Traditional Geographic Information System Research Articles

Supporting Fire Response: Advanced Spatial Data Analytics for Hydrant Access Assessment

ABSTRACTCalifornia faces increasing wildfire frequency and severity, necessitating effective firefighting strategies along with well‐located infrastructure. Hydrants are vital for urban safety and must comply with established standards to adequately protect people and property. One such standard involves hydrant spacing, critical for ensuring effective emergency response in the event of a fire. Traditional geographic information systems techniques are not well suited to fully assess hydrant networks, especially in the context of spacing given complex road network geographies. This paper introduces an innovative approach to assess hydrant spacing. The developed technique is applied in the evaluation of infrastructure in Santa Barbara, California. The results reveal significant code violations along streets throughout the region, suggesting clustered pockets of vulnerability and risk. Potential strategies emerge from this analysis to enhance firefighting preparedness, offering guidance to local agencies regarding hydrant system limitations across this fire‐prone region.

Geo-Phenomenology: A Qualitative and Humanistic GIS Approach to Exploring Lived Experience

Critical discussions are developing to combine geographic information systems (GIS) and qualitative methods as an alternative approach to traditional quantitative GIS, but the possibility of integrating spatial information technology and phenomenology is still unknown. This study explores a new qualitative and humanistic GIS approach called geo-phenomenology. It attempts to improve the ability to validate and authenticate findings and to gain a holistic understanding of the complex interplay among space, place, and human emotion through a combination of phenomenology, natural language processing methods, and GIS. To illustrate this approach, this study focuses on international students and examines the effects of geographic mobility on individuals’ sense of attachment and belonging. Importantly, it allows for a more sensitive approach to the spatial scale of material culture as a mediator of sense of place. The overlay of emotional mapping and land use provided a perspective for narrative interpretation and hypothesis building, ultimately leading to the discovery of key evidence determining the main themes of international students’ sense of place attachment and belonging. By combining quantitative emotion detection with qualitative phenomenological interpretation in GIS, this study concludes that geo-phenomenology can help us consider the rich nuances of lifeworlds from multiple perspectives.

Decentralizing spatial data: the convergence of Geographic Information Systems and Web 3.0 technologies


 
 
 Geographic Information Systems (GIS) have long served as pivotal tools for map- ping and understanding spatial relationships. However, the dawn of Web 3.0 technologies has catalyzed a transformative shift in the geospatial domain. This research meticulously investigates this transformation, focusing on the integration of decentralized spatial data storage, blockchain, Artificial Intelligence (AI), and Machine Learning (ML) with traditional GIS frameworks. Decentralized systems, un- derpinned by the principles of Web 3.0, present a promising alternative to centralized data storage, addressing challenges related to scalability, data sovereignty, and system vulnerabilities. Blockchain technology, traditionally associated with financial transactions, emerges as a cornerstone in this new GIS paradigm, ensuring unparalleled data integrity, transparency, and security. Its decentralized ledger system, combined with consensus mechanisms, offers a robust and transparent framework for managing diverse spatial data- sets, ranging from land registries to intricate environmental monitoring systems. The incorporation of AI and ML technologies further augments the capabilities of GIS. Beyond mere visualization, GIS, when powered by AI and ML, can process vast datasets, discern complex patterns, and even predict future spatial trends with remarkable accuracy. This research emphasizes the role of real-time and dynamic queries, highlighting the transition from static GIS analyses to more adaptive and predictive geospatial evaluations. While the potential advantages of this technological convergence are substantial, the research also sheds light on inherent challenges, espe- cially those related to the management of high-volume real-time data and ensuring data consistency across diverse sources. Building upon foundational works in the field, this study offers a holistic and comprehensive perspective on the synergistic potential of Web 3.0 technologies, AI, ML, and blockchain within GIS. It not only extends the findings of prior research but also paves the way for future explorations, setting the stage for innovative advancements in geospatial analysis.
 
