GIS Tools Research Articles

How has digital participatory mapping influenced urban planning: Views from nine planning cases from Finland

Although the successfulness of public participation projects has been studied from many different perspectives, there is a lack of knowledge of how participation influences the planning outcomes. Through the interview study of nine Finnish urban planning projects, we studied how the use of a digital public participation GIS tool has influenced the outcomes of urban planning. In the selected cases the information collected with a PPGIS tool has been highly valued by the planners, leading to concretely influential participation in 6 out of 9 cases. In these cases, the planners gave concrete examples of how the information had influenced the created plan or draft. We created a model that describes how the information produced by participants is traveling from the participants to the outcome of the planning process. With this model, the main factors limiting the degree of influence were recognized, and actions were presented that could increase the influence.

Concept of Assessment of Age-Friendly Residential Areas (AFRA): A Case Study of Gdańsk, Poland

(1) Background: Local governments are facing a considerable challenge to accurately verify cities, as well as to diagnose the condition of housing estates in the context of their friendliness to life of older people in order to be able to pursue a sustainable pro-ageing policy. In response to these needs, universal methodology for identifying age-friendly residential areas (AFRA) in cities was developed and tested. Thus, the main objective of the research was to develop an innovative methodological approach to the AFRA assessment, taking into account integrated functional-spatial and aesthetic indicators with particular emphasis on the ways of presenting results. (2) Methods: The methodology was based on the general, international assumptions of “ageing in place”, “age-friendly city”, “active ageing”, and an in-depth analysis of contemporary trends in this field, using international guidelines and recommendations, as in the case of survey data from the target international population and information provided by experts. (3) Results: The overall result of the project is a universal methodology for diagnosing housing estates in cities, taking into account infrastructural and landscape determinants in terms of their friendliness to older people, including a presentation of the usefulness of GIS tools to create thematic maps visualising the degree of friendliness. (4) Conclusions: This innovative approach to AFRA visualisation will expand the knowledge about the possibilities of diagnosing age-friendly spaces in the city that are conducted at the level of the city’s settlement units. The developed list of criteria influencing the friendliness of housing estates for older citizens can be useful for public entities in creating city and housing planning policies for private entities to manage their own investment plans and implement the concept of on-site ageing in their planning and for real estate agents to explore the real estate market for the needs of older clients.

Methodology of Mosaicking and Georeferencing for Multi-Sheet Early Maps with Irregular Cuts Using the Example of the Topographic Chart of the Kingdom of Poland

The Topographic Chart of the Kingdom of Poland (pol. Topograficzna Karta Królestwa Polskiego, commonly referred to as ‘the Quartermaster’s Map’, hereinafter: TKKP) is the first Polish modern topographic map of Poland (1:126,000, 1843). Cartographic historians acclaim its conception by the General Quartermaster of the Polish Army, noting its editorial principles and technical execution as exemplars of the early 19th-century cartographic standards. Today, it stands as a national heritage relic, furnishing invaluable insights into the former Polish Kingdom’s topography. Although extensively utilised in geographical and historical inquiries, the TKKP has yet to undergo a comprehensive geomatic investigation and publication as spatial data services. Primarily, this delay stems from the challenges of mosaicking and georeferencing its 60 constituent sheets, owing to the uncertain mathematical framework and irregular sheet cuts. In 2023, the authors embarked on rectifying this by creating a unified TKKP mosaic and georeferencing the map to contemporary reference data benchmarks. This endeavour involved scrutinising the map’s mathematical accuracy and verifying prior findings. The resultant product is accessible via the ‘Maps with the Past’ platform, developed by the Institute of History of the Polish Academy of Sciences The dissemination of raster data services adhering to OGC standards such as WMTS (Web Map Tile Service), ECW (Enhanced Compression Wavelet), and COG (Cloud Optimized GeoTIFF) facilitates the swift and seamless integration of the generated data into web and GIS tools. The digital edition of the TKKP emerges as a pivotal resource for investigations spanning natural and anthropogenic environmental transformations, sustainable development, and cultural heritage studies.

