Conventional Geographic Information Systems Research Articles

Participatory topological mapping: A novel approach for exploring and communicating situated knowledge of complex socio-ecological systems

Land use change impacts on Sámi reindeer husbandry are well-documented, but existing maps often fail to capture socio-ecological relationships between herders, reindeer and nature. Conventional Geographic Information Systems (GIS) simplify these relationships, lacking local context and excluding valuable knowledge due to their rigid structure. This paper introduces participatory topological mapping, a low-tech, knowledge co-production method that allows communities to share geospatial insights without advanced software. Combining hand-drawn maps with a standardised topological structure facilitates the visualisation of geographical relationships and dynamic land use systems from a local perspective. Developed and assessed through a Swedish case study in collaboration with Vittangi and Malå reindeer herding communities, the method aims to reduce barriers to knowledge exchange and enhance dialogue between Indigenous knowledge-holders, researchers and decision-makers. The paper discusses the authors’ experiences with participatory topological mapping, emphasising its potential and limitations for knowledge exchange. The method is advocated for broader use, recognising its value in articulating concerns about land use change beyond research settings and reindeer husbandry. Participatory topological mapping enables knowledge-holders to control the map and its narrative, deciding what is included or excluded. The maps and accompanying stories are valuable sources for documenting, sharing and analysing local perspectives on landscapes and the effects of land use change. The method treats mapping as a social process with the potential to affect how we understanding the world. When thoughtfully applied, it offers a valuable avenue for knowledge co-production, fostering deeper engagement, supporting informed decision-making and empowering communities.

Artificial Neural Networks for Mapping Coastal Lagoon of Chilika Lake, India, Using Earth Observation Data

This study presents the environmental mapping of the Chilika Lake coastal lagoon, India, using satellite images Landsat 8-9 OLI/TIRS processed using machine learning (ML) methods. The largest brackish water coastal lagoon in Asia, Chilika Lake, is a wetland of international importance included in the Ramsar site due to its rich biodiversity, productivity, and precious habitat for migrating birds and rare species. The vulnerable ecosystems of the Chilika Lagoon are subject to climate effects (monsoon effects) and anthropogenic activities (overexploitation through fishing and pollution by microplastics). Such environmental pressure results in the eutrophication of the lake, coastal erosion, fluctuations in size, and changes in land cover types in the surrounding landscapes. The habitat monitoring of the coastal lagoons is complex and difficult to implement with conventional Geographic Information System (GIS) methods. In particular, landscape variability, patch fragmentation, and landscape dynamics play a crucial role in environmental dynamics along the eastern coasts of the Bay of Bengal, which is strongly affected by the Indian monsoon system, which controls the precipitation pattern and ecosystem structure. To improve methods of environmental monitoring of coastal areas, this study employs the methods of ML and Artificial Neural Networks (ANNs), which present a powerful tool for computer vision, image classification, and analysis of Earth Observation (EO) data. Multispectral satellite data were processed by several ML image classification methods, including Random Forest (RF), Support Vector Machine (SVM), and the ANN-based MultiLayer Perceptron (MLP) Classifier. The results are compared and discussed. The ANN-based approach outperformed the other methods in terms of accuracy and precision of mapping. Ten land cover classes around the Chilika coastal lagoon were identified via spatio-temporal variations in land cover types from 2019 until 2024. This study provides ML-based maps implemented using Geographic Resources Analysis Support System (GRASS) GIS image analysis software and aims to support ML-based mapping approach of environmental processes over the Chilika Lake coastal lagoon, India.

Planning and Analyzing Transit Networks: An Integrated Approach Regarding Requirements of Passengers and Operators

Providing an equally sufficient and efficient transit service requires careful planning and permanent monitoring of service quality, operating costs, and revenues. These requirements need a model that is capable of determining impacts on passengers as well as operators. Additionally, it is important to provide suitable and powerful methods to design and to modify the transit network. The transport planning software VISUM attempts to fulfill these requirements. In contrast to conventional Geographic Information Systems (GIS), which are extended to provide specific functionality for transit planning, VISUM is a comprehensive transportation model with additional GIS functionality. It seeks to fill the gap between conventional GIS programs and vehicle scheduling programs.

