Integration Of Geographic Information System Research Articles

Investigation of changes in land use/land cover using principal component analysis and supervised classification from operational land imager satellite data: a case study of under developed regions, Pakistan

Monitoring and understanding Land Use/Land Cover (LU/LC) is critical for sustainable development, as it can impact various environmental, social, and economic systems. For example, deforestation and land degradation can lead to soil erosion, loss of biodiversity, and greenhouse gas emissions, affecting the quality of soil, air, and water resources. The present research examined changes in (LU/LC) within the underdeveloped regions of Balochistan and Sindh provinces, which are situated in Pakistan. In order to monitor temporal variations of LU/LC, we employed Geographic Information System (GIS) technique, to conduct an analysis of satellite imagery obtained from the Landsat 8 Operational Land Imager (OLI) during the time period spanning from 2013 to 2023. In order to obtain an accurate LU/LC classification, we used principal component analysis (PCA) and a supervised classification approach using the maximum likelihood algorithm (MLC). According to the results of our study, there was a decrease in the extent of water bodies (− 593.24 km2) and vegetation (− 68.50 km2) by − 3.43% and − 0.40% respectively. In contrast, the area occupied by settlements in the investigated region had a 2.23% rise, reaching a total of 385.66 square kilometers. Similarly, the extent of barren land also expanded by 1.60%, encompassing a total area of 276.04 square kilometers, during the course of the last decade. The overall accuracy (94.25% and 95.75%) and K value (91.75% and 93.50%) were achieved during the year 2013 and 2023 respectively. The enhancement of agricultural output in Pakistan is of utmost importance in order to improve the income of farmers, mitigate food scarcity, stimulate economic growth, and facilitate the expansion of exports. To enhance agricultural productivity, it is recommended that the government undertake targeted initiatives that aimed at enhancing water infrastructure and optimizing land use to foster a sustainable ecological framework. Integrating the sustainable ecological framework provides a foundation for informed decision-making and effective resource management. By identifying areas of urban expansion, agricultural intensification, or alterations in natural LU/LC, stakeholders can design targeted conservation strategies, mitigating potential environmental degradation and promoting biodiversity conservation. In conclusion, the integration of GIS and Remote Sensing (RS) may effectively facilitate the monitoring of land use patterns over a period of time. This combined approach offers valuable insights and recommendations for the judicious and optimal management of land resources, as well as informing policy decisions.

Groundwater flow simulation for artificial recharge: a GIS, remote sensing, and MODFLOW integration

Abstract Groundwater (GW) emerges as a sustainable resource to meet water demand, yet current GW reservoirs fall short of projected population needs. Artificial GW recharge, bolstered by Geographical Information System (GIS) and Remote Sensing (RS) technologies, stands out as a pivotal solution. Examining Aurangabad district in Maharashtra, India the study uncovers distinct challenges: Aurangabad faces escalating water demand due to population growth, leading to GW over-exploitation. Leveraging hydrogeological parameters, rainfall analysis, and GW availability, the study proposes tailored GW recharge techniques. Utilizing MODFLOW simulation, the study explores diverse recharge rates and existing GW availability, showcasing promising results. Integration of stream augmentation, bladder pillow tank methods, and dug well recharge is examined via GIS and RS techniques. Simulation outcomes project significant GW level increases (11.55–23.70 m) with varying recharge rates, effectively meeting region-specific water demand projections. The findings underscore the imperative of sustainable water management practices and technological advancements in addressing water scarcity crises.

Assessing flood susceptibility in the Godavari River Basin, Bhadrachalam Region, Sothern India: A GIS-AHP Multi-Criteria Approach

Floods, as recurrent natural disasters, exert significant impacts on both the environment and human settlements. This study focuses on evaluating the flood susceptibility of the Bhadradri Kothagudem district in Telangana, situated within the Godavari River Basin. The research integrates Geographic Information System (GIS) and the Analytic Hierarchy Process (AHP) in a multi-criteria approach to analyze and map flood susceptibility. Landsat-8 data, digital elevation model data and rainfall serve as inputs for assessing the flood susceptibility. The study considers various topographical features such as elevation, slope, roughness, contours and aspect, along with factors like land use land cover, flow accumulation, stream direction, stream network, drainage density, flow length, distance from the river, soil, normalized difference vegetation index and topographic wetness index. These variables are rescaled on a scale of one to five and combined to generate a comprehensive flood susceptibility map of the Kothagudem district using GIS. The AHP is implemented through GIS, assigning weightages on a scale of one to five based on the priority of spatial classes within thematic maps. The flood susceptibility map is produced on a scale of five, designating scale class five as of very high susceptibility and scale class one as low. Scale classes two, three and four represent intermediate levels of susceptibility. The resulting flood susceptibility maps offer valuable insights for disaster preparedness, risk mitigation and land-use planning in the Kothagudem district. The integration of GIS and AHP provides a robust methodology for assessing and visualizing flood susceptibility, enabling informed decision-making for resilient and sustainable development in flood-prone regions.