 

Integrative Geospatial Analysis: Unveiling Insights through GIS Modeling and Statistical Evaluation of SPT‐N and Soil Types Data of New Kabul City, Afghanistan

The precise evaluation of subsurface soil information is paramount for effective infrastructure design and planning. Geotechnical soil maps (GSMs) play a pivotal role in estimating subsurface properties. As Kabul City, Afghanistan’s largest metropolitan area, undergoes rapid expansion and the demand for safer infrastructure rises, the necessity for precise geotechnical information becomes increasingly urgent. Nevertheless, there is a lack of comprehensive studies on urban geotechnical zoning maps in Afghanistan. Therefore, to this end, this study utilizes inverse distance weighting (IDW) interpolation approaches for the construction and characterization of GSMs using a traditional geographic information system (GIS). Data about soil types and standard penetration (N‐value) up to 30 m depth were extracted from 130 locations in New Kabul City, Afghanistan. GSMs incorporating N‐value and soil types were constructed utilizing the IDW technique within the ArcGIS platform. The outcomes reveal that the subjected region was dominated by cohesive soil with N‐values varying from 7 to 45 in three different sections. The findings exhibit strong empirical correlations between N‐values and depth, with an R2 value of 0.95 and an RMSD value of 0.71. Moreover, the correlation coefficient to predict soil type classification is 97%, and it stands at 95% for N‐value prediction. These results facilitate the rapid evaluation of subsoil strength and stiffness, offering valuable insights for project planners and feasibility researchers.

Computational approaches towards the understanding of past boundaries: A case study based on archaeological and historical data in a hilly region in Germany

Abstract Boundaries at different scales or in different cultural contexts vary in permeability, fuzziness, and continuity. The contribution of methods from the Geographical Information Systems (GIS) toolbox used in archaeology for the understanding of boundaries is explored in a case study based on known boundaries that are located in a hilly region east of Cologne, Germany. The known political and religious boundaries date back to the 16th and early 17th century. Furthermore, a linguistic boundary traversing the study area is well-known. A classification of the reliability of the political boundaries is presented based on evidence from different sources including archaeological sites. A traditional GIS method for delimiting territories is Voronoi polygon generation, also known as Thiessen polygons. A variant uses least-cost distances, accounting for costs of movement. A site catchment of a settlement consists of all locations that can be reached by expending a given cost limit. Both the initial Voronoi computations as well as the site catchments failed to reconstruct a significant proportion of the known past boundaries. Therefore, the association of the known boundaries with rivers, ridges, and modern parish boundaries was tested and found significant. In contrast, poor soils and voids identified by least-cost Kernel Density Estimation (LC-KDE) of 16th century settlement locations are no preferred locations of past boundaries. Boundaries of Voronoi polygons based on modified cost models taking the association of past boundaries with ridges, rivers, and modern boundaries into account reconstructed about 27 % of the confirmed past political boundaries successfully. The association of the linguistic boundary with the features mentioned above is insignificant. Diagnostic place names are the traits forming the basis of Voronoi diagrams and LC-KDE applied in archaeological studies for reconstructing boundaries. Considering the uneven distribution and fairly low number of traits, the results of these two approaches are satisfactory.

Efficient Calculation of Distance Transform on Discrete Global Grid Systems

Geospatial data analysis often requires the computing of a distance transform for a given vector feature. For instance, in wildfire management, it is helpful to find the distance of all points in an area from the wildfire’s boundary. Computing a distance transform on traditional Geographic Information Systems (GIS) is usually adopted from image processing methods, albeit prone to distortion resulting from flat maps. Discrete Global Grid Systems (DGGS) are relatively new low-distortion globe-based GIS that discretize the Earth into highly regular cells using multiresolution grids. In this paper, we introduce an efficient distance transform algorithm for DGGS. Our novel algorithm heavily exploits the hierarchy of a DGGS and its mathematical properties and applies to many different DGGSs. We evaluate our method by comparing its speed and distortion with the distance transform methods used in traditional GIS and general 3D meshes. We demonstrate that our method is efficient and has minimal distortion.

