Aug 2026· Applied Sciences· Vol 16, pp. 8150· 0 citations· 38 references
Abstract
Geological conditions fundamentally constrain land-use suitability, terrain stability, and long-term sustainability, yet they remain underutilized in urban planning frameworks. This study presents a GIS-based geological suitability assessment model, tested on the City of Valjevo, Serbia, integrating lithological, structural, land use/land cover change and spatial data to guide urban development decisions. Seven lithological units—Quaternary deposits, lacustrine sediments, carbonate rocks, volcanic and pyroclastic rocks, ophiolites, ophiolitic mélanges, and Jadar Block sediments—were classified into four suitability classes based on lithological composition, structural characteristics, and rock mass behavior. An Integrated Geological Index (Igeo) was derived using an area-weighted approach across a regular hexagonal grid, enabling spatially explicit suitability mapping. Comparison with land use/land cover changes for 2012–2021 revealed a notable mismatch between geological suitability and observed development patterns: favorable and conditionally favorable terrains cover 72.5% of the study area but account for only 48.7% of recent urban expansion, while unfavorable terrains, occupying just 20.9% of the territory, absorbed 51.3% of new development. No expansion occurred within highly unfavorable terrains. These findings expose critical gaps in integrating geological criteria into planning practice and demonstrate a reproducible methodology for embedding geological suitability into sustainable urban development strategies across geologically heterogeneous regions.
Understanding landform distribution is essential for sustainable land-use planning and environmental management, particularly in regions with diverse terrain such as Benue State, Nigeria. Despite the importance of terrain information for agriculture, settlement development, and environmental conservation, quantitative landform classification in many parts of the state remains limited. This study aims to classify and analyse the major landforms of Makurdi, Gboko, and Katsina-Ala areas of Benue State and examine their implications for sustainable land-use planning. A GIS-based Multi-Criteria Analysis (MCA) approach was employed using secondary spatial datasets, including a 30 m Digital Elevation Model (DEM), satellite imagery, geological maps, soil data, and hydrographic information. Terrain parameters such as slope, elevation, curvature, drainage density, and land cover were derived and integrated through weighted overlay analysis in a GIS environment to produce a landform classification map. The analysis identified four dominant landform types: plains, hills, valleys, and plateaus. Plains constitute the most extensive landform, covering approximately 52% of the study area, mainly in Makurdi and parts of Gboko. Hills account for about 23%, plateaus approximately 10%, while valleys associated with the Benue River and its tributaries represent about 15% and exhibit high drainage density and susceptibility to seasonal flooding. The study highlights the need for land-use planning strategies that align with landform characteristics. Plains should be prioritized for agriculture, while hills and plateaus are more suitable for controlled development and conservation practices. Valley areas require careful management due to flood risks, including improved drainage planning and restrictions on settlement expansion in vulnerable zones.
This study investigates spatial and temporal land use and land cover changes in the Kuruwita Divisional Secretariat Division, Sri Lanka, over a ten-year period from 2013 to 2022 using Geographic Information System (GIS) and remote sensing techniques. Multi-temporal satellite images obtained from the United States Geological Survey were analyzed through supervised classification to identify five major land use categories: agriculture, forest, urban, water, and bare land. The classified data were processed in ArcGIS to generate land-use maps and calculate areal changes for each category. The results reveal a rapid expansion of urban land from 22 km² (8%) to 78 km² (30%), indicating accelerated semi-urban transformation, while agricultural land also showed notable growth. In contrast, forest cover declined sharply from 30% to 10% of the total land area, and water bodies were reduced by nearly half, reflecting increasing pressure on natural resources. Bare land exhibited a significant decrease, suggesting intensified land utilization driven by development activities. Overall, the findings demonstrate a clear shift from natural and semi-natural land uses toward urban and agricultural dominance in Kuruwita, highlighting the need for sustainable land use planning and environmental management to ensure balanced development in emerging semi-urban regions.
I. U. Yakandawala, W. Wijesinghe· Sri Lanka Journal of Sustain...· 0 citations
This study performs a spatiotemporal analysis and multi-dimensional attribution of land subsidence within Guangzhou's urban rail transit zones. Utilizing TS-InSAR (SBAS and PS-InSAR) on multi-source SAR imagery, we identified a “Stable North, Subsiding South” paradigm. While the urban core remains stable, extreme subsidence exceeding $280 ~\text{mm} /$ year persists in the rapidly developing Panyu and Nansha districts. Integrating GIS-based spatial overlay analysis, we quantified the driving mechanisms: a superposition of thick (15-40m) marine-terrestrial soft soils and anthropogenic pressures, including heavy building loads, groundwater extraction, and metroinduced socio-agglomeration. Tectonic faults further catalyze localized differential settlement. We propose a lightweight, intuitive analytical framework that bypasses the complexity of traditional geotechnical modeling. This approach provides essential spatial decision support for operational safety, early warning, and sustainable infrastructural planning in high-density deltaic metropolises.