Asset Information Model Management-Based GIS/BIM Integration in Facility Management Contract

Achieving efficiency success status inside an organization’s built environment and obtaining a positive return on investments need robust and comprehensive asset management and maintenance processes based on the efficiency of contract information documents within the built asset lifecycle. This paper aims to highlight the appropriate interactive approach for construction projects to build the information flow scope of asset facility management contracts based on GIS (Geographical Information System) and BIM (Building Information Modeling) integration processes and sustainability standards, and project as-built contractual documents to support owners and stakeholders with the intent of improving asset management processes. Expert interviews and contract information flow types in several facility management processes conducted in both local and international facility management organizations were used to assist the information flow scope method. The study classified and built significant integrated information and data flow models for a case study to serve as contract guidelines, including efficiency performance measures and indicators for monitoring procedures, technical evaluation, and financial issues in order to provide high-performance service quality in facility management applications.

Geographic Information System (GIS) Application in Soil Fertility Management: A Review

As the global population expected to reach 10 billion by 2050 and arable land decreases, innovative soil management strategies are required to maximize agricultural productivity while preserving natural resources. GIS, as a powerful technology, offers a comprehensive solution by enabling the collection, storage, analysis, and visualization of spatial data for agricultural purposes. By integrating GIS with sensors, communication technologies, and data analytics, precision agriculture is possible, allowing for efficient use of agricultural inputs and reduced environmental impact. GIS technology facilitates the simulation and modeling of biological ecosystems, providing valuable insights for sustainable soil management. It has diverse applications in agriculture, ranging from soil nutrient mapping to yield estimations and runoff detection. GIS works by overlaying various layers of information onto digital maps, allowing for the identification of relationships and patterns that are crucial for optimizing soil fertility. Detailed maps created through GIS highlight the distribution of soil nutrients, pH levels, and moisture content, enabling informed decision-making on fertilizer use, irrigation techniques, and land management practices. By harnessing the power of GIS, farmers and land managers can make data-driven decisions that maximize agricultural productivity, conserve resources, and protect soil health for future generations. The integration of GIS with other technologies further enhances its effectiveness in soil fertility management. Overall, GIS is a valuable tool for understanding and managing soil fertility, contributing to sustainable agriculture and food security.

Navigating Aged Care Services with GIS: Trends, Developments, and Future Directions

BackgroundWith the growing challenge of an aging population, emerging technologies are increasingly being integrated into the production, organization, and delivery of aged care services. Geographic Information System (GIS), a computer-based tool for spatial information analysis and processing, has made significant strides in the allocation of care recources and service delivery for older adults, a notably vulnerable group. Despite its growing importance, cross-disciplinary literature reviews on this theme are scare. This scoping review was conducted to encapsulate the advancements and discern the future trajectory of GIS applications in aged care services.MethodsA comprehensive search across nine databases yielded 5941 articles. Adhering to specific inclusion and exclusion criteria, 61 articles were selected for a detailed analysis.ResultsThe 61 articles span from 2003 to 2022, with a notable increase in publications since 2018, comprising 41 articles (67% of the total) published between 2018-2022. Developed countries contributed 66% of the papers, with 45% focusing on accessibility issues. In the domain of aged care services, GIS has been predominantly utilized for model construction, mapping, and site selection, with a growing emphasis on addressing the unique needs of different subgroups of older adults.ConclusionThe past two decades have seen substantial growth in the application of GIS in aged care services, reflecting its increasing importance in this field. This scoping review not only charts the historical development of GIS applications in aged care services but also underscores the need for innovative research approaches. Future directions should emphasize the integration of GIS with diverse methodologies to address the heterogeneous needs of older adults and improve the overall delivery of aged care services. Such advancements in GIS applications have the potential to significantly enhance the efficiency, accessibility, and quality of care for the aging population.

