Mohamed H. Aly Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Professor

University of Arkansas at Fayetteville

faculty

20 h-index 92 pubs 1,100 cited

Research Areas

Machine Learning Applications Remote Sensing and Satellite Data Forest Monitoring and Management Land Use and Land Cover Dynamics Wildfire Susceptibility Modeling Data Fusion Techniques Environmental Monitoring Meta-analysis and systematic reviews

Links

ORCID Research Group

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OverviewAI-generated summary

Mohamed H. Aly's research focuses on the application of machine learning and data fusion techniques for environmental monitoring and analysis. He has investigated machine learning models for predicting wildfire susceptibility in Arkansas, utilizing satellite data and Google Earth Engine for enhanced tree species mapping and forest monitoring. His work also includes systematic reviews of machine learning applications in assessing land use/cover dynamics and their impact on land surface temperatures, as well as estimating forest above-ground biomass in Arkansas using multisensor data fusion. Aly has also explored big data analyses for tracking spatio-temporal trends of air pollution from wildfires in California and integrated modeling frameworks for forecasting land use and land cover dynamics. Additionally, his research has touched upon the use of synthetic aperture radar for bathymetric mapping in nearshore coastal waters.

Metrics

  • h-index: 20
  • Publications: 92
  • Citations: 1,100

Selected Publications

  • Contrasting Radar Scattering Regimes in Titan and Earth's Aeolian Dunes (2025) DOI
  • Contrasting Radar Scattering Regimes in Titan and Earth's Aeolian Dunes (2025) DOI
  • An Integrated CA–Markov Modeling Framework for Forecasting Land Use and Land Cover Dynamics in Arkansas, USA (2025) DOI
  • Machine Learning and Multisensor Data Fusion for Forest above Ground Biomass Estimation in Arkansas (2025) DOI
  • A Comprehensive Systematic Review of Machine Learning Applications in Assessing Land Use/Cover Dynamics and Their Impact on Land Surface Temperatures (2025) DOI
  • GEOSPATIAL ASSESSMENT OF FLASH FLOOD SUSCEPTIBILITY IN MAKKAH, SAUDI ARABIA (2025) DOI
  • SYNTHETIC APERTURE RADAR FOR BATHYMETRIC MAPPING IN NEARSHORE COASTAL WATER (2025) DOI
  • OPERATIONAL FLOOD HAZARD MAPPING AND IMPACT ASSESSMENT IN BANGLADESH USING SENTINEL-1, MODIS, AND GOOGLE EARTH ENGINE (2020-2024) (2025) DOI
  • FLASH FLOOD SUSCEPTIBILITY ANALYSIS IN JEDDAH, SAUDI ARABIA, USING A GIS-BASED AHP APPROACH (2025) DOI
  • Enhancing Tree Species Mapping in Arkansas’ Forests Through Machine Learning and Satellite Data Fusion: A Google Earth Engine–Based Approach (2025) DOI
  • Fusion-Based Approaches and Machine Learning Algorithms for Forest Monitoring: A Systematic Review (2025) DOI
  • Enhancing Tree Species Mapping in Arkansas' Forests through Machine Learning and Satellite Data Fusion: A Google Earth Engine-Based Approach  (2024) DOI
  • MULTISENSOR SATELLITE DATA FUSION AND MACHINE LEARNING FOR ESTIMATING AND EXTRAPOLATING ABOVE-GROUND BIOMASS IN ARKANSAS FORESTS (2024) DOI
  • HIGH-RESOLUTION FLOOD MAPPING IN NORTHWEST ARKANSAS USING LIDAR AND GOOGLE EARTH ENGINE (2024) DOI
  • Big data analyses for determining the spatio-temporal trends of air pollution due to wildfires in California using Google Earth Engine (2024) DOI

Collaborators

Researchers in the database who share publications

Abdullah Al Saim University of Arkansas at Fayetteville 6 shared publications Rasool Vahid University of Arkansas at Fayetteville 2 shared publications

Similar Researchers

Based on overlapping research topics

Rasool Vahid University of Arkansas at Fayetteville
Machine Learning Applications Land Use and Land Cover Dynamics Meta-analysis and systematic reviews
Related 3 shared topics