A GIS-supported Multidisciplinary Database for the Management of UNESCO Global Geoparks: the Courel Mountains Geopark (Spain)

The management of a UNESCO Global Geopark (UGGp) requires a vast wealth of miscellaneous scientific knowledge that can be successfully organised using a Geographical Information System (GIS). This paper presents a pragmatic GIS database to assist in the suitable governance of the Courel Mountains UGGp (2017) in Northwest Spain. The database is structured in 66 coverages compiled from public sources and previous works or produced through traditional mapping (combining fieldwork and photointerpretation) and GIS tools. The acquired data was later homogenised and validated by a multidisciplinary team and archived in independent coverages. Forty thematic maps illustrate the broad range of cartographic information included in the GIS database. Among them, 25 basic maps provide an overview of the UGGp and 15 new maps focus on crosscutting and technical issues. All maps illustrate the huge potential of GIS to create new resources combining coverages and adapting the legend according to their purpose and audience. The database facilitates the suitable publishing of consistent outputs (e.g., brochures, books, panels, webpages, web serves), as well as the elaboration of technical data to assist the park management. The database furnishes information on the design of education actions, touristic routes, activities and Geopark facilities. The GIS database is also a supportive tool for scientific research and provides the necessary knowledge to conduct geoconservation actions based on land use, geological hazards and the occurrence of natural and cultural heritages. Altogether, the GIS database constitutes a powerful instrument for policy-making, facilitating the identification and evaluation of alternative strategy plans.

Geophysical Mapping of Ghana Using Advanced Cartographic Tool GMT

Ghana is a country exceptionally rich in geologic mineral resources with contrasting topographic relief and varied geophysical setting. This paper evaluated the geological and geophysical setting of Ghana with a special focus on the impact of the geologic setting and topography on gravity. Specifically, it assessed how variations in geology, topography, landscapes and the environment control the geophysical parameters and how these vary among the major regions of the country – the Volta Basin, Northern Plains, Ashanti-Kwahu (Kumasi) and Coastal Plains in the Accra surroundings. Previous studies utilizing traditional Geographic Information System (GIS) approaches have documented the geologic evolution of Ghana evolved as a part of the West African Craton. As a contribution to the existing research, this paper presents a regional analysis of Ghana by integrated mapping of geology, geophysics and topography of the country. The technical approach of this research focuses on utilizing the console-based scripting cartographic toolset Generic Mapping Tools (GMT) integrated with QGIS for processing and mapping the datasets: General Bathymetric Chart of the Oceans (GEBCO), Earth Gravitational Model 2008 (EGM-2008), gravity grids. The theoretical background is based on the geologic research of West Africa supported by high-resolution data. The paper defines a conceptual cartographic framework for integrated geologic and geophysical visualization in a regional-scale mapping project on Ghana.

Processes and events in the centre: a dynamic data model for representing spatial change

ABSTRACT Traditional geographic information system models for map representation use superposition of layers to model physical reality, neglecting the integrity of the environment and limiting the ability to express interactions between features in complex phenomenon. This results in limitations regarding dynamic simulation and geographic causality reasoning. In this paper, we extend the framework of the geographic scene by formalizing the relationship between geographic processes and events to construct a dynamic data model: the process-event-centred dynamic data model. The key element of this data model is relationships between processes, events, and states of the natural or man-made phenomenon of interest. The identified relationships can be translated into a network of hierarchical, developmental, and causal graphs and realized in the Neo4j graph database. The implementation in the graph database supports spatio-temporal reasoning in geographic scenes and achieves an organizational framework for simulating spatio-temporal dynamics and complex calculations. The example of a 2019 mega-typhoon process is used to demonstrate the introduced process-event-centred model and its implementation in the graph database. A series of queries to the graph database show the capabilities of the data model for spatial reasoning and dynamic modeling.

