A5076859356- Flood Risk Assessment and Management
- Groundwater and Watershed Analysis
- Urban Heat Island Mitigation
- Landslides and related hazards
- Geochemistry and Geologic Mapping
- Fire effects on ecosystems
- Soil erosion and sediment transport
- Remote Sensing and Land Use
- Land Use and Ecosystem Services
- Geophysics and Gravity Measurements
- Automated Road and Building Extraction
- Geological and Geochemical Analysis
- Hydrology and Watershed Management Studies
- Heavy metals in environment
- GNSS positioning and interference
- Soil and Land Suitability Analysis
- Soil Geostatistics and Mapping
- Smart Agriculture and AI
- X-ray Diffraction in Crystallography
- Hydrocarbon exploration and reservoir analysis
- Solar and Space Plasma Dynamics
- Radioactivity and Radon Measurements
- Remote-Sensing Image Classification
- High-pressure geophysics and materials
- Water Quality and Pollution Assessment
Khushal Khan Khattak University Karak
2022-2025
University of Chinese Academy of Sciences
2024-2025
Xinjiang Institute of Ecology and Geography
2024-2025
Chinese Academy of Sciences
2024-2025
COMSATS University Islamabad
2022
The present research is conducted in the southern region of Khyber Pakhtunkhwa, Pakistan, to identify groundwater potential zones (GWPZ). We used three models including Weight Evidence (WOE), Frequency Ratio (FR), and Information Value (IV) with twelve parameters (elevation, slope, aspect, curvature, drainage network, LULC, precipitation, geology, Lineament, NDVI, road, soil texture, that have been prepared integrated into ArcGIS 10.8. reliability applied models' results was validated using...
Groundwater is a crucial natural resource that varies in quality and quantity across Khyber Pakhtunkhwa (KPK), Pakistan. Increased population urbanization place enormous demands on groundwater supplies, reducing both their quantity. This research aimed to delineate the potential zone Kohat region, Pakistan by integrating twelve thematic layers. In current research, Potential Zone (GWPZ) were created implementing Weight of Evidence (WOE), Frequency Ratio (FR), Information Value (IV) models...
The management of groundwater systems is essential for nations that rely on as the principal source communal water supply (e.g., Mohmand District Pakistan). work employed Remote Sensing and GIS datasets to ascertain recharge zones (GWRZ) in Pakistan. Subsequently, a sensitivity analysis was conducted examine impact geology hydrologic factors variability GWRZ. GWRZ determined by employing weighted overlay thematic maps derived from about drainage density, slope, geology, rainfall, lineament...
Landslides are a recurrent environmental hazard in hilly regions and affect the socioeconomic development Pakistan. The current study area is tourism hydro energy hub of Pakistan affected by hazard. A landslide susceptibility mapping (LSM) Hindu Kush Himalayan, Swat District, Pakistan, can be created to reduce demographic losses due landslides. This conducted apply three bivariate models, including weights evidence (WOE), frequency ratio (FR), information value (IV) for an LSM that has not...
The decision support system for agro-technology transfer (DSSAT) is a worldwide crop modeling platform used crops growth, yield, leaf area index (LAI), and biomass estimation under varying climatic, soil management conditions. This study integrates DSSAT with satellite remote sensing (RS) data to estimates canopy state variables like LAI biomass. For estimation, Moderate Resolution Imaging Spectroradiometer (MODIS) product (MCD15A3H MOD17A2 / MOD17A3 products biomass) are used. Field...
Impervious surfaces are an essential component of our environment and mainly triggered by human developments. Rapid urbanization population expansion have increased Lahore's urban impervious surface area. This research is based on estimating the imper- vious area ( uisa ) growth from 1993 to 2022. Therefore, we aimed generate accurate map Landsat time series data Google Earth Engine gee ). We used a novel global index gisai for extraction. The accomplished significant results, with average...
This study proposes a fusion approach to enhancing urban remote sensing applications by integrating SAR (Sentinel-1) and optical (Landsat-8) satellite datasets. The technique combines feature-based simple layer stacking (SLS) improve the accuracy of impervious surface (UIS) extraction. textures modified indices are used for feature extraction, classification is performed using XGBoost machine learning algorithm in Python Google Earth Engine. focuses on four global cities (New York, Paris,...
Sustainable groundwater development stands out as a contemporary concern for growing global populations, particularly in stressed riverine arid and semi-arid regions. This study integrated satellite-based (Sentinel-2, ALOS-DEM, CHIRPS rainfall) data with ancillary lithology infrastructure datasets using Weight of Evidence (WoE) Frequency Ratio (FR) models to delineate Groundwater Potential Zones (GWPZs) the Hangu District, hydrologically region northern Pakistan, support Development Goals...
Soil erosion is one of Pakistan’s most serious environmental threats. This study used geospatial modelling to identify the distinct zones susceptible soil in Murree, Pakistan. Using a machine learning technique Google Earth engine (GEE) and Earth, we identified 1250 events. The inventory (dependent variable) was separated into two datasets, for training (70%) testing (30%). Elevation, slope, aspect, curvature, stream, precipitation, LULC, lithology, soil, NDVI, distance road were prepared...
Urbanized riverine cities in southern Asian developing countries face significant challenges understanding the spatiotemporal thermal impacts of land use/land cover (LULC) changes driven by rapid urbanization and climatic variability. While previous studies have investigated factors influencing surface temperature (LST) variations, gaps persist integrating Landsat imagery (7 8), meteorological data, Geographic Information System (GIS) tools to evaluate effects specific LULC types, including...
Factors that affect the diffusion of lead (Pb) in zircon are still a debatable issue amongst geochronologists. These anisotropy, chemical composition, metamictization, radiation damages, and defects such as vacancy Frenkel pairs. Careful investigations effects require detailed description at atomic levels. This study focuses on details Pb pathways (anisotropy) scale level perfect lattices for better understanding thermo/petro-chronological problems geosciences. The applications Density...
Multi-temporal unmanned aerial vehicle (UAV) imagery and topographic data were used to characterize evaluate the geomorphic changes of two active landslides (Nara Nokot) in Pakistan. Ortho-mosaic images field-based investigations utilized assess geomorphological changes, including Topographic Wetness Index, slope, displacement. Volumetric specific areas measured using Geomorphic Change Detection (GCD) tool. The depletion zone Nara landslide was characterized by failures main scarps,...
The investigation of various factors effecting the Lead (Pb) diffusion in phosphate minerals such as apatite is still challenging interpretation (UTh)/Pb geochronology. For system, have closure temperatures range 375 to 600 °C and therefore can be used for mid-temperature thermochronological and/or petrochronological questions i.e., reconstruction thermal events Earth's crust. There uncertainty whether Pb characterized by thermally activated volume anisotropic profiles or instead impacted...
More recently Kohat's fold-thrust belt, including the Karak area has emerged as an important hydrocarbon fertile region of western Himalayan orogenic system. The Eocene and Paleocene strata, mechanical weak units representing a shallow decollement have noticeable contribution to deformation style petroleum system area. In present study, surface mapping is integrated with seismic information elucidate structural area, data reveal that there are two different entities, separated by Fault Zone....
The study put forward a data fusion approach for urban remote sensing that combines SAR (Synthetic Aperture Radar) and optical satellite data. By integrating datasets from different sensors spatial-temporal scales, the technique aims to extract more accurate information. utilizes two methods: feature-based fusion, where relevant features are extracted fused, simple layer stacking (SLS), original directly stacked as multiple layers. This using textures (using Sentinel-1) modified indices...