Landslides constitute a significant geohazard in mountainous regions where complex interactions between terrain morphology, geological structures, hydrological conditions, and anthropogenic activities contribute to slope instability. Despite increasing concerns regarding slope failures along critical transportation corridors in South Africa, regional-scale comparative landslide susceptibility assessments remain limited, particularly within the structurally complex terrains of the Bushveld Igneous Complex. This study presents a GIS-based landslide susceptibility assessment of the Fetakgomo-Tubatse Municipality, Limpopo Province, South Africa, with particular emphasis on engineered slopes along the R37 and R555 transport corridors. Ten landslide conditioning factors, including slope angle, aspect, elevation, lithology, soil type, rainfall, land use/land cover, and proximity to roads, rivers, and geological lineaments, were integrated using three susceptibility modelling approaches: the Analytical Hierarchy Process (AHP), Fuzzy Logic, and the Extreme Gradient Boosting (XGBoost) machine-learning algorithm. The AHP model employed expert-derived pairwise comparisons and achieved an acceptable consistency ratio of 0.074, while the Fuzzy Logic model incorporated membership functions and a gamma operator to represent environmental uncertainty and gradual susceptibility transitions. Model performance was evaluated using Receiver Operating Characteristic Area Under the Curve (ROC-AUC), confusion matrix analysis, overall accuracy, balanced accuracy, McNemar’s test, and no-information rate statistics. The results indicate that the Fuzzy Logic model achieved the highest predictive performance (ROC-AUC = 0.769), followed by the AHP model (ROC-AUC = 0.757) and the XGBoost model (ROC-AUC = 0.739). Confusion matrix evaluation further confirmed the superior classification performance of the Fuzzy Logic model through higher overall and balanced accuracy values. High-susceptibility zones were concentrated along steep slopes, weathered lithological units, structurally controlled terrains, and road-cut sections where geological discontinuities interact with anthropogenic slope modifications. The findings demonstrate that uncertainty-based susceptibility modelling provides improved predictive capability within geologically heterogeneous terrains and highlight the value of integrating expert knowledge, spatial analysis, and machine-learning techniques for landslide hazard assessment. This study contributes one of the first comparative susceptibility assessments for the Eastern Limb of the Bushveld Igneous Complex and provides a transferable framework for infrastructure planning, disaster risk reduction, and slope management in mountainous environments worldwide.
Fumani Nkanyane, F. Sengani· Discover Geoscience· 0 citations
This study analyzes land use dynamics in Fălticeni Municipality over four decades (1985–2025), examining the influence of major political, socio-economic, and demographic changes on urban development. The transition from a centrally planned economy to a market economy, Romania’s democratic transformation and European integration, together with migration and population dynamics, have driven largely unregulated urban expansion at the expense of agricultural land and natural landscapes. Recent urban growth has also extended into areas with varying geomorphological vulnerability, increasing exposure to landslide hazards, while the city continues to face challenges related to abandoned industrial areas and insufficient forested land and green spaces. By integrating land use change analysis with physical vulnerability indicators, this study highlights the need for risk-informed and sustainable urban planning in medium-sized cities. It proposes a planning framework based on ecological zoning, controlled urban expansion on suitable terrain, brownfield redevelopment, the establishment of peri-urban forests, and the implementation of essential infrastructure supported by comprehensive geomorphological susceptibility assessments. The proposed approach provides practical guidance for enhancing urban resilience and can be replicated in other cities facing similar environmental and development challenges.
Mihai Barbacariu, M. Mîndrescu, Mihai Radu Vânturache et al.· Land· 0 citations
Municipal solid waste management is a critical challenge in hydro‐environmentally sensitive regions, requiring complex evaluations for landfill siting. This study develops a risk‐informed Geographic Information System (GIS)‐based multi‐criteria decision analysis (MCDA) framework for landfill site selection in Edirne Province. Edirne represents a highly constrained decision space due to its low‐lying topography, floodplain dynamics, dense river networks, and intensive agriculture. Using the Analytic Hierarchy Process (AHP), the framework integrates eight key criteria: flood susceptibility, river proximity, slope, elevation, land use/land cover (LULC), geological structure, soil characteristics, and accessibility. Results reveal that moderate suitability areas dominate the province (64.1%), followed by high (21.9%) and low (12.4%) suitability. Very high suitability areas are severely restricted, covering only 0.8% (52.3 km
2
) and emerging as fragmented patches where favorable conditions intersect. This spatial scarcity is primarily driven by critical environmental bottlenecks, specifically compatible LULC (0.4%), suitable geology (4.8%), and low‐permeability soils (3.9%), which collectively exert a strong spatial filtering effect. Ultimately, this structured GIS‐MCDA screening approach informs sustainable waste management planning in environmentally constrained regions. The severe limitation of highly suitable land demonstrates that conventional landfill expansion is spatially restrictive. The findings underscore the urgent need for strategies aligned with Sustainable Development Goals (SDGs 6 and 11), emphasizing surface and groundwater protection, resource recovery, recycling, and a critical transition away from landfill‐dependent waste systems.
E. Özgenç· Environmental Quality Manage...· 0 citations