A5034160184- Flood Risk Assessment and Management
- Land Use and Ecosystem Services
- Urban Heat Island Mitigation
- Remote Sensing in Agriculture
- Hydrology and Drought Analysis
- Hydrology and Watershed Management Studies
- Soil erosion and sediment transport
- Remote Sensing and Land Use
- Remote Sensing and LiDAR Applications
- Plant Parasitism and Resistance
- Conservation, Biodiversity, and Resource Management
- Distributed systems and fault tolerance
- Plant Molecular Biology Research
- Coastal wetland ecosystem dynamics
- Remote-Sensing Image Classification
- Plant Micronutrient Interactions and Effects
- Tropical and Extratropical Cyclones Research
- Disaster Management and Resilience
- Infrastructure Resilience and Vulnerability Analysis
- Groundwater and Watershed Analysis
- Silicon Effects in Agriculture
- Plant responses to water stress
- Fire effects on ecosystems
- Aeolian processes and effects
- Hydrology and Sediment Transport Processes
Hong Kong Baptist University
2022-2025
COMSATS University Islamabad
2021-2022
Phytohormones (PHs) play crucial role in regulation of various physiological and biochemical processes that govern plant growth yield under optimal stress conditions. The interaction these PHs is for survival stressful environments as they trigger signaling pathways. Hormonal cross initiate a cascade reactions which finely tune the architecture help to grow suboptimal Recently, studies have highlighted such abscisic acid, salicylic ethylene, jasmonates responses toward environmental...
Abstract Land use changes profoundly affect hydrological processes and water quality at various scales, necessitating a comprehensive understanding of sustainable resource management. This paper investigates the implications land alterations in Gap-Cheon watershed, analyzing data from 2012 2022 predicting up to 2052 using Future Use Simulation (FLUS) model. The study employs Hydrological Program-FORTRAN (HSPF) model assess quantity dynamics. Seven classes were identified, their evolution was...
Abstract Timely and accurate estimation of rice-growing areas forecasting production can provide crucial information for governments, planners, decision-makers in formulating policies. While there exists studies focusing on paddy rice mapping, only few have compared multi-scale datasets performance classification. Furthermore, mapping large geographical with sufficient accuracy planning purposes has been a challenge Pakistan, but recent advancements Google Earth Engine make it possible to...
Urbanization-led changes in land use cover (LULC), resulting an increased impervious surface, significantly deteriorate urban meteorological conditions compromising long-term sustainability. In this context, we leverage machine learning, spatial modelling, and cloud computing to explore predict the changing patterns growth associated thermal characteristics Bahawalpur, Pakistan. Using multi-source earth observations (1990–2020), field variance index (UTFVI) is estimated evaluate heat island...
Abstract The rapid increase in urbanization has an important effect on cropping pattern and land use/land cover (LULC) through replacing areas of vegetation with commercial residential coverage, thereby increasing the surface temperature (LST). LST information is significant to understand environmental changes, urban climatology, anthropogenic activities, ecological interactions, etc. Using remote sensing (RS) data, present research provides a comprehensive study LULC changes water scarce...
Gully erosion is a serious threat to the state of ecosystems all around world. As result, safeguarding soil for our own benefit and from actions must guaranteeing long-term viability variety ecosystem services. developing gully susceptibility maps (GESM) both suggested necessary. In this study, we compared effectiveness three hybrid machine learning (ML) algorithms with bivariate statistical index frequency ratio (FR), named random forest-frequency (RF-FR), support vector machine-frequency...
Soil erosion triggered by water and wind pose a great threat to the sustainable development of Pakistan. In this study, combination geographic information systems (GISs) machine learning approaches were used predict soil rates. The Revised Wind Erosion Equation (RWEQ) model was evaluate erosion, map factors, analyze rates for each land use type. Finally, maps spatially integrated identify risk regions recommend management in According our estimates, Potohar Plateau its surrounding mostly...
Abstract Flood susceptibility mapping (FSM) is crucial for effective flood risk management, particularly in flood‐prone regions like Pakistan. This study addresses the need accurate and scalable FSM by systematically evaluating performance of 14 machine learning (ML) models high‐risk areas The novelty lies comprehensive comparison these use explainable artificial intelligence (XAI) techniques. We employed XAI to identify significant conditioning factors at both model training prediction...