GIS-based biomass resource assessment with BRAVO

Data management and analysis are important for the application of water quality modeling in water environmental protection. The integration of the Environmental Fluid Dynamics Code (EFDC) model with Geographical Information Systems (GIS) is discussed in this paper. The data management and analysis ability of this widely used water quality model was enhanced by the integration. Database methods are used to integrate the different types of modeling data into a GIS platform. The spatial data modeling and analysis capacity of GIS is used in the pre-processing and post-processing of EFDC. The integration application is demonstrated by a case study of the Lower Charles River Basin water quality model, which was built with EFDC and has 56 varying-size curvilinear horizontal grids and 8 vertical layers. The case study shows that the integrated system significantly improved the application of EFDC with more efficient data processing, organization and analysis, and can be used as a powerful tool for water environmental management and decision making.

Implementation of a feature-constraint mesh generation algorithm within a GIS

O avanço dos recursos tecnológicos na era digital tem favorecido os estudos urbanos em termos de ferramentas e metodologias cada vez mais apuradas para a compreensão dos fenômenos contemporâneos, dentre elas as técnicas de geoprocessamento em plataformas SIG (Sistemas de Informação Geográfica). A ampliação desmesurada de informação para os estudos urbanos suscita uma reflexão sobre instrumentos metodológicos na era digital. Partindo do pressuposto que a cidade contemporânea é histórica, e portanto, um acúmulo materializado de idealizações passadas, busca-se evidenciar a relevância da análise morfológica e do instrumental da história urbana potencializado por tecnologias digitais, para a compreensão da cidade contemporânea em sua complexidade, reconhecendo sua historicidade, a partir de seu processo urbano. Para demonstrar o potencial da articulação entre a cartografia digital em plataforma SIG e as abordagens clássicas da morfologia urbana, adota-se como objeto empírico a Área Central da Cidade do Rio de Janeiro, selecionando casos de áreas tensionadas pelos vestígios de projetos realizados no século XX, para refletir sobre as possibilidades da cartografia digital na decodificação do emaranhado de projetos e desígnios que deram origem ao palimpsesto urbano que estrutura a Área Central Carioca.

The political push to increase power generation from renewable sources, such as solar energy, requires knowing the best places to site new solar power plants with respect to the applicable regulatory, operational, engineering, environmental, and socioeconomic criteria. Therefore, we present applications of remote sensing data for mapping suitable areas for concentrated solar power (CSP) plants. Our approach uses satellite data from National Aeronautical and Space Administration’s Global Energy and Water Cycle Surface Radiation Budget project at a resolution of 1 deg for estimating global solar radiation for the study area. Then we develop a computational model built on a geographic information system (GIS) platform that divides the study area into a grid of cells and estimates the site suitability value for each cell by computing a list of metrics based on applicable site requirements using GIS data. The computed metrics include population density, solar energy potential, federal lands, and hazardous facilities. Overall, some 30 GIS datasets are used to compute eight metrics. The site suitability value for each cell is computed as an algebraic sum of all metrics for the cell with the assumption that all metrics have equal weight. Finally, we color each cell according to its suitability value. We present results for CSP that drives a stream turbine and parabolic mirror connected to a Stirling engine.

Geographical Information System (GIS) is associated as an essential tool and as a part of natural resource management activities worldwide. Though, GIS is receiving special attention in the field of hydrology and the aquaculture management, their deployment for spatial decision support in this domain continues to be very slow. This situation is owing to a variety of constraints together with an absence of appreciation of the technology, restricted understanding of GIS principles and associated methodology, and inadequate structure commitment to confirm continuity of these spatial decision support tools. This paper addresses these constraints and includes the use of basic GIS techniques. Fish and water samples were collected and analyzed from seven sites along the Cauvery river basin, Tamilnadu, India and the results were incorporated into GIS platform. The section on GIS terminology addresses the two fundamental types of GIS (Mapping and Interpretative analysis), and discusses the aspects related to the visualization of outcomes. Spatial distribution maps were prepared for the above analyzed parameters. Inverse Distance Weighting (IDW) tool have been applied to express the results obtained from the study area.