Examining the effect of urbanization on various land cover classes and environmental quality using remote sensing and GIS methods

It is vital for public awareness and decision-makers to investigate the impact caused by changes in urban land use and land cover on ecosystem service values (ESVs) in order to promote sustainable urban development, protect the environment, protect public health, and ensure communities’ long-term well-being. Changes in ecosystem services brought on by changes in land use and cover (LULC) are a crucial early indicator and warning sign of ecological shifts. Using remote sensing and GIS tools, this study examined the shifting dynamics of ESVs in the Haridwar district in Uttarakhand state, India. The evaluation of land use land cover (LULC) changes was carried out by analyzing satellite images of the research region from 2001 to 2021. In addition, we examined changes in ecosystem services according to the study area’s LULC classifications. Using a random forest machine learning classifier, satellite images were classified into five categories of land cover: water bodies, forests, built-up areas, agricultural land, and bare land. The findings showed that from 2001 to 2021, forest cover and water bodies fell by 15.35% and 41.50%, respectively, while urban area and agricultural area rose by 69.24% and 12.31%, respectively. Due to increased urbanization and degradation of water bodies and forest areas, ESV fell from 103.19 USD ha −1 year −1 in 2001 to 70.53 USD ha −1 year −1 in 2021. The combination of LULC with the value of ecosystem services may improve our knowledge of several difficulties in an urban ecosystem. As a result, we advocate for the incorporation of LULC and ESVs as a tool that might be useful to urban planners and land managers in the future for sustainable development of natural resources.

Cities facing the European green deal: Urban policy and locals’ perspective in the post-socialist area

The European Green Deal (EGD) is a comprehensive and ambitious strategy to achieve climate neutrality in the European Union. Cities play a crucial role as places of accumulation of resources, as well as increased consumption. This study attempts to respond to whether the largest cities in Poland (the main development cores of the country and, more broadly, Central Europe) address the development challenges of the EU articulated in the EGD and derived from the concept of a smart city.In this study, not only the theory behind the smart city concept but also the strategic documents of the largest Polish cities in that matter are analysed. The socio-spatial analyses identified the existing discrepancies between the perspectives of local authorities and inhabitants in implementing contemporary development concepts. There were indicated SHS (smart hot spots) - which are those located in the city centre and places that act as mobility hubs, as well as SCS (smart cold spots) - which are remote from the centre or degraded and decapitalised places. The crucial challenge for urban policymakers is to level internal environmental and socio-economic inequalities and prevent the formation of “emerald islands” in the city interior.The proposed inclusive approach offers a tool that could be used in many similar case studies, including the need for dialogue with local society, the special consideration of the local context, heterogeneity and greater attention to the new sources of knowledge, including GIS tools, enabling the building of a viable local system.

SEGMENTATION OF PARCEL BOUNDARY INDICATIONS IN VERY HIGH-RESOLUTION ORTHOPHOTO MOSAICS FOR CONTROL POINT IDENTIFICATION

Several Land Parcel Geometry issues in Indonesia's Land Registration Process, such as parcel overlapping, gaps between parcels, and incorrect parcel shapes and sizes, are currently being addressed through a block adjustment approach. One crucial aspect of the block adjustment process is determining control points that tie the parcel geometry to the land coordinate system. Detailed Observations and measurements of parcel points in the field and aerial photographs established these control or tie points. Rectifying land parcels requires many control points, requiring substantial time and effort. The automation phase is critical to expedite the control point identification process. This research uses artificial intelligence techniques to identify control points in very high-resolution orthophoto mosaics. The method employed for control point identification involves the Segment Anything Model (SAM) algorithm to segment parcel boundary indications accurately. Enhance the quality of segmentation results conducted by fine-tuning, followed by centerline extraction and refinement of the extracted data. Based on the segmentation, a SAM model capable of accurately segmenting building objects is attained, After the centerline extraction process and modifications to the existing geometric operations within the GIS Tool, at the edges of buildings, fences, and walls derived points. These points can serve as control point indications in the block adjustment process.

