Geographic Information System Analysis Research Articles

Geopatial Technologies in Civil Engineering : A Critical Literature

This study investigates the role of geospatial technologies in enhancing the efficiency and effectiveness of civil engineering projects. Geospatial technologies, including Geographic Information Systems (GIS), remote sensing, and spatial analysis, have revolutionized the field of civil engineering by providing critical tools for planning, design, construction, and management of infrastructure projects. The integration of these technologies enables accurate terrain mapping, real-time monitoring, and data-driven decision-making, which are crucial for ensuring the safety, sustainability, and resilience of modern infrastructure. This research aims to explore the applications of geospatial technologies in various civil engineering projects, including highway planning, urban development, and environmental monitoring. The study also examines the potential benefits and limitations of these technologies and provides recommendations for their effective integration into civil engineering practices. By understanding the impact of geospatial technologies on civil engineering projects, this research aims to contribute to the development of more efficient, sustainable, and resilient infrastructure that supports the needs of modern society.

Automated GIS-based decision tool for rehabilitation of a drinking water infrastructure in Tlemcen, Algeria

Water resource management relies heavily on the utilization of decision-making systems to guide the strategic rehabilitation and renovation of infrastructure within water distribution networks (WDNs). This study aims to develop and apply a scripting tool in ArcGIS for decision-making in WDN. It combines a collection of decision support systems, including Geographic Information Systems (GIS) and multi-criteria analysis, for infrastructure renovation and rehabilitation. The research is divided into two main sections. The first focuses on creating and implementing the analytic hierarchy process tool in ArcGIS, while the second discusses its application in the study area, which is the drinking water distribution network of an urban area in Tlemcen, located in the Northwest of Algeria. The study’s results reveal that 25% of the network is in critical condition and require immediate rehabilitation. Sixty-two percentage of the network is classified as moderately urgent, indicating a pressing but less immediate need for intervention. Finally, the remaining 13% of the network requires attention over a longer timeframe for rehabilitation. The main criteria influencing pipe prioritization are material (26% of total weight), laying date (26% of total weight), and pressure (20% of total weight). This developed tool can be easily adapted and applied by engineers and water management officers. It serves as a guide for decision-makers and planners in urban water management in Tlemcen and can be replicated and applied to other areas worldwide.

A method for hierarchical weighted fitting of regular grid DSM with discrete points

Abstract. A Digital Surface Model (DSM) is a crucial spatial geographic information data used to describe the shape of the earth’s surface in Geographic Information Systems (GIS). DSM is the core data used in terrain analysis in GIS. A regular grid DSM is generally generated by interpolating a large number of discrete point clouds. This paper proposes a method of using a hierarchical weighted strategy to fit a regular grid DSM with discrete points. This method uses a pyramid hierarchical strategy to refine the target regular grid from one grid with finer parameters of 3*3, until the nth level (the interval of the grid is equal to the expected interval), and then gradually places the discrete point cloud into the corresponding grid by weighted averaging, and uses the result of this level as the initial value of the next level. This algorithm can avoid the problem of low efficiency in retrieving a large number of discrete point clouds, and the indirect interpolation method not considering the contribution of distant neighboring point clouds. The operation of point cloud data is a stream operation, which does not require consideration of the topological information of point clouds, and has simple operation and no additional memory consumption. It is especially suitable for the production of regular grid DSM with massive point clouds. To verify the effectiveness of this method, the article selected six typical terrain data such as high mountains, mountains, hills, plains, urban areas, and lakes for experiments. The results show that compared with the construct-TIN method for producing DSM, this method has very good processing accuracy and processing efficiency.

Mapping soil trace metal distribution using remote sensing and multivariate analysis.