The current review conducts a comprehensive comparison of Quantum GIS (QGIS) and ArcGIS in the context of healthcare applications, aiming to assist users in selecting the most appropriate GIS platform for their specific needs. Geographic Information Systems (GIS) are essential tools in healthcare, providing capabilities for spatial analysis, disease mapping, and resource allocation. Driven by the need to improve healthcare delivery and public health strategies, this study compares the functionalities, costs, and support systems of QGIS and ArcGIS. The major objective is to determine which GIS platform offers the best balance of cost-efficiency and performance across various healthcare scenarios. The methodology encompasses a detailed comparative analysis, incorporating quantitative data from user satisfaction surveys, performance evaluations, and real-world case studies. Findings reveal that QGIS, as an open-source GIS software, is highly cost-effective and customizable, making it particularly advantageous for budget-limited projects and smaller organizations requiring flexibility. Its extensibility via plugins and robust user community fosters continuous innovation and improvement. QGIS proves exceptionally effective in healthcare applications such as disease mapping and accessibility analysis, where customization and cost-efficiency are critical. Conversely, ArcGIS is distinguished by its advanced analytical capabilities and strong performance in handling complex, large-scale studies. Its sophisticated tools and comprehensive spatial analysis functionalities are essential for thorough healthcare research and planning. Although ArcGIS incurs higher costs, its extensive feature set, professional support, and exhaustive documentation justify the investment for large organizations and research institutions engaged in detailed GIS projects. In conclusion, both QGIS and ArcGIS exhibit significant strengths in key healthcare applications. QGIS excels in affordability and flexibility, while ArcGIS provides superior analytical power and support for extensive projects. Future research should focus on integrating real-time data and enhancing user experience to further optimize GIS applications in healthcare.

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.

The Program for the Development of the Armed Forces of Ukraine until 2020 and the goals set out in the Strategic Defense Bulletin of Ukraine define the tasks of creating combat control systems (C4ISR) and defense planning (DRMIS). It is important to focus on the role of a geographic information system (GIS), as a common core in the process of interaction of these systems. These issues are mostly solved in the leading NATO countries, in particular, in their framework architectures. The information infrastructure has all the hallmarks of the Unified Information Environment of special-purpose systems, so the choice of platform is quite a challenge. The purpose of the article is to analyze and compare special software GIS-platforms for the highest level of information infrastructure of the Ministry of Defense of Ukraine. It is considered that GIS has the following properties: saving, organizing, editing and analyzing geographic data; includes visual abilities to reflect geographic information; has some GIS tools, or uses a GIS platform in its decision; distribution or processing of cartographic attribute data and data from other sources. To compare these properties, the general needs for GIS technology from the Ukrainian Defense Forces are defined. They are due to the creation of a joint GIS-core decision support system for the C4ISR type system (Command, Control, Computers, Communications, Intelligence, Surveillance, and Reconnaissance) and the DRMIS type defense management planning system. As a result of a comparative analysis of software platforms ArcGIS and QGIS with special software deployed on their basis, it was found that these platforms meet all the requirements for GIS with support for all key functions. However, using most advantages, it has been found that ArcGIS is the best choice. Even considering the option of paying for licenses, this will reduce the risks of providing further support.

BIM-GIS-DCEs enabled vulnerability assessment of interdependent infrastructures – A case of stormwater drainage-building-road transport Nexus in urban flooding

The seismic risk associated with bridges is a function of the structural vulnerabilities and geological conditions at the bridge site. Geographic Information Systems (GIS) allow to integrate spatial information, such as seismic attenuation or local amplification, into ad-hoc information on the structural characteristics of bridges, thereby increasing knowledge on the seismic risk to which a bridge network is exposed. The aim of this study is to develop a scale of susceptibility to the amplification effect by gathering available data on geographic information system platforms. Among other things, this information includes the thickness of the quaternary deposit and surficial geology, complemented with ambient noise measurements. The region of study, the Saint Lawrence Valley, covers an area measuring 32,000 km2, extending from Quebec City in the north to the US border in the south, and includes approximately 5000 bridges and overpasses. The highest susceptibility levels in the present study are associated with colluvial, alluvial and marine deposits. The proposed susceptibility scale is to be used for a bridge network, and can be integrated into existing seismic evaluation scoring procedures. It contributes to seismic risk reduction for bridge and overpass networks by improving available assessment procedures for prioritising mitigation strategies, emergency planning and post-earthquake interventions.