Using Neural Networks for Bicycle Route Planning

This paper presents the usage of artificial neural networks (NNs) in bicycle route planning. This research aimed to check the possibility of NNs to transfer human expertise in bicycle route design by training the NN on an already established set of bicycle routes and then using the trained NN to design the routes on the novel area. We created two NNs capable of choosing the best route among the given road network by training them on two different areas. The bicycle routes produced by NNs were the same at best and had 75% overlap at the worst compared to those produced by human experts. Furthermore, the mean square error for all of our NN models varied from 0.015 and 0.081. We compared this new approach to the traditional multicriteria GIS (geographic information system) analysis (MA) that requires the human expert to define the bicycle route selection criteria. The benefit of using NN over the MA was that the NN directly transfers the human expertise to a model. In contrast, the MA needs the expert to select multiple criteria and adjust their weights carefully.

Combination of GIS with Different Technologies for Water Quality: An Overview

Water is one of the most important requirements in daily life, which represents the largest part of the Earth. As a result of the economic, industrial and social development in most countries led to increased pollution in water resources. It is, therefore, necessary to monitor water quality continuously to prevent a future catastrophe that adversely affects the quality and quantity of water wealth. Geographic Information System (GIS) is used in various fields to monitor, analyze data collected from different geographical locations. Integration of GIS and other technologies has become an indispensable tool. This gives us direct control over solution expansion, cost reduction, powerful complex case analysis as well as increased accuracy and efficiency of geospatial data. In recent years, many combinations of GIS with different technologies such as remote sensing, wireless sensor networks, internet of things approaches have been proposed due to the rapid progress of technology development in many applications. However, in last several years, there is no survey paper has been published about water quality using the integration of GIS and other technologies. Therefore, this paper investigates the status of continuous search in the field of GIS and its integration with other technologies (Remote Sensing, Internet of Things, Web, etc.) for water quality management and monitoring to maintain the water resources in a proper way. As conclusions, the integration of the GIS with these technologies is a powerful platform for analyzing and processing big data and mapping geographic remotely in less time, less cost, high speed and with more accurate details and in real time compared to traditional geographic information systems. This paper also highlights future research trends about the cooperation of GIS with other technologies for matters that are related to water quality. Doi: 10.28991/HIJ-2021-02-03-10 Full Text: PDF

A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy

The multifunctional Ecosystem Service supply analysis at the spatial level is often the output of a weighted sum of layers in a Geographic Information System (GIS). This procedure is weak in detecting and representing the relationships between the input layers. Nonetheless, composite indicators produced by overlaying techniques are quite common in applied research and their discrepancies are underestimated in the scientific community, thus affecting the quality of resulting composite maps. In this work, we empirically test the effectiveness of multivariate statistics to obtain reliable composite Ecosystem Maps in the Turin metropolitan area (north-west Italy). We apply the Principal Component Analysis (PCA, using Matlab and ESRI ArcGis) to seven Ecosystem Service models (Habitat Quality, Carbon Sequestration, Water Yield, Nutrient Retention, Sediment Retention, Crop Production and Crop Pollination) and we evaluate how much the resulting composite map differs from the traditional GIS overlay. In doing this, the spectral analysis (with eigenvectors and eigenvalues) of the covariance matrix of the normalized layers confirms the heuristic arguments about the dependence between Ecosystem Services. We show that the PCA method can provide valuable results in landscape Green Network design, avoiding the limits of standard overlaying procedures. Finally, smoothing and classification techniques, applied to PCA estimates, can further improve the approach and encourage its use in various ecological indicators.

A qualitative geographical information system interpretation of mobility and COVID-19 pandemic intersection in Uttar Pradesh, India.

Mobility of individuals and their physical social networks are the root causes for the spread of current coronavirus pandemic. We propose here a method of visualizing the spatial and chronological aspects of the spread of this virus based on geographical information systems (GIS) and Gephi graphs. For this approach we used qualitative data from newspaper reports and prepared layouts varying from macro to micro scales that show that this approach can enrich traditional GIS approaches, thereby assisting mobility planners and policymakers.