Trace metal soil contamination poses significant risks to human health and ecosystems, necessitating thorough investigation and management strategies. Researchers have increasingly utilized advanced techniques like remote sensing (RS), geographic information systems (GIS), geostatistical analysis, and multivariate analysis to address this issue. RS tools play a crucial role in collecting spectral data aiding in the analysis of trace metal distribution in soil. Spectroscopy offers an effective understanding of environmental contamination by analyzing trace metal distribution in soil. The spatial distribution of trace metals in soil has been a key focus of these studies, with factors influencing this distribution identified as soil type, pH levels, organic matter content, land use patterns, and concentrations of trace metals. While progress has been made, further research is needed to fully recognize the potential of integrated geospatial imaging spectroscopy and multivariate statistical analysis for assessing trace metal distribution in soils. Future directions include mapping multivariate results in GIS, identifying specific anthropogenic sources, analyzing temporal trends, and exploring alternative multivariate analysis tools. In conclusion, this review highlights the significance of integrated GIS and multivariate analysis in addressing trace metal contamination in soils, advocating for continued research to enhance assessment and management strategies.

Unveiling spatial insights: navigating the parameters of dynamic Geographic Information Systems (GIS) analysis

In today's rapidly evolving landscape of Geographic Information Systems (GIS), understanding the intricate parameters that govern GIS analysis is paramount. This title encapsulates the essence of delving into the multifaceted dimensions of GIS, where a myriad of factors converges to shape the process and outcomes of spatial analysis. From the selection of input data and spatial layers to the fine-tuning of analytical techniques and model parameters, every step in GIS analysis is governed by a set of parameters that influence the accuracy, reliability, and relevance of the results. The title beckons researchers, practitioners, and enthusiasts alike to embark on a journey of exploration, unraveling the complexities of GIS analysis and its underlying parameters. It speaks to the dynamic nature of GIS, where the interplay of spatial data, computational algorithms, and user-defined parameters creates a rich tapestry of insights and discoveries. Whether mapping urban growth patterns, assessing natural resource availability, or modeling environmental change, understanding the parameters of GIS analysis is essential for unlocking the full potential of spatial data and informing decision-making processes. Moreover, the title hints at the transformative power of GIS as a tool for understanding and addressing complex spatial phenomena. By scrutinizing the parameters of GIS analysis, researchers can gain deeper insights into the underlying processes driving spatial patterns and trends. They can identify optimal parameter settings, refine analytical workflows, and enhance the accuracy and precision of spatial models and predictions. In essence, "Exploring the Parameters: Understanding the Dynamics of GIS Analysis" encapsulates the essence of GIS as a dynamic and evolving field, where the exploration of parameters serves as a gateway to unlocking the full potential of spatial analysis and harnessing the power of geography to address real-world challenges and opportunities.

Unlocking Geographical Insights: Exploring the Application of Modern Tools and Techniques in Geographic Studies

Abstract: This research paper explores the transformative impact of modern tools and techniques on geographical studies. Focusing on innovations such as Geographic Information Systems (GIS), remote sensing, and spatial analysis, the paper investigates how these technologies have revolutionized the field of geography. The paper examines the diverse applications of modern tools in addressing key geographical challenges, including land use planning, environmental monitoring, and disaster management. Furthermore, it explores the integration of emerging technologies such as artificial intelligence, machine learning, and augmented reality, and their potential to further enhance geographical research and analysis. By highlighting the benefits, limitations, and future directions of modern tools and techniques in geographical studies, this paper contributes to a deeper understanding of their role in advancing knowledge and informing decision-making in a rapidly changing world.

Site selection for nature-based solutions for stormwater management in urban areas: An approach combining GIS and multi-criteria analysis

In recent years, particularly following the definition of the UN Sustainable Development Goals (SDGs) for 2030, Nature-Based Solutions (NBS) have gained considerable attention, capturing the interest of both the scientific community and policymakers committed to addressing urban environmental issues. However, the need for studies to guide decision-makers in identifying suitable locations for NBS implementation within urban stormwater management is evident. To address this gap, the present study employs a methodological approach grounded in multi-criteria analysis integrated with Geographic Information Systems (GIS) to identify areas with potential for NBS implementation. In this process, ten NBS were proposed and tested in the drainage area of a shallow tropical urban lake in Londrina, southern Brazil. Additionally, the study investigates areas hosting lower-income populations, a relevant aspect for public managers given the diverse economic subsidies required to implement NBS. Furthermore, the study incorporates a preliminary analysis that evaluates the potential ecosystem benefits to determine the most suitable NBS for a specific site. The result shows that all the ten analyzed NBS were deemed suitable for the study area. Rain barrels had the highest percentage coverage in the study area (37.1%), followed by tree pits (27.9%), and rain gardens (25.4%). Despite having the highest distribution in the basin area, rain barrels exhibited only moderate ecosystem benefits, prompting the prioritization of other NBS with more significant ecological advantages in the final integrated map. In summary, the methodology proposed showed to be a robust approach to selecting optimal solutions in densely populated urban areas.