Empirical Model of Unconsolidated Tephra Erosion: Verification and Application on Micro Catchment

Erosion is an important process that shapes the earth's surface. Given the complexity of the process, efforts to understand it are essential. Over the last 50 years, numerous models of soil particle erosion by surface runoff emerged, some of which share similar forms and parameters. The differences lie in the coefficient values of the parameters, attributed to the characteristics of the soil material such as texture, structure, and organic matter content. However, these erosion models tend to underpredict in the case of new volcanic deposit erosion. The erosion model for unconsolidated tephra, proposed by Yunita, was developed through laboratory experiments using volcanic material from Merapi Volcano, Indonesia. Nevertheless, the model has not been implemented for other cases. Therefore, this study aims to verify the erosion model for volcanic material in other cases, explore the possibility of broader implementation, identify the factors that influence its accuracy, and determine the model’s limitations. To verify the model’s potential for broader application, we applied it to micro-scale catchments in St. Hellens (USA), Sakurajima (Japan), and a laboratory scale plot in Merapi (Indonesia). The verification yielded satisfactory results for all three cases, especially for new tephra deposits. In the case of St. Helens, the extrapolation of model coefficients was proven to still be applicable even for thicker tephra layers. However, the erosion prediction was overestimated for tephra layer deposits older than 1 year, as the erosion rate decreases over time due to the compaction and stabilization of the tephra layer. In the Sakurajima, the model was also suitable for predicting long-term erosion amounts (daily and monthly). Meanwhile, in Merapi, the model provided accurate predictions for slopes of 20º and 25º but was less accurate for 30º slopes, where the measured erosion was due to both erosion and slope failure. These verification results demonstrate the potential of applying the empirical erosion model to micro catchments with relatively homogenous slopes and tephra properties. The sensitivity test revealed that slope, runoff, rainfall intensity, and volcanic ash thickness are strongly influence the erosion rate. This study also simplified the volcanic ash erosion model as a function of slope (S0), runoff (q), and rainfall (i) by assuming the value of (1-τc/τ0) is equal to 1. Further study using GIS tools is required for its application on several catchments with heterogeneous characteristics. Doi: 10.28991/CEJ-2024-010-07-02 Full Text: PDF

Scaling up time–geographic computation for movement interaction analysis

AbstractUnderstanding interactions through movement provides critical insights into urban dynamic, social networks, and wildlife behaviors. With widespread tracking of humans, vehicles, and animals, there is an abundance of large and high‐resolution movement data sets. However, there is a gap in efficient GIS tools for analyzing and contextualizing movement patterns using large movement datasets. In particular, tracing space–time interactions among a group of moving individuals is a computationally demanding task, which would uncover insights into collective behaviors across systems. This article develops a Spark‐based geo‐computational framework through the integration of Esri's ArcGIS GeoAnalytics Engine and Python to optimize the computation of time geography for scaling up movement interaction analysis. The computational framework is then tested using a case study on migratory turkey vultures with over 2 million GPS tracking points across 20 years. The outcomes indicate a drastic reduction in interaction detection time from 14 days to 6 hours, demonstrating a remarkable increase in computational efficiency. This work contributes to advancing GIS computational capabilities in movement analysis, highlighting the potential of GeoAnalytics Engine in processing large spatiotemporal datasets.

GeoGPT: An assistant for understanding and processing geospatial tasks

Decision-makers in GIS often need to combine multiple spatial algorithms and operations to solve geospatial tasks. While professionals can understand and solve these tasks by using GIS tools sequentially, developing workflows for various tasks can be inefficient, as even slight differences in tasks require corresponding adjustments in the workflow. Recently, large language models (e.g., ChatGPT) presented a strong performance in semantic understanding and reasoning. Especially, AutoGPT can further extend the capabilities of large language models (LLMs) by automatically reasoning and calling externally defined tools. Inspired by these studies, we attempt to increase the efficiency of developing workflows for handling geoprocessing tasks by integrating the semantic understanding ability inherent in LLMs with mature tools within the GIS community. Specifically, we develop a new framework called GeoGPT that can conduct geospatial data collection, processing, and analysis in an autonomous manner. In this framework, a LLM is used to understand the demands of users, and then think, plan, and execute defined GIS tools sequentially to output final effective results. In this process, our framework is user-friendly, accepting natural language instructions as input and adapting to various geospatial tasks, which can serve as an assistant for GIS professionals. A systemic evaluation and several cases, including geospatial data crawling, spatial query, facility siting, and mapping, validate the effectiveness of our framework. Though limited cases are presented in this paper, GeoGPT can be further extended to various tasks by equipping with more GIS tools, and we think the paradigm of “foundational plus professional” implied in GeoGPT provides an effective way to develop next-generation GIS in this era of large foundation models.