Dynamic Optimization Modeling of Smart Tourism Information System Using VRGIS in Big Data Environment.

The establishment of an intelligent, comprehensive, and all-encompassing information system for tourism management is the current trend in tourism informatization as a result of the continual development of modern information technology. Significant advancements in the field of VRGIS and its usage in research have been made as a result of the use of VRGIS to categorize, assess, plan, and manage tourism resources. The analysis of the recent development of VRGIS in tourism resource research is the first section of this work. This study examines and implements a mobile, computerized, and intelligent tourism service system that gives visitors a sense of the surrounding landscape using VRGIS. Three-dimensional mapping, environment detection, personal trajectory, and Weibo sharing are just a few of the system's many helpful features. While travelling, tourists can get services that are more intelligent and practical. The drawbacks of conventional geographic information systems include their reliance on sophisticated models, network limitations, and operational challenges. New software architecture is put in place to get rid of network restrictions, virtual reality peripherals are used to make operation more convenient, and system modeling is rebuilt using the TIN data model and model simplification. The results of experiments show improved refresh rates and peripheral expansion modules. The user experience is enhanced by this research.

Freight Operations Modelling for Urban Delivery and Pickup with Flexible Routing: Cluster Transport Modelling Incorporating Discrete-Event Simulation and GIS

Urban pickup and delivery (PUD) activities are important for logistics operations. Real operations for general freight involve a high degree of complexity due to daily variability. Discrete-event simulation (DES) is a method that can mimic real operations and include stochastic parameters. However, realistic vehicle routing is difficult to build in DES models. The objective is to create a DES model for realistic freight routing, which considers the driver’s routing decisions. Realistic models need to predict the delivery route (including time and distance) for variable consignment address and backhaul pickup. Geographic information systems (GIS) and DES were combined to develop freight PUD models. GIS was used to process geographical data. Two DES models were developed and compared. The first was a simple suburb model, and the second an intersection-based model. Real industrial data were applied including one-year consignment data and global positioning system (GPS) data. A case study of one delivery tour is shown, with results validated with actual GPS data. The DES results were also compared with conventional GIS models. The result shows the intersection-based model is adequate to mimic actual PUD routing. This work provides a method for combining GIS and DES to build freight operation models for urban PUD. This has the potential to help industry logistics practitioners better understand their current operations and experiment with different scenarios.

Automatic Horizontal Curve Identification for Large Areas from Geographic Information System Roadway Centerlines

The geography of horizontal roadway curves is critical to various disciplines, especially to transportation safety, because of their strong correlation with traffic crashes. Remarkably, conventional geographic information system (GIS) roadway centerlines, while fundamental and ubiquitous in current geospatial databases, do not include curve inventories. This study presents an improved method for automatic horizontal curve identification using GIS roadway centerline networks as the data source. Analyzing each vertex of the network geometry, this method identifies the curves by detecting deflections from straight lines using a vertex deflection angle threshold. Different from literature that uses a static threshold, this method develops and applies a dynamic threshold by considering two variables—the roadway speed and the centerline vertex density. The method is capable of self-adjusting using k-means clustering to compensate for uneven centerline digitization. The method can also detect spiral transitions and can handle the complexities of street networks represented using dual centerlines. The testing and validation of the method were performed on a large dataset by applying a combination of goodness of fit metric and visual inspection. The results show that this method improves curve identification accuracy and can provide broader applicability for curve identification using GIS centerlines of various representations and digitization quality in large geographic areas.