Revisiting tornado watch #211 - a spatial analysis of the May 31, 1985 tornadoes using present-day data for the state of Pennsylvania

On the evening of 31 May 1985, a devastating and deadly tornado outbreak impacted Ohio, Pennsylvania, New York, and Ontario, Canada. A total of 41 tornadoes occurred resulting in 88 fatalities: the deadliest tornado outbreak of the 1980s. Pennsylvania experienced the greatest number of tornadoes with 21 affecting the Commonwealth, causing 65 fatalities. Despite its severity, Pennsylvania’s deadliest tornado outbreak has not been spatially analyzed in academic literature. With the outbreak occurring nearly 40 years ago, one must consider the potential impacts today in comparison to the 1985 time-period. Has the natural and built landscape changed to the extent that the population would be further impacted both directly and indirectly? To assist in answering this question, this study performs a Geographic Information System (GIS) analysis of Pennsylvania’s historical and present-day land cover, census, and building data in locations impacted by the 1985 tornadoes. Data between the two time periods is compared and analyzed to quantify changes since 1985 to estimate if the impacts would be lesser or greater in relation to the expanding bull’s eye effect. This includes estimating the number of fatalities that would occur in the present-day.

Integration of Geographic Information Systems and Spatial Data Analysis in Location Decision Making for Manufacturing Industries

Integration of Geographic Information Systems and Spatial Data Analysis in Location Decision Making for Manufacturing Industries

Spatiotemporal Land Use/Land Cover Changes and Impact on Urban Thermal Environments: Analyzing Cool Island Intensity Variations

This study pioneers the comprehensive evaluation of the spatiotemporal evolution of land use/land cover (LULC) in Hangzhou city, introducing the novel water body shape index (WBSI) to analyze its seasonal impacts on the urban thermal environment and urban cool island (UCI) effects, uncovering distinct patterns of thermal regulation. It particularly investigates how distance gradients and the water body shape index (WBSI) influence land surface temperature (LST) in the urban core. The region’s climate, featuring hot summers and cold winters, highlights significant seasonal LST variations. Addressing a gap in existing UCI research, the analysis extends beyond the typical large-scale planning focus to include small-scale, high-resolution aspects. Employing remote sensing and geographic information system (GIS) analysis techniques, this study analyzes the seasonal dynamics in Hangzhou’s central urban area. High-resolution LST data, obtained through single-channel inversion and resolution enhancement algorithms, are crucial to this analysis. This study employs the maximum likelihood classification method to analyze land use and land cover changes from 1990 to 2020. This analysis reveals potential drivers of urban thermal environment changes, such as the expansion of residential and commercial areas and the reduction in green spaces. Different regions in LST data are delineated to assess the cool island effect, and the complexity of water body boundaries is quantified using the water body shape index. Spatial and temporal patterns of LST changes are investigated using multivariate regression and time-series analysis models. We identified significant changes in LULC over the past 30 years in Hangzhou, closely correlating with a continuous rise in LST. This observation underscores a clear finding: the strategic importance of blue–green infrastructure in mitigating urban heat, a novel insight that extends the current understanding of urban thermal dynamics. A clear and novel finding of this study is that the intensity of the cool island effect from large water bodies not only diminishes with distance but is intricately influenced by the complexity of their shapes, as quantified by the WBSI, whereas the complexity of their boundaries enhances this effect. Additionally, the regulatory role of the cool island effect is observed to vary seasonally, being most pronounced in summer and less so in autumn and winter, thereby demonstrating a positive impact. In conclusion, our findings innovatively highlight how the specific shapes of water bodies, quantified through the water body shape index (WBSI), emerge as critical, yet previously underappreciated, drivers in modulating the urban thermal environment. This underscores a new avenue for urban planning, advocating for the strategic design of water bodies within urban landscapes. It also finds that spatial factors and seasonal variations significantly affect the intensity of the cool island effect. These findings offer valuable evidence for urban planning and climate change adaptation, emphasizing balancing natural elements with the built environment in urban design.

