Shamsa Kanwal

ORCID: 0000-0002-3670-9949
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About
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Research Areas
  • Coastal wetland ecosystem dynamics
  • Flood Risk Assessment and Management
  • Coastal and Marine Dynamics
  • Tropical and Extratropical Cyclones Research
  • Landslides and related hazards
  • Climate variability and models
  • Water resources management and optimization
  • Spatial and Panel Data Analysis
  • Urban Stormwater Management Solutions
  • Precipitation Measurement and Analysis
  • Municipal Solid Waste Management
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Fire effects on ecosystems
  • Soil and Land Suitability Analysis
  • Groundwater and Watershed Analysis
  • Aeolian processes and effects
  • Urban Transport and Accessibility
  • Income, Poverty, and Inequality
  • Hydrology and Drought Analysis

Hong Kong Polytechnic University
2018-2022

National University of Sciences and Technology
2016-2020

This study presents the use of geographical information system (GIS) datasets and methods to investigate landslide susceptibility in rugged mountainous terrain Shigar Shyok Basins northern areas Pakistan. Study area is situated Karakorum region where catastrophic landslides occur frequently pose a serious threat local living conditions. Landslide index maps were prepared by combining four main indicators groups: (1) human induced parameters, which contain Landsat 8 imagery distance from...

10.1080/19475705.2016.1220023 article EN cc-by Geomatics Natural Hazards and Risk 2016-08-24

Abstract Spatial–temporal rainfall assessments are integral to climate/hydrological modeling, agricultural studies, and water resource planning management. Herein, we evaluate spatial–temporal trends patterns in Pakistan for 1961–2020 using nationwide data from 82 stations. To assess optimal spatial distribution characterization, twenty-seven interpolation techniques geo-statistical deterministic categories were systematically compared, revealing that the empirical Bayesian kriging...

10.1038/s41598-021-86412-x article EN cc-by Scientific Reports 2021-03-25

Coastal erosion endangers millions living near-shore and puts coastal infrastructure at risk, particularly in low-lying deltaic coasts of developing nations. This study focuses on morphological changes along the ~320-km-long Sindh coastline Pakistan over past three decades. In this study, Landsat images from 1989 to 2018 an interval 10 years are used analyze state erosion. For purpose, well-known statistical approaches such as end point rate (EPR), least median squares (LMS), linear...

10.3390/rs12010008 article EN cc-by Remote Sensing 2019-12-18

This study employed remote sensing (optical and synthetic aperture radar) data analysis techniques to quantify vertical ground displacements assess their contribution coastline erosion. To provide evidence from Pakistan, we selected the coast of Karachi—a mega-city located along dynamic Indus River Delta—which has been experiencing severe coastal erosion during last few decades. Observations C-band Envisat/ASAR Sentinel-1A sensors over 2004–2010 2014–2016 periods, respectively, enabled us in...

10.3390/rs14092054 article EN cc-by Remote Sensing 2022-04-25

Karachi is located on southernmost border of Pakistan along the Arabian Sea coast. Concerned institutions fear occurrence subsidence in city, further contributing to relative sea level rise. No direct measurement has been made so far about rate and its contribution city's submergence risk. Our study presents first preliminary results vertical ground deformation over this area using an advanced Temporarily Coherent Point InSAR technique Envisat/Asar Sentinel-l A data. These datasets allowed...

10.1109/igarss.2018.8518223 article EN IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium 2018-07-01

Barrier islands (BIs) are the first line of defense against sea/wave actions in coastal areas, and assessing their stability is crucial context effective planning. Therefore, this study evaluates spatial–temporal shoreline changes BIs Pakistan over past three decades (1989–2018). Satellite data from Landsat missions used to delineate shorelines 19 Pakistan. After delineating satellite observations, two well-known statistical methods (i.e., end point rate (EPR) linear regression (LRR))...

10.3390/jmse9030295 article EN cc-by Journal of Marine Science and Engineering 2021-03-08
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