Digital Twin Smart City: Integrating IFC and CityGML with Semantic Graph for Advanced 3D City Model Visualization

The growing interest in building data management, especially the building information model (BIM), has significantly influenced urban management, materials supply chain analysis, documentation, and storage. However, the integration of BIM into 3D GIS tools is becoming more common, showing progress beyond the traditional problem. To address this, this study proposes data transformation methods involving mapping between three domains: industry foundation classes (IFC), city geometry markup language (CityGML), and web ontology framework (OWL)/resource description framework (RDF). Initially, IFC data are converted to CityGML format using the feature manipulation engine (FME) at CityGML standard’s levels of detail 4 (LOD4) to enhance BIM data interoperability. Subsequently, CityGML is converted to the OWL/RDF diagram format to validate the proposed BIM conversion process. To ensure integration between BIM and GIS, geometric data and information are visualized through Cesium Ion web services and Unreal Engine. Additionally, an RDF graph is applied to analyze the association between the semantic mapping of the CityGML standard, with Neo4j (a graph database management system) utilized for visualization. The study’s results demonstrate that the proposed data transformation methods significantly improve the interoperability and visualization of 3D city models, facilitating better urban management and planning.

Using GIS Tools and Remote Sensing Data to Assessment of Land Capability and Suitability for Agriculture in New Aswan Area, Aswan Governorate, Egypt

Using GIS Tools and Remote Sensing Data to Assessment of Land Capability and Suitability for Agriculture in New Aswan Area, Aswan Governorate, Egypt

Regional Differences in the Spread of Pneumonia in Russia: A Comparative Spatiotemporal Analysis of the Situation in 2017–2021

Introduction: Pneumonia remains a respiratory disease of concern that keeps influencing morbidity and mortality throughout the world in the 21st century. Increased incidence rates of pneumonia have been registered in Russia for a long time. In this regard, regional surveillance seems relevant across the country for a better understanding of recent spatial differences in the disease spread and their fluctuations. Objective: To carry out a spatiotemporal analysis of regional differences in pneumonia prevalence in the adult population of Russia in 2017–2021 with a focus on pre- and COVID-19 pandemic periods, given the Russian long-term dynamics for 2010–2022. Materials and methods: The study covers the years 2017–2021 with sufficient data on pneumonia prevalence collected. Static and dynamic parameters were calculated for the compared pre- and pandemic periods. A series of cartograms developed using GIS tools made it possible to visualize the information obtained and assess the spatiotemporal situation of the process under study. Results: The long-term dynamics of pneumonia prevalence rates in the adult population in Russia was examined with the regional trends in 2017–2021 assessed. In 2017–2019, they rose in most regions of Russia but the growth rate did not exceed 30 %. In 2019–2021, in the context of the COVID-19 pandemic, the pneumonia situation changed dramatically and the disease rates increased in most regions. A significant deterioration of the situation was observed in most of the European part of Russia with the growth rates ranging from 70 % to 90 %. The number of regions with a null increase in the pneumonia prevalence dropped from 25 to five. Conclusions: Changes in the regional differences in the disease prevalence in the adult population of Russia for 2017–2021 were assessed. The uneven interregional spread of pneumonia complicated during the pandemic compared with the pre-pandemic period. Increased growth rates of the disease prevalence of varying intensity were observed in 80 Russian regions.

Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine

The article offers a detailed expert analysis on handling spatial information of territorial communities amid administrative and land reforms. The authors have developed multiple methodological recommendations and justified the selection of efficient tools for contemporary GIS systems. It also delves into the essence of GIS technologies, the nuances of working with geodata, and provides a concise overview of the world's most prevalent GIS platforms. The paper outlines an algorithm for developing a land resource management strategy for communities in preparation for land reform. Through the analysis and visualization of spatial data, the paper highlights enhancements in economic valuation and the ability to pinpoint risks and infringements of property rights. The study selects the Cadastr.UA system on the Soft.Farm platform, developed by Ukrainian company Quart Soft, as a notably user-friendly and promising GIS for land accounting and auditing. Research based on the experimental practical application of most functions of GIS Cadastr.UA indicates that this system aligns well with the needs for land plot accounting and auditing within the framework of Ukraine's Public cadastral map. The paper details the practical implementation of GIS technologies, using Cadastr.UA as a case study, and illustrates how to employ selected GIS tools in various scenarios and tasks.