Study on the Influence of Land Use Change on Carbon Emissions Using System Modeling under the Framework of Dual Carbon Goals

At the crucial period of addressing climate change, especially to the carbonization of land use change, it is vital that relevant actions are taken to enable two ambitious dual-carbon goals, namely, ensuring that carbon emissions peak before 2030 and achieving carbon neutrality before 2060. This research investigates the impacts of land use changes on carbon emissions using a novel approach that integrates Light Detection and Ranging (LiDAR) with Geographic Information System (GIS). This approach is innovative due to its high quality three-dimensional representation to quantified exact carbon stock and forest emissions occurring due to specific land-use change. Therefore, through actual LiDAR, this research helps demarcate the pattern emitting different land-use measures, including deforestation, urban programs, agricultural differences, and forest and land changes, over historical change records and verified carbonization formulas. Similar qualitative levels between LiDAR and GIS analysis help determine the varying degrees of carbonization occurring due to enhanced deforestation, urban additions, and agricultural contributions while reporting the possible procedural carbons acquired during reforestation and other measurements. The results helped clarify that the most distinct level of land utilization shows the least level of carbon sent into the air. Therefore, the implication is that strategic land use measures and better working conditions can curb carbon indications. These signals support land-use policy and preparedness goals in a low carbon level. This study creates valuable records for the land utilization and cartograph, created through the power of LiDAR and GIS analysis.

Analyzing Air Pollution in Urban Delhi: A Quantitative Assessment of Particulate Matter (PM) Concentrations

Air pollution poses significant challenges to urban environments, with particulate matter (PM) concentrations being a major concern due to their adverse effects on public health and the environment. This research paper aims to quantitatively assess PM concentrations in urban Delhi, focusing on spatial, temporal, and seasonal variations across diverse urban microenvironments. The research design involved mobile air quality monitoring using real-time PM sensors mounted on a vehicle, coupled with Geographic Information System (GIS) analysis to map pollution hotspots and assess correlations with urban features. The key findings of the study reveal significant spatial variability in PM concentrations, with industrial zones and busy intersections emerging as hotspots for pollution. Seasonal variations in PM levels, with elevated concentrations during winter months and lower levels during the monsoon season, underscore the influence of meteorological factors on air quality dynamics. The study also identifies correlations between PM concentrations and respiratory disease cases, highlighting the adverse health effects of air pollution. The implications of these findings extend to air quality management strategies and public health interventions, emphasizing the need for targeted measures to mitigate pollution levels and protect public health in urban environments.

Assessment of the locational potential of floating offshore wind energy in South Africa

Expanding floating wind into new markets could support emission reduction targets in several national contexts. It furthers the need for adequate assessments to gain a full understanding of the technology’s potential in future markets. South Africa is a prime case study as it has seen limited industry and policy developments despite its huge technical potential for floating offshore wind (FOW). This paper assessed the locational potential of floating wind in South Africa through a three-phased approach that evaluated the key technical drivers/barriers of the technology, conducted a Geographic Information System analysis (GIS) using ArcMap 10.8 to exclude unsuitable sites based on a predetermined exclusion criteria (including marine protected zones, underwater cables, major oil and gas deposits, etc.), and estimated the total harvestable capacity in the feasible sites. The study found that 2% (246,105.4 km2) of South Africa’s entire Exclusive Economic Zone (EEZ) is suitable for hosting floating wind turbines, with a potential to generate a maximum of 142.61 GW of floating wind power. Although the Western Cape province holds the highest potential (80.52 GW) for floating wind in the country, the Eastern Cape region, with a locational potential of 20.04 GW, is considered most suitable for early-stage developments due to the availability of grid connection points, limited marine traffic, and proximity to appropriate port facilities. Future work can conduct techno-economic assessments to evaluate the technical and economic implications of developing floating wind in distinct sites in the country’s EEZ.