Critical Approaches to GIS and Spatial Mapping in Indonesia Forest Management and Conservation

The conventional Geographic Information Systems (GIS) and spatial mapping techniques fail to understand a spatially complex forest area. This is because forest landscapes cannot be easily mapped into a two-dimensional map, which is usually used in spatial planning. In addition, planning maps are the fundamental factors of land grabbing issues. To solve this problem, counter-mapping arises at the local level as a tool to overcome the problem of land grabbing in forest areas in Indonesia. Counter mapping is defined here as part of a broader term under participatory mapping or citizen mapping. However, counter-mapping also faces critiques in terms of different epistemological and socio-economic-political conditions at the local level. This article elaborates the use of GIS and spatial mapping methods within a 'critical' social science approach based on literature review and field experiences. This article also aims to analyze counter-mapping as a ‘tool’ to solve the forest land-use problem, which can contribute to the choice of policy instruments in forest management and conservation in Indonesia.

Environmental geology assessment on the regional Pitay landfill site: a case study in Kupang, Indonesia

The Provincial Government of East Nusa Tenggara of Eastern Indonesia has intended to construct a new regional landfill site in Pitay–Kupang, which would accommodate municipal waste of two cities. Considering that environmental degradation in landfill sites has been a substantial issue for many developing cities in Indonesia, this study evaluates the pre-determined site on a local scale based on environmental geology parameters. It employs a conventional Geographical Information System based—Multi-Criteria Decision Analysis (GIS-MCDA) method which is based on the analysis of regional criterion, assessed by expressing values on each parameter presented on thematic maps and overlaid altogether as a screening process, and the exclusion criterion analysis, which sets a buffer zone to filter out irrelevant locations. The regional criterion parameters are: Lithology, groundwater depth, slope gradient and rainfall intensity, whilst the exclusion criterion parameters are: Distance from rivers and lakes, shorelines, settlements, main roads, airports and protected areas, distance from potential geological hazards such as fault zones, floods and mass movements, and distance from any geological potential which may be developed in the future. The biggest area reduction for suitable landfill site candidate is lithology, correlating with groundwater depths, and distance from rivers. Here we identified four potential sites located west and centre of Pitay, situated on Bobonaro scaly clay lithology unit, arguably possessing no groundwater with a slope gradient of 0–20%, rainfall intensity below 1000 mm, and is distant from any potential hazards, promising geological resources and other unfavorable criteria relating to environmental degradation.

Learning from critiques of GIS for assessing the geoweb and indigenous knowledges

Advances in geospatial technologies over recent years have marked dramatic changes in traditional cartographic practices and conventional geographic information systems (GIS). Scholars in GIScience and digital geographies commonly argue that, compared to GIS, the geospatial web (geoweb) offers improved opportunities for Indigenous communities to make their own maps, contribute their own place-based content, and tell their own stories. Critical GIS has informed us about the potential issues with the use of spatial technologies in Indigenous contexts, which we synthesize into three themes: 1. compartmentalizing and distilling Indigenous knowledges, 2. undermining Indigenous ways of knowing and of transferring knowledges, and 3. exploiting and assimilating Indigenous knowledges. These three criteria are used to assess what Indigenous communities should examine when engaging with the geoweb and Indigenous knowledges. Our analysis focuses on issues of data ownership, access, sharing, and appropriation. We point to ways in which Indigenous peoples should carefully assess various components of the geoweb to avoid the misrepresentation, distortion, assimilation, exclusion, and exploitation of Indigenous knowledges and Indigenous ways of transmitting knowledge. We conclude with potential solutions for development of the geoweb.

Expressing History through a Geo-Spatial Ontology

Conventional Geographical Information Systems (GIS) software struggles to represent uncertain and contested historical knowledge. An ontology, meaning a semantic structure defining named entities, and explicit and typed relationships, can be constructed in the absence of locational data, and spatial objects can be attached to this structure if and when they become available. We describe the overall architecture of the Great Britain Historical GIS, and the PastPlace Administrative Unit Ontology that forms its core. Then, we show how particular historical geographies can be represented within this architecture through two case studies, both emphasizing entity definition and especially the application of a multi-level typology, in which each “unit” has an unchanging “type” but also a time-variant “status”. The first includes the linked systems of Poor Law unions and registration districts in 19th century England and Wales, in which most but not all unions and districts were coterminous. The second case study includes the international system of nation-states, in which most units do not appear from nothing, but rather gain or lose independence. We show that a relatively simple data model is able to represent much historical complexity.