Sensitivity Analysis and GIS Tools for Groundwater Vulnerability Assessment. (Application in the Middle Chellif Plain, Algeria)

Contamination due to rapid urban development, industrialization, and agricultural sources is increasingly threatening the groundwater resources of the plioquaternary phreatic aquifer of the Middle Western Cheliff. An intrinsic vulnerability assessment was carried out based on the DRASTIC method on parameters involved in the vertical transfer of pollution from the soil surface. The vulnerability maps obtained showed a high extension of areas of medium vulnerability (54%). On the other hand, areas of low vulnerability occupied about 36%. The high and very high vulnerability was mainly related to low water depth values (8% and 2%, respectively). The results of a sensitivity analysis using the two tests—the single parameter sensitivity analysis and the map removal sensitivity analysis—show that every parameter is, without fail, required for the computation of the vulnerability index. The validation of the vulnerability map produced by the DRASTIC method confirmed the evolution of this sensitivity which decreases towards the S.W. of the plain with nitrate concentrations between 30 and 120 mg/L. Planners can use the produced risk maps as tools to make a preliminary choice of priority locations for various forms of environmental sustainability.

Use of GIS tools, enhanced by FFT filtering methods, to detect blurred craters in Synthetic Digital Elevation Models, to improve their location and morphological characterisation

Filtered Geomorphic Reference Models (FGRMs), extracted from High-Pass Filters based on the Fast Fourier Transform (HPF-FFT), provide a semi-automated and objective detection of a wide range of geoforms and geomorphic situations (flat areas, slopes, depressions, or valley bottoms). The method is sensitive enough to reveal numerous inflection points that enable the identification of subtle changes in relief polarity, resulting in accurate representations of real land depressions. The effectiveness of this method has been demonstrated in lunar landscapes, utilizing altimetry extracted from high-precision Planetary Digital Elevation Models (PDEMs) to construct crater inventories with well-defined FGRMs. However, when analysing lunar environments with closely-spaced geomorphic features, the FGRMs display blurring and generalization effects, reducing their capability to identify all existing crater depressions. This limitation controls the ability of FGRMs, to generate reliable crater inventories. This study examines such effects in three experiments. Using Synthetic Digital Relief Models (SDRMs) constructed by means of a MATLAB script two experiments are performed. In Experiment_1 different scenarios of proximity between aligned craters are analysed. The marks, or footprints, formed by craters of identical size and shape (i.e., circular bowl-shaped depressions with central peaks) are considered, resulting in simplified PDEMs. Various scenarios of crater centre separation (proximity) and the presence of internal features within craters are also analysed. Experiment_2 validates the method with different proximities, locations and crater sizes. Experiment_3 validates the approach in a sampled area of LRO lunar PDEM corresponding to Zelinskiy crater (Mare Ingenii area). To address these blurring effects, a hybrid methodology is employed, generating FGRMs extracted from HPF-FFT, in conjunction with other GIS and remote sensing tools, such as singular point zoning, aspect-slope zoning, and edge-limits zoning. As a result, the correspondence between the FGRMs and the synthetic forms is examined, aiding the comprehension of the graphical response provided by filtering in these cratered areas. The methodology demonstrates that FGRMs derived from HPF-FFT are sensitive to capturing connections between shapes as soon as the crater features start to merge, while blurring becomes evident when the craters are located at a proximity of <20 model units. Additionally, the results highlight the method's utility in accurately locating crater footprints and morphologically characterizing inner crater features, even when crater centres are closely spaced. This approach effectively mitigates blurring effects and enables the precise localization of crater marks and their internal features. The validations carried out in complex relief and high precise DEMs provide a use in real situation.