Grid planning and pre-project site survey require the support of Geographic Information System (GIS). However, the existing grid GIS platform adopts B/S mode which can only be run and viewed on the computer connected to the company’s intranet, thus failing to meet the needs of on-site investigation by the planners. Therefore, the application of mobile GIS platform to pre-grid planning is an inevitable development direction for the future power grid information system, and how to manage more efficiently and use the data collected by mobile GIS terminal will be an urgent problem to be solved. Based on the authors’ learning and practical experience, this work first analyzed the potentials of mobile GIS for grid planning, then discussed the problems in high voltage grid planning, and finally proposed the system function and overall architecture design based on mobile GIS platform.

Large scale block cave mining has been operated for over 30 years in the Erstberg Mining District in the province of Papua, Indonesia. The ore body is divided into four vertically stacked ore bodies: Gunung Bijih Timur (GBT), Intermediate Ore Zone (IOZ), Deep Ore Zone (DOZ), and Deep Mill Level Zone (DMLZ). The GBT and IOZ mines were closed on 1993 and 2003, DOZ mine is in its peak production performance 80 ktpd, and DMLZ mine is still in the development stage to prepare mine infrastructures. This situation generates gradual downward settling of the surface or subsidence. Significant deformation changes at the surface by block caving subsidence could damage the mine’s infrastructures in surface and underground and also affect geological structures overlying the mining areas which may result in surface impacts on the natural geomorphology and land use.
 
 In this paper, integrated system based on Geographic Information System (GIS) platform applied to predict ground movements due to underground mining. Deep Ore Zone (DOZ) block cave mine is studied for subsidence prediction. The mining extraction thickness model is obtained from height of draw (HOD) observed data. Subsidence Engineering Handbook (SEH) of empirical model and measured data from mining fields is used for subsidence calculation parameters. The calculations were performed in GIS. The maximum vertical displacement has been predicted about 12m by means of full caving mining method.
 
 Keywords: Ground movements, block caving, GIS, underground mining, and subsidence

This study proposes a geographic information system (GIS)-based cellular automata (CA) model, which is designed for planning bikeways upon existing footpath networks within an urban area. The CA model was developed based on a GIS platform as a visual interface whereby spatiotemporal characteristics and spatial processing can be combined in a highly effective way. The host value of each CA cell is conditioned upon four indicator variables, namely cycling demand level, land-use nature, social value, and traffic safety. This model gives traffic planners a quick and intuitive framework to develop cycling facilities under limited land resources. A model prototype has been developed in a common desktop GIS and applied to a mid-sized rapidly developing area in Singapore.

The paper takes the typical Karst-Phreatic in the north of China-Dawu Water Source as an example, and the risk assessment of groundwater pollution is conducted by using the Overlay and Index method. Unsaturated zone media, net recharge, rich water property of aquifer and depth to groundwater table are chose as the intrinsic vulnerability indexes, and types of land use, sources of pollutants and extent of groundwater exploitation are chose as the special vulnerability indexes. Indexes weights are determined by using the Analytic Hierarchy Process. The risk assessment map is obtained based on the spatial analysis platform of Geographical Information System. The rationality of the risk assessment model and risk assessment results are validated by using the Single-Parameter Sensitivity Method and groundwater anomalies, respectively. The study area is classified into highest risk, higher risk, middle risk, lower risk and lowest risk sub areas based on the qualitative evaluation results. Results show that highest and higher risk sub areas account for 39.0%, which are located at a certain Petrochemical Company and the Gougao-Xiaowu area, the unsaturated zone media is the most sensitive factor in the risk assessment of groundwater pollution. The risk map obtained from the Overlay and Index Method is a promising tool for the design of groundwater management and protection schemes, which contributes to the development of human survival.

The artificial neural network (ANN) is a frontier theory of complex non-linearity scientific and artificial intelligence science. At present, the theory is seldom used for urban land suitability evaluation. It is a new method that combines geographic information system (GIS) and artificial neural network technology together. In order to evaluate urban land suitability properly, a new analysis index system is put forward in this paper. According to the index system, taking Jinan as an example, and based on the GIS platform, we have evaluated the urban land suitability using the BP neural network model. The result shows that the simulated urban land suitability of Jinan, divided into 6 types, is accurate and effective.