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Geoinformatics

What Will Learn?

  • Course Aims
    The aim of this course is to support students to: • Understand Spatial Data processing. • Apply Multiple Criteria Evaluation for Planning and spatial decisions. • Carry out the basic spatial analysis required for urban projects. • Perform basic statistical analysis for urban projects. • Solve problems by using contemporary tools.
  • Course Goals
  • Good Health and Well-being
  • Quality Education
  • Gender Equality
  • Clean Water and Sanitation
  • Affordable and Clean Energy
  • Decent Work and Economic Growth
  • Industry, Innovation and Infrastructure
  • Reduced Inequality
  • Sustainable Cities and Communities
  • Climate Action
  • Peace and Justice Strong Institutions

Requirements

Description

  • English Description

    Spatial Data processing – Spatial descriptive statistics – Basic concepts in spatial data analysis – Multiple Criteria Evaluation for Planning and spatial decisions – Theoretical and technical aspects of Modeling spatial data – Introduction to remote sensing – Basic satellite image processing tasks – Concepts and tools for representing data in large urban areas – Basic spatial regression models – Through Research Survey , the students will Design of the questionnaire and survey – Data management, analysis and report writing – Statistical tools and their application to survey research
  • Arabic Description

    Spatial Data processing – Spatial descriptive statistics – Basic concepts in spatial data analysis – Multiple Criteria Evaluation for Planning and spatial decisions – Theoretical and technical aspects of Modeling spatial data – Introduction to remote sensing – Basic satellite image processing tasks – Concepts and tools for representing data in large urban areas – Basic spatial regression models – Through Research Survey , the students will Design of the questionnaire and survey – Data management, analysis and report writing – Statistical tools and their application to survey research
  • Department
    Urban Planning
  • Credit Hours
    3
  • Grades
    Total ( 100 ) = Midterm (15) + tr.Major Assessment (45 = tr.Industry 0% , tr.Project 30% , tr.Self_learning 10% , tr.Seminar 5% ) + tr.Minor Assessment (5) + tr.Oral/Practical (15) + Exam Grade (20)
  • Hours
    Lecture Hours: 1, Tutorial Hours: 4, Lab Hours: 0
  • Required SWL
    125
  • Equivalent ECTS
    5
  • • Burrough, Peter A. McDonnell, Rachel A., “Principles of GIS” Oxford University Press, 2000.
  • • Cho, George: “Mastering GIS: Technology, applications and management: Geographic Information Science”, John Willy & son, Ltd, England, 2005.
  • • De Mers, Michael N., “GIS Modeling in raster” John Willy and Sons Inc., 2002.
  • • Klaus Tempfli, Norman Kerle, Gerrit C. Huurneman and Lucas L.F. Janssen, "Principles of Remote Sensing, An introductory Textbook", ITC, The Netherlands, 2009.
  • • Longley, Paul A.: “Geographic Information systems and science”, John Willy & son, Ltd, London, England, 2001.
  • • Longley, Paul A., Goodchild, Micheal F., Maguire, David J. and Rhind, David W. "Geographic Information Science and Systems" 4th Edition, 2017
  • • Otto Huisman and Rolf A. de By, "Principles of Geographic Information Systems, An introductory Textbook", ITC, The Netherlands, 2009.
  • • Reddy, G. P. and Singh, S. K. "Geotechnologies Land Resources Mapping, Monitoring and Management", Springer, 2018
  • • Reeve, Derek & Petch, James: “GIS organizations and People: A socio technical approach”, Taylor &Francis Ltd, London,1999.
  • • Shi, W., Goodchild, M., Batty, M., Kwan, M.-P., Zhang, A, “Urban Informatics”, The Urban Book Series, Springer Singapore, 2021
  • • Thakuriah P., Tilahun N., Zellner M. (eds) Seeing Cities Through Big Data. Springer Geography. Springer, Cham, 2017 - Burrough, Peter A. McDonnell, Rachel A., Principles of GIS Oxford University Press, 2000.