Replication of the Question-Based Spatial Computing Approach – Experiences and Suggestions for Further Developments

Geographic Information Systems (GIS) have developed into complex toolboxes and require analysts to formulate spatial questions according to the requirements of the data formats and tools provided by their specific GIS-application. The recently proposed language for spatial computing aims to provide a question-based and thus more comprehensible approach for spatial analyses that especially supports scientists and experts from other disciplines to conduct spatial analyses in their fields. In this contribution, we apply the question-based spatial computing approach to a case study in the humanitarian field and compare the resulting script to one written using a conventional GIS tool. The comparison of the two versions of the script is based on six criteria covering qualitative and quantitative aspects of the analysis. We also discuss the implementation concept behind the new language. Our results show that the new approach requires fewer computational steps than the conventional script. In addition, the declarative approach allows users to focus on the content of the spatial question, and the query-like character of the language makes it easier to understand for non-GIS specialists. In addition, we share observations on challenges of the further development of the language as an outcome of this study.

Study on the Development of Geo-Spatial Big Data Service System based on 7V in Korea

Within recent years, enormously increasing open government data, smart devices, and location-based service requires several new approaches and solutions, incapable in the conventional geo-spatial information technology. Many endeavors in public and private sectors try to overcome the inherent deficiency of conventional Geographic Information System (GIS) by integrating Big Data and geo-spatial technology into Geo-Spatial Big Data platform. To secure technology to store, manage, analyze, and deliver service efficiently for Geo-Spatial Big Data (GSBD) with high volume in size, this study interprets GSBD platform as 7V characteristics and suggests 7V-based implementation strategy for GSBD service system. Especially, the concept and characteristics of GSBD were examined from the GSBD service perspective, based on which, a framework for GSBD service was suggested, with a plan to implement a 7V-based GSBD service system. Finally, a service scenario was set to analyze the changes in South Korea territory, with a pilot system for a GSBD service supporting it being implemented and substantiated.

Natura 2000 habitat of Mt. Argentario promontory (southern Tuscany, Italy)

ABSTRACTThe Mt. Argentario promontory (southern Tuscany, Italy) is a protected area hosting habitats and species of European importance. The Mt. Argentario Natura 2000 habitat map (1:10,000) was compiled from photo-interpretation and field surveys, integrated with data from past cartographic and phytosociological studies. Conventional geographical information system procedures were used to select and manage spatial information, and delimit the map polygons. The following attributes were assigned to each map polygon: (i) habitat type name, with Natura 2000 code and (ii) percentage cover of the habitat type. Where multiple habitat types were associated in a mosaic attributed to the same polygon, the percentage cover of each habitat type was estimated. The survey allowed to identify and map a total of 13 Natura 2000 habitat types covering more than 40% of the study area. Presence and conservation importance of the detected habitat types are discussed, together with the usefulness of this kind of maps for monitoring and managing purposes.

Geographic Information Science and the Analysis of Place and Health.

The representation of place is a key theoretical advancement that Geographic Information Science can offer to improve the understanding of environmental determinants of health, but developing robust computational representations of place requires a substantial departure from conventional notions of geographic representation in Geographic Information Systems (GIS). Unlike conventional GIS representations based on either objects or locations, we suggest place representation should incorporate dynamic subjective, experiential, and relational aspects of place, as the influence of place on health behavior concerns not only the features that can be objectively observed at a particular location but also the environmental perceptions of the individual, as molded by biological, social, and experiential characteristics. In addition, assessments of environmental exposures on health outcomes should focus on individuals' time-activity patterns and microenvironment profiles, which form a potentially unique personalized exposure environment for each individual. Addressing these representational challenges via collaborative research has the potential to advance both Geographic Information Science and health research.