Geographical Information System: Strengthening the Delivery of Medical Education

ABSTRACT In the field of medical education, geographic information system (GIS) can contribute in several ways to strengthen the process of delivery of education. As medical institutions plan to integrate GIS in the delivery of medical education, there can be some challenges that must be given due attention to optimize the benefits. In conclusion, the integration of GIS in medical education can expose medical students to enriching learning experiences. Acknowledging the importance and merits of GIS, there is an immense need to explore the possibility and introduce it in medical education to benefit medical students and widen their perspective on health care.

IMPLEMENTATION OF A GEOGRAPHIC INFORMATION SYSTEM IN MONITORING THE IMPLEMENTATION OF HOUSING CONSTRUCTION

Building the 864-unit housing complex was a significant construction undertaking. Within an implementation period of 18 months and a project area of approximately 34 hectares, this project demanded efficient management to control the time and budget that had been set. To achieve this goal, it is necessary to implement effective planning, organization, management and resource allocation processes. This process aims to break down project management into simpler tasks or activities, provide time estimates for each task, and continuously monitor their progress. Although conventional planning tools such as Primavera and Msproject can provide a time representation of the tasks to be performed, they are not yet able to provide spatial or geographic monitoring of these tasks within the scope of the project. By integrating Geographic Information Systems (GIS), this project can gain additional benefits. GIS allows identifying data about the progress of construction tasks, and then presenting them in the form of maps. This not only visualizes overall progress graphically and geographically, but also makes it easy to extract useful summaries to support project decision making. With GIS, construction project monitoring not only becomes more efficient, but also more up-to-date and relevant to the scope of the project involving various dispersed structures. It is hoped that GIS integration can improve project management control and optimize the final results of the construction of the 864 housing complexes.

Using GIS-supported MCDA method for appropriate site selection of parking lots: The case study of the city of Tetovo, North Macedonia

The provision of adequate parking spaces for vehicles has emerged as a prominent and challenging issue confronted by towns, cities, and municipal authorities in recent years. Addressing this problem necessitates a thorough examination of the prevailing physical conditions in existing parking areas, while simultaneously undertaking analyses to identify suitable locations for new parking areas or parking lots. This study focuses on the city of Tetovo, North Macedonia, investigating and assessing the available parking areas while analyzing potential sites in accordance with the city's needs and requirements. To facilitate decision-making, a Multi-Criteria Decision Analysis (MCDA) approach is employed to address the parking site selection analysis problem. The weightage of criteria utilized in the analysis is estimated, and potential parking solutions or site selections for new parking areas are identified through the combined application of Geographical Information System (GIS) and Analytic Hierarchy Process (AHP) techniques, identifying primary and sub-criteria, with a focus on Land Use and Transportation as the main criteria for selecting parking lots. The integration of GIS and AHP offers an effective and optimal methodology for site selection and identifying suitable parking locations. AHP method, applied to criteria, determined relative weights through expert opinions, while GIS facilitated spatial analysis for identifying suitable parking locations. The study identifies accessibility to main roads as the criterion carrying the greatest weight (0.517), while accessibility to cultural facilities holds the lowest weight (0.117). The study serves as a pivotal resource for sustainable urban management and decision-making, providing insights into future urban planning and the identification of suitable parking lot sites to foster sustainable development within the city.

Mobile mapping system for historic built heritage and GIS integration: a challenging case study

To manage the historic built heritage, it is of fundamental importance to fully understand the urban area under study, so that all its characteristics and critical issues related to historical conformation, stratification, and transformations can be better understood and described. Geometric surveying allows a deeper investigation of these characteristics through analytical investigation in support of urban planning theories as well. To date, geomatics provides various tools and techniques to meet the above-mentioned needs, and mobile mapping system (MMS) is a technology that can survey large areas in a short time, with good results in terms of density, accuracy, and coverage of the data. In this context, the article aims to verify whether this approach can also be useful in the complex and stratified reality of the historic urban context. The case analyzed—the historical center of Sabbioneta—presents some criticalities found in many urban centers of historical layout. Examples are narrow streets inserted in an urban context with multi-story buildings and consequent difficulty in receiving the GNSS signal and difficulty in following general MMS survey guidelines (trajectories with closed loops, wide radius curves). The analysis presented, relating to a survey carried out with Leica Pegasus:Two instrumentation, in addition to describing the strategies used to properly develop the survey, aims to analyze the resulting datum by discussing its possibilities for use in urban modeling, for cartographic or three-dimensional information modeling purposes. Particular attention is paid to assessing whether the quality of the data (accuracy, density) is suitable for the urban scale. Finally, an analysis of the data obtained from MMS was made with the geographic-topographic database (DBGT), in a GIS (Geographic Information System) environment, to check the possibilities of use and integration between the two models.

