2+ models to compute the net internal area of each dwelling and validate our results by comparing these values to the ones registered in official government data sets.

2024, International Journal of Geographical Information Science

Small-scale spatial events are situations in which elements or objects vary in such a way that temporal dynamics is intrinsic to their representation and explanation. Some of the clearest examples involve local movement from conventional traffic modeling to disaster evacuation where congestion, crowding, panic, and related safety issue are key features of such events. We propose that such events can be simulated using new variants of pedestrian model, which embody ideas about how behavior emerges from the accumulated interactions between small-scale objects. We present a model in which the event space is first explored by agents using 'swarm intelligence'. Armed with information about the space, agents then move in an unobstructed fashion to the event. Congestion and problems over safety are then resolved through introducing controls in an iterative fashion and rerunning the model until a 'safe solution' is reached. The model has been developed to simulate the effect of changing the route of the Notting Hill Carnival, an annual event held in west central London over 2 days in August each year. One of the key issues in using such simulation is how the process of modeling interacts with those who manage and control the event. As such, this changes the nature of the modeling problem from one where control and optimization is external to the model to one where this is intrinsic to the simulation.

2024, International Journal of Geographical Information Science