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The study examines the complex dynamics of changes in LULC over three decades, focused on the years 1992, 2002, 2012, and 2022. The research highlights the significance of comprehending these alterations within the framework of environmental and socio-economic consequences. The changes in land use and land cover (LULC) have significant and far-reaching effects on ecosystems, biodiversity, and human livelihoods. This study offers useful information for politicians, conservationists, and urban planners by examining historical patterns and forecasting future changes. The study utilized a Multilayer Perceptron Neural Network (MLP-NN), a well-known machine learning technique that excels at collecting intricate patterns. This model’s design had three layers: input, hidden, and output. The model underwent 10,000 iterations during its training process, and a thorough statistical analysis was conducted to assess the impact of each driving component. The MLP-NN model demonstrated impressive performance, with a skill measure of 0.8724 and an accuracy rate of 89.08%. The accuracy of the LULC estimates for 2022 was verified by comparing them with observed data, ensuring the model’s reliability. Moreover, the presence of evidence likely was found to be a significant factor that had a substantial impact on the accuracy of the model. The study highlights the effectiveness of the MLP-NN model in accurately predicting changes in LULC. The model’s exceptional accuracy and proficiency make it a powerful tool for future LULC forecasts. Identifying the primary causes of model performance and understanding their implications may help to enhance land management strategies, encourage spatial planning, guide accurate decision-making, and facilitate the development of policies that align with sustainable growth and development. [ABSTRACT FROM AUTHOR]

The petrographic analysis and physico-mechanical assessment of the Nikanai Ghar Formation, exposed in the vicinity of the Bando Obo marble, near Swabi Town, north-western Pakistan, were carried out to assess and look into its prospects to serve as a building stone for engineering projects. Nine fresh bulk samples representing different textural types were chosen to investigate petrographic properties, as well as the physical and mechanical behaviour of the Nikanai Ghar Formation. A series of geotechnical tests and petrographic analyses were carried out to assess the material's suitability for construction applications. These geotechnical tests included measurements of unconfined compressive strength (UCS), Unconfined tensile strength (UTS), specific gravity (SG), shear strength (SS), porosity, and water absorption. The obtained physical qualities were then compared to standard specifications to evaluate their appropriateness for use in construction. The analysed samples are divided into different textural and mineralogical categories based on a careful microscopic examination of three representative thin sections. Four of the samples, JTN-1, JTN-2, JTN-4, and JTN-7, have a striking mineralogical similarity, both consisting primarily of calcite with only traces of opaque ore minerals. However, their textures are different, i.e., shape, grain size, and grain boundaries. JTN-2, JTN-9, and JTN-8 samples are medium-grained and sub-equi-granular while JTN-1, JTN-4, and JTN-5 are predominantly fine-grained and equi-granular. The JTN-3, JTN-6, and JTN-7 Samples are coarse-grained and sub-equi-granular to granular and contain trace amounts of muscovite, rutile, and ilmenite. The analysis showed that the Nikanai Ghar Formation can be used as aggregates by the domestic building sector because it falls within the parameters of standard specifications. [ABSTRACT FROM AUTHOR]