Geomatics and Environmental Engineering
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ISSN 1898-1135
e-ISSN: 2300-7095
Issue Date
2025
Volume
Vol. 19
Number
No. 3
Description
Journal Volume
Geomatics and Environmental Engineering
Vol. 19 (2025)
Projects
Pages
Articles
Analysis of Road Network Structure Using Scale-Free Network Theory in Context of Potential Fire Department Interventions in Urbanized Area
(Wydawnictwa AGH, 2025) Kowalczyk, Anna Maria; Garustowicz, Adam
Roads are essential to fire departments for saving lives and protecting health. The development of urban structures and the increasing complexity of transport systems necessitate the search for novel solutions and tools for spatial analyses in safety terms. This study aims to determine whether the city’s transport system network exhibits scale-free network characteristics and whether crucial center nodes can be identified for the efficient functioning of the entire system. The study developed two transport system network models: one based on the Topographic Objects Database, and the other on data from devices that record vehicle traffic at selected nodes. Both were found to follow the bell-shaped curve characteristic of random networks, however, the second network model differed significantly from the first model due to the identification of nodes that could potentially act as hubs in an emerging scale-free network. A simulation was conducted to model the impact of cutting off these crucial nodes (centers), with a visualization of the network structure’s behavior. In conclusion, using scale-free network theory to optimize FD operations is reasonable and useful. In this scenario, the transport system network displays scale-free characteristics, thus allowing for the identification of the most crucial functional points of the entire structure.
Identifying Geological Fault Structures Using GGMplus Satellite Data and Derivative Methods to Characterize Mount Endut Geothermal Systems via 3D-Inversion Gravity Modeling
(Wydawnictwa AGH, 2025) Soekarno, Hari; Pranoto, Bono; Restiana, Andini; Martha, Agustya Adi; Prakoso Setiadi, Tio Azhar; Hudayat, Nurul; Rais, Achmad Fachrudin; Suwarno, Yatin; Turmudi; Sutejo, Bayu
The geological map shows that the Mount Endut area possesses a geothermal system, which is suggested by the presence of geothermal surface manifestations: the Cikawah and Handeleum hot springs. The existence of a subsurface geological fault structure along the manifestations creates good permeability for the geothermal reservoir. The purpose of this study was to utilize Global Gravity Model plus (GGMplus) gravity satellite data to prove the existence of a geological fault structure around the manifestation area with the first horizontal derivative (FHD) and second vertical derivative (SVD) methods, then, we developed a conceptual model of the geothermal system from the 3D-inversion gravity method. Results show a cap suspected of being clay, with a density of 2.52–2.58 g/cm3 at depth of 0–1250 m. The reservoir layer was suspected to be lava rock with a density of 2.60–2.66 g/cm3 at a depth of 1500–3000 m, also, the heat source layer was suspected to be an igneous intrusion with a density of 2.70–2.72 g/cm3 at depth of 1750–3000 m.
Automating Compliance: Advanced Verification Techniques for Information Requirements in BIM Railway Projects
(Wydawnictwa AGH, 2025) Wrzosek, Maciej; Owerko, Tomasz; Rochel, Maciej; Kasznia, Dariusz
Since BIM (building information modelling) emerged as the standard for project preparation, there has been a demand for rapid compliance-checking. This article explains this issue in railway building projects, it focuses on establishing a common ground for the creation, verification, and management of EIR (exchange information requirements). Using examples from European railway projects, the authors illustrate how EIR structures and standards can vary. The paper demonstrates basic requirements to ensure BIM models comply with contracting authorities’ requirements thus supporting effective planning for the design, construction, and operation phases. The study also reviews existing requirements, engineering processes, and testing methods, creating a link between BIM and software-engineering practices such as unit testing, system testing, and integration testing to ensure comprehensive model validation. By highlighting the use of buildingSMART Open BIM standard, such as information delivery specifications (IDS) and industry foundation classes (IFC), the study illustrates their role in the automated or semi-automated compliance verification. The research results showed the limitations of the verification tools and methods that are currently being used in the industry, emphasizing the need for further advancements in computer-aided verification. Presented coverage percentages are based on a limited set of EIR documents and tool assessments, these values should be considered to be estimates based on specific assumptions and not definitive generalizable results.
Multi-Perspective Evaluation of Urban Green Views: Spatial and Street-View Data Integration in Sudirman Central Business District, Indonesia
(Wydawnictwa AGH, 2025) Pradana, Mohammad Raditia; Wibowo, Adi; Semedi, Jarot Mulyo
Urban green spaces (UGSs) are critical for enhancing urban livability and sustainability by providing both ecological and human-centered benefits. This study integrates spatial landscape metrics and the street-level visibility of greenery (measured through the green view index [GVI]) in order to evaluate the structural and visual characteristics of UGSs in a dynamic urban area – specifically, the Sudirman Central Business District (SCBD) of Jakarta, Indonesia. The analysis focuses on examining the roles of landscape metrics such as area, perimeter, compactness, shape index, and elongation in influencing the GVI and its spatial variability across different types of urban green spaces (including parks, green corridors, and open spaces). The results indicated that larger and more compact UGSs significantly contributed to higher GVI levels (thus, reflecting better visual greenery), while elongated and fragmented green spaces exhibited greater variability and lower visibility. Non-linear relationships (assessed through random forest regression and SHAP analysis) further revealed the complex interactions between GVI and landscape metrics, thus emphasizing the importance of incorporating advanced statistical approaches. The limitations that are related to data quality, temporal coverage, and spatial heterogeneity are also discussed, thus highlighting opportunities for future research for addressing these challenges through multi-temporal analyses and spatially explicit models. By bridging the gap between the spatial configurations and visual perception of UGSs, this study contributes to sustainable urban-planning strategies that are aimed at optimizing green spaces for ecological functionality and human well-being.
Geospatial and Optimized SVM-Based Landslide Susceptibility Zonation of South District of Sikkim, India
(Wydawnictwa AGH, 2025) Anuragi, Saurabh Kumar
Landslide identification and susceptibility maps play vital roles in supporting planners and decision-makers who manage disaster risks. By providing accurate information, these maps significantly contribute to minimizing the potential losses of life and property. To create effective landslide-susceptibility models, it is essential to incorporate a combination of terrain characteristics and meteorological factors, thus enhancing our understanding and preparedness for such events. This study presents a comparative analysis of three kernel functions (linear, polynomial, and RBF) of an support vector classifier (SVC) accompanied by a grid-search in order to determine optimal hyper-parameter settings. The primary objective of this methodological framework is to ensure accurate and reliable predictions for the generation of landslide-susceptibility maps in the South District of Sikkim, India. In this investigation, 14 conditioning factors were considered, including aspect, distance to streams, distance to roads, drainage density, elevation, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), plan curvature, profile curvature, rainfall, slope, soil type, and earthquake susceptibility. The performances of the models were evaluated using a range of metrics, including the training score, testing score, kappa, sensitivity, specificity, accuracy, and area under the curve (AUC). Optimal hyper-parameter tuning for each SVC kernel was conducted through a grid-search approach. The results indicated that the SVC_poly and SVC_rbf models surpassed the linear model, achieving accuracy and AUC values of 0.907 and 0.908, respectively, in developing susceptibility maps. Consequently, both the SVC_poly and SVC_rbf models were identified as the most reliable and effective tools for landslide-susceptibility mapping in this study, making them optimal choices for predictive analyses in this domain.