Since at least half of the world’s population resides and works within coastal land, the coastal zone processes and resource management is of great economic and social importance. One of the fundamental issues for coastal city planners, researchers, managers, and engineers is the coastal city land-use suitability. Land-use suitability is the ability of a given type of land to support a defined use. Rapid urbanization and consequent haphazard growth of cities result in deterioration of infrastructure facilities, loss of agricultural land, water bodies, open spaces, and many micro-climatic changes. Hence, accurate data on coastal city hazards are essential and valuable tools for coastal planning and management, sustainable coastal development, coastal environment conservation, selection of a site for coastal city structures, and coastal resources. In this investigation, the Delphi and Analytical Hierarchy Process (D-AHP) Hybrid model and Geographic Information System (GIS) technique for Coastal Land-Use Assessment (CLUA) are mapped to detect the most suitable and unsuitable areas in the Kuala Terengganu coastal zone. Furthermore, this research offered information not only on the present urban land-use trend and established amenity status in Kuala Terengganu, but also on the suitability of land for the potential establishment of urban facilities for improved urban planning and appropriate decision-making. Using the D-AHP Hybrid model and GIS tool for coastal city management is broadly practical for government, policymakers, and planners to appropriately strategize and plan for the future of coastal cities in Malaysia and other analog coastal cities around the world.

Climate change is regarded as a serious threat to both environment and humanity, and as a result, it has piqued worldwide attention in the twenty-first century. Natural hazards are expected to have major effects in the coastal cities of the globe. At the same time, about two-thirds of the world’s human population lives in the coastal margins. One of the fundamental issues for coastal city planners is the coastal cities’ environmental change. This paper presents the application of a model framework for the management and sustainable development of coastal cities under a changing climate in Kuala Terengganu Malaysia. The analytic hierarchy process (AHP) is performed in the Expert Choice software for coastal city hazard management. This approach enables decision-makers to evaluate and identify the relative priorities of vulnerability and hazard criteria and sub-criteria based on a set of preferences, criteria, and alternatives. This paper also presents a hierarchy erosion design applied in Kuala Terengganu to choose the important sustainable weights of criteria and sub-criteria as well as the zone as an alternative model.

Mineral prospectivity mapping (MPM) is crucial for efficient mineral exploration, where prospective zones are identified in a cost-effective manner. This study focuses on generating prospectivity maps for hydrothermal polymetallic mineralization in the Feizabad area, in northeastern Iran, using unsupervised anomaly detection methods, i.e., isolation forest (IForest) and deep isolation forest (DIF) algorithms. As mineralization events are rare and complex, traditional approaches continue to encounter difficulties, despite advances in MPM. In this respect, unsupervised anomaly detection algorithms, which do not rely on ground truth samples, offer a suitable solution. Here, we compile geospatial datasets on the Feizabad area, which is known for its polymetallic mineralization showings. Fourteen evidence layers were created, based on the geology and mineralization characteristics of the area. Both the IForest and DIF algorithms were employed to identify areas with high mineralization potential. The DIF, which uses neural networks to handle non-linear relationships in high-dimensional data, outperformed the traditional decision tree-based IForest algorithm. The results, evaluated through a success rate curve, demonstrated that the DIF provided more accurate prospectivity maps, effectively capturing complex, non-linear relationships. This highlights the DIF algorithm’s suitability for MPM, offering significant advantages over the IForest algorithm. The present study concludes that the DIF algorithm, and similar unsupervised anomaly detection algorithms, are highly effective for MPM, making them valuable tools for both brownfield and greenfield exploration.

Coastal hazards are an urgent issue of global concern considering the increasing population pressure in coastal regions, retreating coastlines, and rising seawater levels. Here we demonstrate the process of assessing the vulnerability of a coastal urban environment using the case of Kuala Terengganu, a coastal town in Malaysia, and evaluating the potential social, environmental, and economic impacts. Uncertainties in the human dimensions of global change deeply affect the assessment and responses to environmental, climatic, and non-climate impacts on coastal city population growth and communities. We address these uncertainties by combining a Delphi-Analytical Hierarchy Process (Delphi-AHP) model and Geographic Information System (GIS)tools to determine mitigation and adaptation probabilities as part of a Coastal City Vulnerability Assessment. We conclude by presenting calculations of the short- and long-term suitability for land use and recommending hazard mitigation measures to equip city planners and decision-makers in evaluating hazards and potential impacts on coastal city areas.