Muhammad Salem

Lecturer

Cairo University, Faculty of Urban and Regional Planning (email)

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Deep Learning approach for Modeling Land Use/Land Cover Change Using Remote Sensing Techniques

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  • Deep Learning
  • Land Use Land Cover Change
  • Remote Sensing
Citation:
Salem, M., & Tsurusaki N. (2021).  Deep Learning approach for Modeling Land Use/Land Cover Change Using Remote Sensing Techniques. International Symposium on Earth Science and Technology 2021. 250-253.
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  • Assessment (1)
  • Deep Learning (1)
  • Greater Cairo Region (1)
  • Land Use Land Cover Change (1)
  • Peri-Urban Area (1)
  • Remote Sensing (1)
  • Sustainable Development (1)

Recent Publications

Deep Learning approach for Modeling Land Use/Land Cover Change Using Remote Sensing Techniques
Voluntary Local Review Framework to Monitor and Evaluate the Progress towards Achieving Sustainable Development Goals at a City Level: Buraidah City, KSA and SDG11 as A Case Study
Urban Expansion Simulation Based on Various Driving Factors Using a Logistic Regression Model: Delhi as a Case Study
Urban Areas Management in Developing Countries: Analysis of the Urban Areas Crossed with Risk of Storm Water Drains, Aswan-Egypt
{Detection of Slums from Very High-Resolution Satellite Images Using Machine Learning Algorithms: A Case Study of Fustat Area in Cairo, Egypt}
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