Enhancing Sustainable Mobility: Evaluating New Bicycle and Pedestrian Links to Car-Oriented Industrial Parks with ARAS-G MCDM Approach

The aim of this research is to address the challenge of transforming car-oriented industrial parks into pedestrian- and bicycle-friendly environments. Through the implementation of a multi-criteria decision-making (MCDM) approach, the study aims to evaluate alternative pathway connections and assess their potential impact on bicycle and pedestrian traffic volumes. By enhancing the connectivity of the cycling pathway network, the research seeks to demonstrate the potential for substantial increases in cycling and walking within industrial zones. This research leverages a multi-criteria decision-making framework, specifically the ARAS-G method, and integrates geographic information system analysis alongside Python scripting to project future bicycle usage and assess alternative pathway connections. The study underscores the potential for substantial increases in cycling and walking by augmenting the connectivity of the cycling pathway network. The findings hold practical significance for urban planners and industrial zone developers, advocating a holistic approach to sustainable transportation. The research contributes a comprehensive set of criteria encompassing connectivity, safety, accessibility, efficiency, integration within the urban fabric, and cost-effectiveness to evaluate sustainability and prioritize actions and measures for reestablishing industrial zones as bicycle-friendly spaces.

Modeling on comprehensive evaluation of groundwater quality status using Geographic Information System (GIS) and Water Quality Index (WQI): a case study of Bahir Dar City, Amhara, Ethiopia

Abstract Groundwater is the most important natural resource, and many people throughout the world rely on it for drinking, particularly in rural areas. The present study was carried out to assess the status of groundwater quality and to check its suitability for domestic purposes in urban centres of Bahir Dar City, Ethiopia. Twelve shallow wells were selected for sampling. The sampled water was taken during the dry and summer seasons of the year 2019/2020. pH, turbidity, EC, TDS, chloride (Cl−), nitrate (NO3-), phosphate (PO4-3), total hardness, and Escherichia coli were measured for the suitability analysis. Comparison of measured results with that of WHO and Ethiopian drinking water quality standards wasdone. Moreover, Geographic Information System (GIS) and Water Quality Index (WQI) data analysis techniques were applied in order to investigate the groundwater quality. The spatial distribution map showed that the city's core area had the poorest groundwater quality status. The WQI result obtained from the analysis showed that 41.67, 33.33, and 25% of the sampled groundwater has low, extremely poor, and unsafe quality for drinking purposes, respectively. The present study revealed that anthropogenic activities have a great impact on the quality of groundwater in the area, necessitating immediate mitigating actions.

Walk further and access more! Exploring the 15-minute city concept in Oslo, Norway

The 15-minute city theory has recently become a popular paradigm in urban development. It claims that everyone should have access to the essential services, facilities and green spaces within a 15-minute walk. This article tests this concept in Oslo, Norway using a mixed-methods approach, based on a Geographical Information Systems (GIS) analysis of accessibility, review of relevant plans, interviews with planners and a case study of the Hovinbyen area. The objective was to find out to what extent Oslo is a 15-minute city, and discuss how this concept can be integrated in urban planning strategies more generally. The study shows that the central part of Oslo is already a 15-minute city, and that several areas are transforming in this direction. However, many suburban neighborhoods have low accessibility scores, and, according to the plans, will likely not change much in the future. This article argues that the 15-minute city concept cannot serve as the main development strategy, but such an analysis can be useful as a diagnostic study or to assist planning in rapidly changing areas or city extensions. The concept can therefore be considered as a flexible tool to support other planning strategies that share the same goals and ambitions. Any interventions that such accessibility analyses suggest should be contextualized and developed in combination with other qualitative assessments and in partnership with local communities.

Spatial Planning Policy Analysis and Participation Support Society Towards Environmental Sustainability

The research is purpose to find out implementation spatial planning policies on Bekasi city for stainable environmental management? Analytical methods used are: 1) Geo-physics analysis of land suitability analysis, 2) physical analysis; 3) Analysis of environmental management, 4) Analysis of socio-economic conditions, and 5) Analysis of Geographic Information System (GIS). The results obtained that spatial planning and environmental carrying capacity can be concluded that to meet the needs of diverse development needs to develop a spatial pattern of land use, coordinate, procedures for water and other resources in a unified a dynamic environment. To meet the needs of diverse development needs to develop a spatial pattern coordinate system guana land, procedures for water and other resources in a unified order dynamic environment. For that layout needs to be managed by an integrated pattern through a regional approach with respect to site natural environment, socio-cultural environment, and the artificial environment in accordance with its development. Good city spatial structure with more increased public participation in city layout is expected to be better. The parties involved in these activities the city department of administration, the whole society. There is a direct influence on the city hall community participation in maintaining a healthy environment, so if you want to increase public participation in maintaining a healthy environment can be done by increasing the city spatial planning. Knowledge to community environmental management in maintaining a healthy environment, can be done by improving environmental management Knowledge community.