RETRACTED: 3D landscape art design and network space reconstruction based on complex embedded system

Network space has gone beyond the map. Many critics claim that Geographic Information Systems (GIS) determines the environment. New geotechnical technologies such as embedded computer systems and tools, cyberspace network space reconstruction, and aerial photography allow network space to obtain large amounts of back-specified 3D data, but these 3D technologies are environmentally friendly. Help deal with positive criticism. Can connect GIS and 3D. It back-specifies the 3D model with basic data and adds a ground-based network space reconstruction to the traditional GIS aerial view. This proposed to place GIS and 3D in an index frame and wrap the environmental and network space elements using 3D GIS for the network space reconstruction of the new landscape archeological network space. 3D-models and displays in scene architectonic examination and plan. These scene models, close to drawings and guides, are urgent during plan examination and exploration by the scene engineering program. In this regard, models offer scene scientists and creators of various activity methods for visual reasoning and visual correspondence. This commitment investigates the different elements of (enlarged) models for scene designers, incorporating investigation, affirmation, union and introduction regarding use and cycle. It presents a typology of models depending on their exhibition (instrumental use), exemplified by a few cases. Even though the attention here is on the function of models in scene engineering, the contention created in this paper is additionally pertinent to the firmly related controls of engineering and metropolitan plan and accordingly replaceable.

Messy maps: Qualitative GIS representations of resilience

To include qualitative aspects of flood resilience, such as emotion, social connections and experience, into urban planning, we present a methodology incorporating innovative and experimental map visualisations of informal settlements. The concept of resilience in urban planning is often deployed in technocratic ways using quantitative tools such as geographic information systems (GIS). Yet in the urban Global South, where high proportions of the population live in informal settlements, the knowledge infrastructures used by public authorities leave little room for participation and consideration of local experience. We outline arts-based workshop activities and a qualitative GIS methodology to map resilience as defined by informal settlement residents in two case study cities, Nairobi (Kenya) and Cape Town (South Africa), with applicability across the urban Global South. For each city, four map layers were generated: (i) flood footprints showing resident’s spatial knowledge of floods; (ii) georeferenced, narrated 360° photo spheres capturing different perspectives about a space; (iii) spatial social network maps showing residents connections to formal and informal actors before/during floods; (iv) multimedia pop-ups communicating contextual details missing from traditional GIS maps. We show how these prototype maps can be integrated within planning knowledge infrastructures. For spatially imprecise qualitative aspects of resilience in informal settlements, placing markers on a map makes them visible in ways that planners can begin to engage with. Although challenges remain, we found openness in Nairobi and Cape Town by city-level actors to use qualitative forms of evidence, and that the contextual detail aided their retention and understanding of resilience.

Design and monitoring of oil and gas industry facilities based on the use of ultra-light aviation and digital technologies

The current stage in the development of the information support of the oil and gas complex is is characterized by the transition from corporate information and reference geographic information systems (GIS) to the development and creation of automated information-analytical and information-management systems. Traditional GIS – technologies provide optimal organization and comfortable access to databases of geographically distributed information. The new generation of GIS is designed, in addition to providing information and reference functions, to solve a set of tasks for managing complex multi-level geotechnical systems (GTS) of oil and gas condensate fields for the purpose of rational nature management and sustainable development of natural and man-made GTS.

Next-generation geospatial-temporal information technologies for disaster management

Traditional geographic information systems (GIS) have been disrupted by the emergence of Big Data in the form of geo-coded raster, vector, and time-series Internet-of-Things data. This article discusses the application of new scalable technologies that go far beyond relational databases and file-based storage on spinning disk or tape to incorporate both storage and processing data in the same platform. The roles of the Apache Hadoop Distributed File Systems and NoSQL key-value stores such as the Apache Hbase are discussed, along with indexing schemes that optimally support geospatial-temporal use. We highlight how this new approach can rapidly search multiple GIS data layers to obtain insights in the context of early warning, impact evaluation, response, and recovery to earthquake and wildfire disasters.