Interpreting the Fuzzy Semantics of Natural-Language Spatial Relation Terms with the Fuzzy Random Forest Algorithm

Naïve Geography, intelligent geographical information systems (GIS), and spatial data mining especially from social media all rely on natural-language spatial relations (NLSR) terms to incorporate commonsense spatial knowledge into conventional GIS and to enhance the semantic interoperability of spatial information in social media data. Yet, the inherent fuzziness of NLSR terms makes them challenging to interpret. This study proposes to interpret the fuzzy semantics of NLSR terms using the fuzzy random forest (FRF) algorithm. Based on a large number of fuzzy samples acquired by transforming a set of crisp samples with the random forest algorithm, two FRF models with different membership assembling strategies are trained to obtain the fuzzy interpretation of three line-region geometric representations using 69 NLSR terms. Experimental results demonstrate that the two FRF models achieve good accuracy in interpreting line-region geometric representations using fuzzy NLSR terms. In addition, fuzzy classification of FRF can interpret the fuzzy semantics of NLSR terms more fully than their crisp counterparts.

Physarum machines imitating a Roman road network: the 3D approach

Physarum Polycephalum is a single cell visible by unaided eye. This is a plasmodial, vegetative stage of acellular slime mould. This single cell has myriad of nuclei which contribute to a network of bio-chemical oscillators responsible for the slime mould’s distributed sensing, concurrent information processing and decision making, and parallel actuation. When presented with a spatial configuration of sources of nutrients, the slime mould spans the sources with networks of its protoplasmic tube. These networks belong to a family of planar proximity graphs. The protoplasmic networks also show a degree of similarity to vehicular transport networks. Previously, we have shown that the foraging behaviour of the slime mould can be applied in archaeological research to complement and enhance conventional geographic information system tools. The results produced suffered from limitation of a flat substrate: transport routes imitated by the slime mould did not reflect patterns of elevations. To overcome the limitation of the ‘flat world’ we constructed a three-dimensional model of Balkans. In laboratory experiments and computer modelling we uncovered patterns of the foraging behaviour that might shed a light onto development of Roman roads in the Balkans during the imperial period (1st century BC – 4th century AD).

Function Modeling Improves the Efficiency of Spatial Modeling Using Big Data from Remote Sensing

Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have applied those models in a multiprocessor environment. Few, however, have recognized the inefficiencies associated with the underlying spatial modeling framework used to implement such analyses. In this paper, we identify a common inefficiency in processing spatial models and demonstrate a novel approach to address it using lazy evaluation techniques. Furthermore, we introduce a new coding library that integrates Accord.NET and ALGLIB numeric libraries and uses lazy evaluation to facilitate a wide range of spatial, statistical, and machine learning procedures within a new GIS modeling framework called function modeling. Results from simulations show a 64.3% reduction in processing time and an 84.4% reduction in storage space attributable to function modeling. In an applied case study, this translated to a reduction in processing time from 2247 h to 488 h and a reduction is storage space from 152 terabytes to 913 gigabytes.

Natura 2000 protected habitats, Massaciuccoli Lake (northern Tuscany, Italy)

ABSTRACTThe Massaciuccoli Lake (northern Tuscany, Italy) Natura 2000 habitat map (1:10,000) was compiled from photo-interpretation and recent phytosociological studies, integrated by field surveys of the vegetation units. Conventional geographical information system procedures were used to select and manage spatial information. The following attributes were assigned to each map polygon: (i) vegetation type, (ii) habitat typology and (iii) percentage cover of the habitat type. Habitat types covering polygons smaller than 50 m2 were treated as points. A total of nine Natura 2000 habitat types were identified and mapped; they cover almost 20% of the study area. The results show that of all sites on the Italian peninsula, Lake Massaciuccoli Calcareous fens with Cladium mariscus covers the largest surface area and is crucial for the national conservation of this habitat type. It is also of priority importance in Europe.