Delineation of Vulnerable Areas Affected by the Eruption of Mount Agung, Bali

Vulnerability is a condition of a community or society that causes the inability to face the threat of disaster. Geographic information systems (GIS) have become essential tools in evaluating natural hazards and risks which is an aspect to define vulnerability of the volcano eruption-affected area. Based on activity of volcano, it is necessary to delineate the vulnerability of areas affected by the eruption of Mount Agung by integrating the Mount Agung Area Network Map and Geological Map with physical vulnerability data and social vulnerability. This research using processing methods and spatial analysis of Geographic Information Systems (GIS) and remote sensing methods. Geographic Information System (GIS) is used to create vulnerability maps using scoring, weighting, and overlay methods. The data used for making the vulnerability map include administrative boundaries, DEM (Digital Elevation Model), secondary data from the BPS 2020 Karangasem Regencyt in Figures, geological maps, settlement data and land cover maps. The results based on these data show the number of areas affected by the eruption of Mount Agung, the data states that the data area with low vulnerability has an area of 0.001490 Ha. Medium vulnerability data has an eruption affected area of 47.024493897 Ha. While the high vulnerability has an affected area of 36.878843877 Ha. Differences in the level of vulnerability are influenced by social vulnerability, physical vulnerability, and environmental vulnerability.Keywords: Delineation, Eruption, GIS, Mount Agung, Vulnerability

The Application of Geographic Information System in Analysing the Voting Patterns among Dayak Voters in the Sarawak State Elections of 2016 and 2021

Geographic information system (GIS) and election-related research focuses on the geographical characteristics of election boundaries, the election information management system and the application of GIS analysis to election boundaries. This article aims to acquire a deeper understanding of the issues affecting Dayak voters during the state elections of 2016 and 2021, geographically. This study employs three spatial analyses: Thematic Map-Density, Spatial Autocorrelation Moran’s I Index and Hot Spot Analysis (Getis-Ord Gi*). In select constituencies with a Dayak-majority, interviews and observations supplemented the spatial data. This article examines Dayak-majority constituencies’ geographical distribution and spatial concentration in the 2016 and 2021 elections. It demonstrates that there are significant differences in the density of voter participation, majorities obtained by candidates, and total votes cast by the electorate across the state in both state elections, confirming the assertion made by researchers of electoral politics in Sarawak that election issues are primarily location-specific and that understanding the problems faced by communities at the local level is essential. It is anticipated that the outcome of this study will aid in providing a spatial overview and projection of state election results and in strategising the future management of state elections.

A Single Data Extraction Algorithm for Oblique Photographic Data Based on the U-Net

In the automated modeling generated by oblique photography, various terrains cannot be physically distinguished individually within the triangulated irregular network (TIN). To utilize the data representing individual features, such as a single building, a process of building monomer construction is required to identify and extract these distinct parts. This approach aids subsequent analyses by focusing on specific entities, mitigating interference from complex scenes. A deep convolutional neural network is constructed, combining U-Net and ResNeXt architectures. The network takes as input both digital orthophoto map (DOM) and oblique photography data, effectively extracting the polygonal footprints of buildings. Extraction accuracy among different algorithms is compared, with results indicating that the ResNeXt-based network achieves the highest intersection over union (IOU) for building segmentation, reaching 0.8255. The proposed “dynamic virtual monomer” technique binds the extracted vector footprints dynamically to the original oblique photography surface through rendering. This enables the selective representation and querying of individual buildings. Empirical evidence demonstrates the effectiveness of this technique in interactive queries and spatial analysis. The high level of automation and excellent accuracy of this method can further advance the application of oblique photography data in 3D urban modeling and geographic information system (GIS) analysis.