Forestry electric vehicle energy routing and mapping GIS tool

ABSTRACT In the United States, new laws and regulations in several states require increasing percentages of vehicles produced in the future to be zero emission to address climate-related issues. Manufacturers are producing more Electric Vehicles (EVs), but potential customers are hesitant to adopt EVs due to range anxiety. Log truck owners are particularly hesitant to invest in electric log trucks (ELTs) due to forest harvest operations remote nature. However, regenerative braking utilizing gravitational potential energy provides the opportunity to increase the range of ELTs. This manuscript presents the workflow for calculating and mapping energy transportation cost on an ELT using a GIS-enabled tool and demonstrates the tool’s applicability through a case study. The study area, the McDonald Dunn Research Forest, included 5,607 ha of forest stands partitioned into 357 harvest polygons averaging 15.7 ha, 326 harvest landings and 295 km of road. Using remotely sensed data from the study site, the tool digitalizes the wood supply chain and optimizes routing based on minimum energy expenditure, providing results such as trip energy cost, distance, and time. The results show the tools forest operations planning potential, applicability as a GIS navigation system, and provides EV buyers with a tool to make informed decisions when investing in technology that could combat climate-related issues. EV adoption will reduce reliance on fossil fuels and potentially ameliorate other environmental problems.

Flood Mapping of Federal Polytechnic Ekowe, Bayelsa State, Using Remote Sensing and GIS Tools

Flood Mapping of Federal Polytechnic Ekowe, Bayelsa State, Using Remote Sensing and GIS Tools

A comparative approach to GIS modelling of terrestrial mobility in archaeological sites. The iron age hillfort of Villasviejas del Tamuja as a study case

The archaeological analysis of Historical mobility is an increasingly studied topic thanks to new geographic information technologies. This paper proposes a modelling exercise of the spatial behaviour of a Second Iron Age community in the Middle Tagus Valley: the hillfort of Villasviejas del Tamuja (Botija, Cáceres). Based on our knowledge of the configuration of the site and the surrounding settlements, we propose a heuristic use of a series of GIS tools to understand how the spatial relationship between both elements was structured. More specifically, we compare the results obtained with different calculation methods that combine two essential variables to address this issue: mobility and visibility relations. On the one hand, we evaluate the results with the application of an already developed methodology: the MADO analysis. On the other hand, we present a complementary procedure for the calculation of Least Cost Paths (LCP), considering the visibility as a key element in the mobility. The methodology uses the same data, in a paradigmatic case study for comparing results. The differences obtained through the use of different tools are thus evaluated in order to weigh up the additional or complementary knowledge that they can provide us with to investigate archaeological research questions such as the defensive architecture of the hillfort or the distribution of other nearby settlements.

GOVERNANCE AND WATER LANDSCAPE IN KHULNA CITY: PAST, PRESENT AND FUTURE DIRECTION

This paper examines the water landscape in Khulna City from two perspectives: household water supply and the importance of surface water in the city’s ecology. The authors seek to explore whether the current water supply system can achieve goal 6.1 of the Sustainable Development Goals (Universal and Equitable access to safe and affordable water for all), and the drivers of surface water deterioration and the city’s ecological changes. Both the primary and secondary materials have been consulted. Analysis of water infrastructure and water body encroachments have been explored using remote sensing and GIS tools. Investigation of the water supply networks in Khulna city shows a clear geographical division, where the planned residential and affluent areas enjoy most of the water network coverage. Affluent areas with piped networks and other sources consumed much more water than other parts of the city. Map-based and observational analysis of the Mayur River and Nirala Canal asserts that the water bodies have been encroached severely. About 65% of the total area of the Nirala canal has been encroached on by the government as well as private organizations and individuals. Businesses on and around the Mayur River are booming. As a result, rivers and canals are unable to maintain water flows resulting in higher intensity of water logging and other ecological disruptions. Several recommendations including supply-based water management, hierarchical water tariffs, increasing water supply coverage, the introduction of non-conflicting activities around water bodies and inter-organizational collaboration have been proposed to make the city resilient against the adverse impacts of climate and man-made disruptions.

Evaluation of land suitability areas for irrigation using GIS and AHP-based tools in the case of Zenti River Catchment, Gofa district, Ethiopia

Evaluation of land suitability areas for irrigation using GIS and AHP-based tools in the case of Zenti River Catchment, Gofa district, Ethiopia