GIS-based multi-influencing factor (MIF) application for optimal site selection of solar photovoltaic power plant in Nashik, India

The significant natural energy sources for reducing the global usage of fossil fuels are renewable energy (RE) sources. Solar energy is a crucial and reliable RE source. Site selection for solar photovoltaic (PV) farms is a crucial issue in terms of spatial planning and RE policies. This study adopts a Geographic Information System (GIS)-based Multi-Influencing Factor (MIF) technique to enhance the precision of identifying and delineating optimal locations for solar PV farms. The choice of GIS and MIF is motivated by their ability to integrate diverse influencing factors, facilitating a holistic analysis of spatial data. The selected influencing factors include solar radiation, wind speed, Land Surface Temperature (LST), relative humidity, vegetation, elevation, land use, Euclidean distance from roads, and aspect. The optimal sites of solar PV power plant delineated revealed that ‘very low’ suitability of site covering 4.866% of the study area, ‘low’ suitability of site 13.190%, ‘moderate’ suitability of site 31.640%, ‘good’ suitability of site 32.347%, and ‘very good’ suitability of site for solar PV power plant encompassing 17.957% of the study area. The sensitivity analysis results show that the solar radiation, relative humidity, and elevation are the most effective on the accuracy of the prediction. The validation of the results shows the accuracy of solar PV power plant prediction using MIF technique in the study area was 81.80%. The integration of GIS and MIF not only enhances the accuracy of site suitability assessment but also provides a practical implementation strategy. This research offers valuable insights for renewable energy policymakers, urban planners, and other stakeholders seeking to identify and develop optimal locations for solar energy power farms in their respective regions.

Enhancing Property Valuation in Ruwa, Harare, Zimbabwe, using Kobo Collect and GIS

The escalating urbanization of Ruwa, a burgeoning suburb on the outskirts of Harare, Zimbabwe, has catalyzed an exigent demand for precise property valuation. Traditional valuation methods have struggled amidst the challenges of manual data collection, data inaccuracies, and protracted analyses. To address these constraints, a pioneering solution emerged at the crossroads of modern data collection and geospatial analysis. The fusion of Kobo Collect and Geographic Information Systems (GIS) presents a transformative avenue to surmount these challenges. The conventional practices faced hurdles marked by manual data collection's limitations. Inherent subjectivity and potential errors from pen-and-paper surveys posed challenges to data integrity. Moreover, as Ruwa underwent rapid changes, the inability to update data in real-time diminished valuation accuracy. Slow analysis processes also constrained timely access to property valuation insights. The integration of Kobo Collect and GIS provides a solution aligned with Ruwa's urban evolution. Kobo Collect's agile data collection forms, accessible on mobile devices, amplify data accuracy and practicality. The assimilation of GIS adds a spatial layer, and geotagging properties, and facilitates spatial analyses, unraveling intricate interplays of property values and geographic context. The outcomes encompass heightened data accuracy, as digital data entry minimizes errors. Efficiency gains result from real-time data entry and expedited analyses. Spatial insights from GIS analysis divulge patterns influencing property values. Stakeholders, empowered with informed decision-making capabilities, envision strategic urban planning and property development. The endeavor was not without challenges. Technical training ensured optimal tool utilization, while data privacy measures secured sensitive information.

UrbanGenoGAN: pioneering urban spatial planning using the synergistic integration of GAN, GA, and GIS

Introduction: Urban spatial planning is critical for the development of sustainable and livable cities. However, traditional planning methods often face challenges in handling complex planning scenarios and large-scale data.Methods: This paper introduces UrbanGenoGAN, a novel algorithm that integrates generative adversarial networks (GANs), genetic optimization algorithms (GOAs), and geographic information system (GIS) to address these challenges. Leveraging the generative power of GANs, the optimization capabilities of genetic algorithms, and the spatial analysis capabilities of GIS, UrbanGenoGAN is designed to generate optimized urban plans that cater to various urban planning challenges. Our methodology details the algorithm’s design and integration of its components, data collection and preprocessing, and the training and implementation processes.Results: Through rigorous evaluation metrics, comparative analysis with existing methodologies, and case studies, the proposed algorithm demonstrates significant improvement in urban planning outcomes. The research also explores the technical and practical considerations for implementing UrbanGenoGAN, including scalability, computational efficiency, data privacy, and ethical considerations.Discussion: The findings suggest that the integration of advanced machine learning and optimization techniques with spatial analysis offers a promising approach to enhancing decision-making in urban spatial planning. This work contributes to the growing field of AI applications in urban planning and paves the way for more efficient and sustainable urban development.

GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies

The industrial revolution and urbanization fundamentally restructured populations’ living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies. Expected final online publication date for the Annual Review of Public Health, Volume 45 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Integration of GIS with the Generalized Reciprocal Method (GRM) for Determining Foundation Bearing Capacity: A Case Study in Opolo, Yenagoa Bayelsa State, Nigeria

This study addresses the pressing need to assess foundation bearing capacity in Opolo, Yenagoa, Bayelsa State, Nigeria. The significance lies in the dearth of comprehensive geotechnical data for construction planning in the region. Past research is limited and this study contributes valuable insights by integrating Geographic Information System (GIS) with the Generalized Reciprocal Method (GRM). To collect data, near-surface seismic refraction surveys were conducted along three designated lines, utilizing ABEM Terraloc Mark 6 equipment, Easy Refract, and ArcGIS 10.4.1 software. This methodology allowed for the determination of key geotechnical parameters essential for soil characterization at potential foundation sites. The results revealed three distinct geoseismic layers. The uppermost layer, within a depth of 0.89 to 1.50 meters, exhibited inadequate compressional and shear wave velocities and low values for oedometric modulus, shear modulus, N-value, ultimate bearing capacity, and allowable bearing capacity. This indicates the presence of unsuitable, soft, and weak alluvial deposits for substantial structural loads. In contrast, the second layer (1.52 to 3.84 m depth) displayed favorable geotechnical parameters, making it suitable for various construction loads. The third layer (15.00 to 26.05 m depth) exhibited varying characteristics. The GIS analysis highlighted the unsuitability of the uppermost layer for construction, while the second and third layers were found to be fairly competent and suitable for shallow footing and foundation design. In summary, this study highlights the importance of geotechnical surveys in Opolo’s construction planning. It offers vital information for informed choices, addresses issues in the initial layer, and suggests secure, sustainable construction options.

Advancements and Applications of Drone-Integrated Geographic Information System Technology—A Review

Drones, also known as unmanned aerial vehicles (UAVs), have gained numerous applications due to their low cost, ease of use, vertical takeover and landing, and ability to operate in high-risk or hard-to-reach areas. The contribution of this review is that of building the bridge between drone technology and its application and advancements in the field of Geographic Information System (GIS). The integration of drones and GIS is valuable as it reduces costs and improves accessibility for geospatial data collection. Traditional methods involving aircraft for aerial photography are expensive, requiring the hiring of aircraft, pilots, and photographers. Drones equipped with advanced cameras and artificial intelligence software can replace the conventional technique and at the same time, be economical and time-efficient. The integration of drones and GIS is expected to bring revolutionary benefits in the fields of precision agriculture, urban planning, emergency health response, disaster management, the development of smart cities, food delivery, etc. In this paper, a state-of-the-art review of the deployment of drone-integrated GIS applications in different fields is presented. Numerous techniques and associated challenges related to their development, formulation, implementation, and regulation are highlighted. It has been concluded that drone-integration solutions in GIS improve efficiency and accuracy, enhance the decision-making process, and facilitate better real-time monitoring. The findings of this review paper are intended to help and benefit researchers, business developers, emergency service providers, industrialists, and policymakers.

Improving the operational efficiency of water desalination systems through the integration of GIS-SCADA

ABSTRACT The overlap of different fields has made it easy to introduce a real development of new technologies. New techniques used in the water sector are introduced; the importance of integration with each other will be increased to work as one unit with more efficiency and effectiveness. Integrating the real-time control of a supervisory control and data acquisition system (SCADA) and the data management and analysis capabilities of a geographic information system (GIS) can assist operators and decision-makers in disaster response and better system control. The objective of this paper is to evaluate the potential use of SCADA in conjunction with GIS to control and manage a water desalination plant network. The aid of the developed integrated system in the management of a water desalination system can be accessed on an interactive single dashboard for the network to simulate real situations through the data collected at each site that can be provided in real-time by SCADA, in addition to the results of analysis of these data that help to take the right decision and deliver the instructions thereon directly to the field devices to deal with any case of emergencies. In addition, this paper introduces an implementation approach of a new category of decision-support tools based on the integration of GIS and SCADA in implemented water desalination plants at the National Water Research Center (NWRC). A general review of both systems including their potentials in water desalination systems and the possibility of integration with each other has been introduced. This study demonstrates how integrating GIS and SCADA into a single dashboard can aid in data acquisition and provide a better understanding of the communication between the various sites and systems’ facility administration, despite the fact that such integration is uncommon because both systems use different IT platforms.