Using Geographic Ontologies and Geo-Characterization to Represent Geographic Scenarios

Traditional Geographic Information Systems (GIS) represent the environment under reductionist thinking, which disaggregates a geographic environment into independent geographic themes. The reductionist approach makes the spatiotemporal characteristics of geo-features explicit, but neglects the holistic nature of the environment, such as the hierarchical structure and interactions among environmental elements. To fill this gap, we integrate the concept geographic scenario with the fundamental principles of General System Theory to realize the environmental complexity in GIS. With the integration, a geographic scenario constitutes a hierarchy of spatiotemporal frameworks for organizing environmental elements and subserving the exploration of their relationships. Furthermore, we propose geo-characterization with ontological commitments to both static and dynamic properties of a geographic scenario and prescribe spatial, temporal, semantic, interactive, and causal relationships among environmental elements. We have tested the utility of the proposed representation in OWL and the associated reasoning process in Semantic Web Rule Language (SWRL) rules in a case study in Nanjing, China. The case study represents Nanjing and the Nanjing presidential palace to demonstrate the connections among environmental elements in different scenarios and the support for information queries, evolution process simulation, and semantic inferences. The proposed representation encodes geographic knowledge of the environment, makes the interactions among environmental elements explicit, supports geographic process simulation, opens opportunities for deep knowledge mining, and grounds a foundation for GeoAI to discover geographic complexity and dynamics beyond the support of conventional theme-centric inquiries in GIS.

TerraBrasilis: A Spatial Data Analytics Infrastructure for Large-Scale Thematic Mapping

The physical phenomena derived from an analysis of remotely sensed imagery provide a clearer understanding of the spectral variations of a large number of land use and cover (LUC) classes. The creation of LUC maps have corroborated this view by enabling the scientific community to estimate the parameter heterogeneity of the Earth’s surface. Along with descriptions of features and statistics for aggregating spatio-temporal information, the government programs have disseminated thematic maps to further the implementation of effective public policies and foster sustainable development. In Brazil, PRODES and DETER have shown that they are committed to monitoring the mapping areas of large-scale deforestation systematically and by means of data quality assurance. However, these programs are so complex that they require the designing, implementation and deployment of a spatial data infrastructure based on extensive data analytics features so that users who lack a necessary understanding of standard spatial interfaces can still carry out research on them. With this in mind, the Brazilian National Institute for Space Research (INPE) has designed TerraBrasilis, a spatial data analytics infrastructure that provides interfaces that are not only found within traditional geographic information systems but also in data analytics environments with complex algorithms. To ensure it achieved its best performance, we leveraged a micro-service architecture with virtualized computer resources to enable high availability, lower size, simplicity to produce an increment, reliable to change and fault tolerance in unstable computer network scenarios. In addition, we tuned and optimized our databases both to adjust to the input format of complex algorithms and speed up the loading of the web application so that it was faster than other systems.

Poverty and environmental nexus in rural Pakistan: a multidimensional approach

The study examines the relationship between poverty and forest cover degradation in rural areas of Pakistan. The area selected for the study District Upper Dir is a rural and relatively backward region located in northwestern Pakistan, in Khyber-Pakhtunkhwa province. The study area is undergoing severe deforestation and natural disasters in the recent past. The study consists of two stages, in first stage the traditional Geographical information system image was used to analyze the spatial–temporal situation of the surroundings. In the second stage, well-designed questionnaire was used to collect the primary information from 420 randomly selected households of research areas. A multidimensional poverty index has been used to measure the poverty profile of the population. It has been found that 55% households were below the poverty line. Almost, 95% households are using wood for cooking purposes. High dependence on natural resources causes forest cover degradation while burning off too much wood causes CO2 emission and leads to environmental degradation. A major portion of population is living on steeply sloped areas with certain risks. It is found that frequency of flash flood is 53% and agricultural land (54%) is at high risk and often flows with flash floods. It is concluded that there is strong correlation between multidimensional poverty and forest cover degradation which leads to climate and environmental risks.