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المقررات الدراسية المتاحة

1.     Introductory information:

Module Name

Environmental GIS

Module Code

EnviGIS2024

Module Type

Requisite

Hours per week

Theory (2 Hours), Tutorial Click or tap here to enter text., practical (2 Hours)

No. of ECTS

6

Semester

2

Lecturer(s) in charge

Yaseen T. Mustafa

Academic Title

Professor

Qualification

PhD

Department

Environmental Science

Faculty /College

College of Science

Contact details

E-mail address: yaseen.mustafa@uoz.edu.krd

Mobile Number: +9647504922553

 

2.     Module Overview:

This module is designed to equip students with the knowledge and skills necessary to apply Geographic Information Systems (GIS) in environmental contexts. It covers the fundamentals of GIS, including spatial data types, data collection, and analysis, along with advanced techniques tailored for environmental applications. Through a combination of lectures, hands-on lab sessions, and project work, students will learn how to utilize GIS technology to address complex environmental challenges, from conservation and resource management to climate change and sustainability.

 

3.     Module Objective:

·       Understand the Principles of GIS: Grasp the core concepts, technologies, and methodologies underlying GIS, focusing on spatial data models, database management, and geospatial analysis.

·       Apply GIS to Environmental Issues: Learn to employ GIS tools and techniques in solving real-world environmental problems, such as habitat mapping, pollution tracking, and impact assessment.

·       Develop Technical GIS Skills: Acquire practical skills in GIS software for environmental data analysis, including data visualization, spatial analysis, and modeling.

·       Integrate Multidisciplinary Data: Master the art of integrating various types of environmental data into GIS for comprehensive analysis and decision-making.

·       Conduct Environmental Research Using GIS: Gain the ability to design and execute GIS-based environmental research projects, from hypothesis formulation to data presentation.

 

 

4.     Assessment Strategy:

Task(s)

Status

Number

Marks

Presentation

(√)

1

10

Reports

(×)

 

 

Assignments

(√)

4

10

Quizzes

(×)

Choose an item.

 

Projects

(×)

 

 

Homework

(√)

4

10

Mid-term examination

(√)

1

20

Review Article

(×)

 

 

Final examination

(√)

1

50

Others

 

 

 

 

5.     Learning OUTCOMES:

Upon successful completion of this module, students will be able to:

·       Demonstrate Proficiency in GIS Software: Efficiently use GIS software tools to collect, manage, analyze, and visualize environmental spatial data.

·       Solve Environmental Problems: Apply GIS methodologies to identify, analyze, and propose solutions to environmental issues, demonstrating critical thinking and problem-solving skills.

·       Conduct Spatial Analysis: Perform advanced spatial analyses pertinent to environmental sciences, such as landscape fragmentation, watershed analysis, and species distribution modeling.

·       Communicate GIS Findings: Effectively communicate the results of GIS analyses to diverse audiences through maps, reports, and presentations, showcasing data visualization skills.

·       Engage in Interdisciplinary Collaboration: Collaborate across disciplines by integrating ecological, geological, and atmospheric data within GIS projects, fostering interdisciplinary understanding and teamwork.

 

6.     Teaching and Learning Methods:

The teaching methods that will be used in this module include:

-        Lecture;

-        Labs;

-        Small group discussion;

-        Assignments;

-        Homework

 

7.     Module Reading List and References:

(Press Minnesota)”

  • de By, R. A., Knippers, R. A., Weir, M. J. C., Georgiadou, Y., Kraak, M. J., Westen, C. J. V., et al. (2004). Principles of Geographical Information Systems: An introductory textbook (3rd  ed. Vol. 1). Enschede: ITC.
  • Johnston, K., Ver Hoef, J. M., Krivoruchko, K., & Lucas, N. (2001). Using ArcGIS Geostatistical Analyst. New York: ESRI Press.
  • Köhl, M., Magnussen, S., & Marchetti, M. (2006). Sampling methods, remote sensing and GIS multiresource forest inventory. Berlin ; London: Springer.
  • Krygier, J., & Wood, D. (2005). Making maps: a visual guide to map design for GIS. New York: Guilford Press.

 

 

8.     Syllabus:

In this section the lecture has to show precisely the contents of the module that s/he presents during the whole semester.  NOTE: the tasks listed in section (4) have to be included.

Weeks

Topic(s)/ Theoretical

Topic(s)/ Practical

1.       

Introduction to the Module

Expectations with respect to Reports and Labs

2.       

Introduction to GIS and its Applications

Fundamentals of ArcGIS - I

3.       

Spatial Data Structures

Fundamentals of ArcGIS – II
(Assign. #01)

4.       

Coordinate System & Attribute Data Structure

Projections and Geo-Positioning
(Assign. #02)

5.       

Map, Layouts, and Data Output (Homework #01)

Creating Maps and a Layout in ArcGIS (Assign. #03)

6.       

Spatial Data Input & Preparation

Aerial Photo Mapping and Digitizing

(Assign. #04)

7.       

Global Positioning Systems

Spatial Operations I - (Suitability Analysis)

(Assign. #05)

8.       

Elementary Geoprocessing (Suitability Analysis)

Spatial Operations II –

(Raster & Surface Analysis)

9.       

Mid-Term Exam

10.    

Spatial Interpolation and Prediction (Homework #02)

Learning how to build a GIS: Shapefile + surface interpolation

 (Assign. #06)

11.    

Network Analysis

 

Construct & Manipulate DEMs using ArcGIS (Assign. #07)

 

12.    

GIS-based Multi-Criteria Decision Analysis

Creating TIN and 3D scenes (ArcScene)  (Assign. #08)

13.    

Applications: Soil, Meteorological Data

(Homework #03)

Network Analyst: Spatial Computation in a Constrained Network (Assign. #09)

14.    

Application: GIS-MCDA

(Homework #04)

Application: GIS and MCDA in Soil Waste landfill site selection (Assign. #10)

15.    

Article Review: presentation

Application: GIS and MCDA in forest planning

16.    

Final Exam

Final Exam

 


Numerical Analysis
شيكردنا ژمارەیی
التحليل العددي
by Bewar Y. Ali

           This course introduces students to classical numerical methods for approximating the solutions of problems in science, engineering, and mathematics through the use of computers. It allows students to deal with numerical methods both at a theoretical level and for programming purposes.