Modeling Place as a Relationship between a Person and a Location

GIScience 2016 Short Paper Proceedings Modeling Place as a Relationship between a Person and a Location J. Mennis 1 , M.J. Mason 2 Department of Geography and Urban Studies, Temple University, 1115 Polett Walk, 309 Gladfelter Hall, Philadelphia, PA 19122, USA Email: jmennis@temple.edu Department of Psychiatry, Virginia Commonwealth University, 515 North 10 th Street, P.O.Box 980489, Richmond, VA 23298-0489 USA Email: michael.mason@vcuhealth.org Abstract Place can be understood, and represented, not only as an attribute of a location but also as the emotional attachments that characterize a relationship between an individual and a location. We demonstrate the development and application of this principle in place-based geographic information systems (GIS) through the use of georeferenced ecological momentary assessment (EMA), an approach for gathering real-time, in-situ data on individuals’ mood states, behaviors, and social interactions via brief surveys delivered on a mobile phone. As a case study, we focus on the representation and analysis of the effect of activity space exposure to vacant housing on perceived safety among a sample of 139 urban adolescents enrolled in a longitudinal, georeferenced EMA study. 1. Introduction Researchers have distinguished place-based geographic information systems (GIS) as emphasizing subjective interpretations of locations (Elwood et al. 2013). It has been suggested that geographic information scientists should look to research in cognitive science and humanistic geography for inspiration to developing representational and analytical approaches to place-based GIS (Winter and Freksa 2012). Such a perspective has informed research on extracting place information from linguistic descriptions, formalizing computational notions of place, georeferencing place data, and reasoning with place data (Gao et al. 2013; Scheider and Janowicz 2014; Vasardani et al. 2013). Health behavior is a domain that is particularly appropriate for place-based GIS (Goodchild 2015), as environmental influences on health behaviors are often moderated by the characteristics of the individual, including not only group characteristics such as race, age, and gender, but also the unique prior life experiences each individual carries with them (Mennis and Mason 2011). Thus, environmental influences on health behaviour can be interpreted to occur through subjective constructions of place. Drawing from research in humanistic geography that posits place-making as construed through personal experience (Tuan 1977), we argue here that place-based GIS can represent place not only as a property of a location (as with conventional GIS), but also as a relationship between an individual and a location – a relationship that is molded by the unique characteristics and experiences of the individual (Mennis et al. 2013). We demonstrate the application of these principles using georeferenced ecological momentary assessment (EMA), an approach for gathering real-time, in-situ data on individuals’ mood states, behaviors, and social interactions via brief surveys delivered on a mobile phone. EMA combined with global positioning systems (GPS) for georeferencing enables the collection of integrated longitudinal survey and activity space data (Epstein et al. 2014; Mason et al. 2015). As a case study, we focus on the representation and analysis of place-based perceptions of safety among a sample of 139 adolescents enrolled in a longitudinal, georeferenced EMA study of substance use in Richmond, Virginia.

Detailed Natura 2000 and CORINE Biotopes habitat maps of the island of Elba (Tuscan Archipelago, Italy)

The island of Elba (Tuscan Archipelago, Italy) Natura 2000 habitat map (1:25,000) and the CORINE Biotopes habitat map (1:25,000) were derived from the phytosociological map of Elba integrated with recent studies and field knowledge of the vegetation units. Conventional geographical information system queries were used to manage and select the spatial information. For each map polygon, the following attributes were assigned: (i) habitat typology and (ii) percentage cover of each habitat type. Where multiple habitat types were associated with the same polygon, the percentage cover of each habitat type was estimated. A total of 27 Natura 2000 habitat types and 58 CORINE Biotopes habitat types were identified, these being distributed in single and/or multiple typological units. Distribution and covers of the different habitat types are discussed. The usefulness of this kind of map for monitoring and managing conservation actions is discussed.