Assessment of groundwater potential zones using an integration of Remote Sensing, GIS and 2D Electrical Resistivity imaging in the Echway watershed, Baro River Basin, Southwest Ethiopia

The objective of this study is to delineate and identify the groundwater potential zone of degraded land in the Echway watershed, southwest Ethiopia, employing a combined approach that includes 2D electrical resistivity, the analytical hierarchy process (AHP), geographic information systems (GIS) and remote sensing (RS). Using a geographic information system (GIS) and remote sensing data, groundwater potential zones were identified by taking into account the soil types, drainage density, geology, lineament density, Land use and land cover, rainfall and slope. Using the AHP method, calculate the weight of thematic layers and rank of subclasses based on the effects of various thematic layers on groundwater potential. A significant weight was provided on the geology of the research region, total annual rainfall, and lineament density. Due to significant effects on groundwater potential zones, only three of the seven theme levels were assigned significant weight in this analysis. The weighted overlay analysis was used to construct the diagram of the zones with groundwater potential. 2D electrical resistivity was utilized to find the groundwater aquifer, and four major electrical layers were discovered: clayey silt, sand, moderately weathered/fractured rock, and basement parent rock. The groundwater potential zones in the study area have been classified into five categories: very low (22.97%), low (13.43%), moderate (32.50%), high (25.12%), and very high (5.98%) covered, respectively. The groundwater potential zone image was created by combining GIS, remote sensing, AHP, and an electrical survey

Generating Water Quality Maps of Klang River Based on Geographic Information System (GIS) and Water Quality Index (WQI)

Water quality index (WQI) and Geographic Information Systems (GIS) play a critical role in managing and modelling a variety of water resource issues, including urban drainage, point and non-point source pollution. Historically, the evaluation of water quality has been a domain reserved for experts, necessitating laborious and time-consuming in situ sampling and laboratory analysis. However, the integration of WQI and GIS has democratized this information, making it accessible to non-experts, thereby enhancing the comprehension of Klang River's water quality. The objective is to employ WQI and GIS to create comprehensive water quality maps. While WQI offers a straightforward numerical evaluation, the incorporation of graphical data provides a nuanced understanding of river pollution. Therefore, hourly WQI data observed at every week in 2 months from October to November 2021 over four stations (Kampung Medan, Kampung Lombong, Taman Pengkalan Batu and Jeti Sungai Udang) in Malaysia was acquired from the Selangor Maritime Gateway (SMG) website and the Malaysian National Water Quality Standard (NWQS). Adopting Inverse Distance Weighting (IDW) interpolation method, WQI parameters at unsampled locations were estimated based on values of nearby sampled points. Database was built to depict the water quality of the Klang River, particularly during the two-month monitoring. Mapping provides a clear indication of the river's water quality. The WQI mapping outcome fall between class II and class IV. The findings indicate varying water quality classes along the Klang River, revealing potential pollution sources in industrial and development areas. It was concluded from the study that the water pollution may be due to its proximity to industrial and development regions.

Scan to BIM Mapping Process Description for Building Representation in 3D GIS

This paper introduces a novel approach for mapping process description with Scan data to Building Information Modeling (BIM) in a 3D Geographic Information System (GIS). The methodology focuses on automatically generating building mass and facade information on the GIS platform using Point Cloud Data (PCD) of Airborne Laser Scanning (ALS). Advanced scanning techniques capture detailed geometry from the physical site and generate high-resolution point clouds, which are processed to create 3D models for GIS integration. The critical contribution of this research lies in a scalable Scan to BIM mapping process, which can be used for generating building footprints and masses, including attributes, on 3D GIS. The resulting integrated BIM–GIS dataset provides an accurate building mass, facade information, facility asset management, and architectural design and facilitates improved decision-making in urban planning based on enhanced visualization, analysis, and simulation. This study suggests a flexible Scan to BIM mapping process description based on use cases, including algorisms. Through prototype development, a case study demonstrates the effectiveness of the process approach, the automatic generation of BIM on a 3D GIS platform, and reducing the manual efforts. The proposed method automatically creates DEM, SHP, GeoJSON, IFC, and coordinate system information from scan data and can effectively map building objects in 3D GIS.