Geomatics and Environmental Engineering
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ISSN 1898-1135
e-ISSN: 2300-7095
Issue Date
2026
Volume
Vol. 20
Number
No. 4
Description
Journal Volume
Geomatics and Environmental Engineering
Vol. 20 (2026)
Projects
Pages
Articles
Topographic differencing for determining reservoir sedimentation using archival cartographic materials and modern measurement methods
(Wydawnictwa AGH, 2026) Baziak, Beata; Bodziony, Marek; Toś, Cezary; Szafarczyk, Anna
The aim of the study was to assess the sedimentation of the Klimkówka reservoir using topographic differencing (TD) analysis of digital elevation models (DEMs) created for two periods: before the reservoir was filled and after 30 years of operation. The archival model was developed from a scanned and calibrated analogue large-scale (1:5,000) topographic map with contour lines and elevation points. The current model was obtained by integrating unmanned aerial vehicle (UAV) photogrammetry and bathymetric measurements with a GNSS-positioned dual-frequency echo sounder. The accuracy of both models was analysed in detail, taking into account cartographic errors, map shrinkage, the scanning and calibration process, and the heterogeneous accuracy of the archival elevation data. Based on the DEM difference, the estimated sedimentation volume was considered unreliable. A detailed analysis of selected cross-sections revealed local accumulation processes in the backwater zone and slope erosion, but did not permit a reliable assessment of the siltation of the entire reservoir. The authors conclude that the reliable application of the TD method requires comparing two models produced with similarly high accuracy (e.g. UAV + bathymetry), while analogue cartographic materials from the 1970s do not meet current accuracy requirements for this type of analysis.
A novel housing price estimation model integrating GIS and DNN: a case study of Istanbul
(Wydawnictwa AGH, 2026) Çoruhlu, Yakup Emre; Dihkan, Mustafa; Yildiz, Okan; Çelik, Mehmet Özgür; Azadi, Hossein
Housing valuation is a concrete reflection of socio-economic inequalities in urban space. Particularly in densely populated, spatially fragmented large cities like Istanbul, the current official mass appraisal system used for property taxation fails to reflect market reality. This situation results in revenue losses in property taxes and spatial injustices. This study develops a Deep Neural Network (DNN)-based model that integrates spatially derived variables from Geographic Information Systems (GIS) and incorporates 24 objective variables related to location, structure, and access in Istanbul. The model, trained on 3,757 samples created using open-source big data, estimated housing values with high accuracy ($R^2$ = 0.979). The findings show that spatial differences in housing values are strongly related to urban variables such as accessibility and proximity to infrastructure. This approach not only produces housing value estimates but also provides a theoretical and methodological framework for spatial analyses of how value is produced in urban space. The study has the potential to support the development of a fair, transparent, and updatable mass appraisal system, especially for developing cities.
Quantitative assessment of drought severity in mining-influenced regions: a case study of lignite and copper extraction areas
(Wydawnictwa AGH, 2026) Rzepecka, Zofia; Birylo, Monika
Droughts occurring in open-pit mining areas are becoming increasingly significant, primarily due to decreased water availability. This poses a danger because it threatens the stable development of society and agricultural production and contributes to increased dust emissions that may interfere with mining operations. Climate change further intensifies these threats. Therefore, research into water availability, continuous monitoring, and environmental health indicators is vital, as the water cycle greatly impacts these factors. The paper aims to investigate drought severity in two large open-pit lignite mines in Turów and Bełchatów, and Legnica–Głogów Copper District (LGOM). The Combined Climatological Drought Index (CCDI) was used, alongside the water budget (WB), to characterise drought at the study sites. High consistency between the indices was observed throughout most of the studied period until 2018. Notably, significant reductions in water availability were recorded from 2018 onwards in the areas of the three studied mines.
Twenty years of soil organic carbon research in Ecuador: a bibliometric and GIS-based assessment of trends and research gaps
(Wydawnictwa AGH, 2026) Reyna-Bowen, Lizardo; Klamerus-Iwan, Anna; Delgado-Moreira, María Isabel
The study assesses the evolution of soil organic carbon (SOC) research in Ecuador between 2003 and 2023 using a bibliometric approach. The search was conducted in the Scopus, Web of Science, and SciELO databases, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. This protocol enabled the systematic identification and evaluation of the literature, resulting in a final selection of 60 peer-reviewed documents focused on SOC in Ecuador. These documents were analysed using RStudio (Bibliometrix), VOSviewer, and QGIS to map research output, collaboration networks, and thematic evolution. The main findings highlight that research on SOC in Ecuador has increased since 2003, largely due to international collaboration, primarily with institutions in Germany, Spain, and the United States. Early studies primarily focused on land-use change (deforestation and agriculture), whereas recent research emphasises remote-sensing applications, carbon stabilisation mechanisms, and nature-based solutions. Most research focuses on high-altitude provinces and protected areas, such as Loja and Chimborazo. The results also indicate that in volcanic ash soils (Andosols), altitude and land-use intensity are the main drivers of variation in SOC stocks. Key gaps include a lack of studies in the Amazon basin and coastal lowlands, as well as the absence of long-term SOC monitoring, both of which limit the development of national SOC inventories. While research output has increased steadily over time, addressing the identified gaps is necessary to establish a comprehensive scientific basis for climate change adaptation and sustainable soil management across the country’s diverse ecosystems.
Point cloud technologies for smart cities: acquisition, processing, and applications
(Wydawnictwa AGH, 2026) Hauzner, Jagoda
Recent progress in LiDAR, UAV, and photogrammetric systems has made spatial data collection faster and more accessible. These tools enable the acquisition of detailed point clouds that form the foundation for many smart city applications. Efficient processing of these datasets is now a practical necessity, especially for everyday tasks such as monitoring roads and bridges, managing traffic, or building 3D city models used in digital twins. This paper reviews both classical and deep learning-based processing methods, data acquisition techniques, and multi-sensor integration strategies. Furthermore, the paper highlights applications beyond infrastructure, such as environmental monitoring of green areas and the analysis of pedestrian and bicycle networks. Despite the significant progress achieved in recent years, several open challenges remain. Among the most important are the need for standardized data formats, improved computational efficiency, and robust fusion of heterogeneous sensor data. Overcoming these difficulties is key to ensuring that digital twins and AI-based analysis become useful tools in practical urban management. Ultimately, continued progress in this field can make a meaningful contribution to the development of smarter and more sustainable cities.