Methods of Spatial Analysis

Code:

GEOGR092

Acronym:

MANE

Keywords
Classification	Keyword
OFICIAL	Geography

Instance: 2025/2026 - 1S

Active?	Yes
Responsible unit:	Department of Geography
Course/CS Responsible:	Bachelor in Geography

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
GEOGR	17	study plan	2	-	6	41	162
			3

Teaching language

Portuguese

Objectives

1. Understand the concepts and principles of spatial analysis, including the manipulation of geographic data with different characteristics for integration into Geographic Information Systems (GIS).


2. Perform spatial analysis using raster and vector tools, including performing geometric and tabular operations on raster and vector models.


3. Apply different methods of spatial statistical analysis, including the use of various methods of comparing spatial data in GIS to obtain the degree of association between qualitative, quantitative, and classified spatial variables.


4. Develop spatial models using Model Builder and apply different spatial interpolation methods.


5. Solve spatial analysis problems geared towards land use planning, knowing how to choose the most appropriate operations and techniques.


6. Apply spatial analysis methodologies and processes based on Multicriteria Analysis.

Learning outcomes and competences

The syllabus for this course aims to provide students with basic knowledge of spatial analysis in raster and vector environments through exercises with practical examples for Geography.
It begins with the basic spatial analysis concepts in Point 1 of the syllabus. This is followed by spatial functions using vector data, as well as spatial statistics (Point 2 of the Program) to achieve learning objectives 1, 2, 3 and 5.
Point 3 of the program develops spatial analysis applied to matrix information with a view to learning objectives 1, 2, 4, 5 and 6. We then introduce spatial modelling oriented towards Geography so that students can achieve objectives 5 and 6. Ultimately, students are expected to use spatial analysis methodologies and think critically about the tools and their use in geography (objectives 5 and 6).

Working method

Presencial

Program

I. INTRODUCTION
1. Spatial analysis and GIS: introduction, definitions, concepts and applications. Recent trends.
2. Spatial data modelling. Types of models and characteristics of good models.
3. Data models and structures: vector and matrix data. Main characteristics and distinctions.
4. Introduction to the ArcGIS Model Builder

II. SPATIAL ANALYSIS AND FUNCTIONS WITH VECTOR DATA MODELS
1. vector and tabular data queries.
2. Tabular joins.
3. Geometric operations on vector models
4. Transferring attributes between different geometries, concepts and simple techniques.
5. Vector-Matrix-Vector data conversion

III. SPATIAL ANALYSIS AND FUNCTIONS WITH A MATRIX DATA MODEL
1. Concepts of resolution, mask and extent in matrix GIS analysis.
2. Types of functions: local (map algebra and reclassification), zonal and global.
3. Spatial interpolations
4. Multicriteria analysis in raster models.

Mandatory literature

George Grekousis; Spatial Analysis Methods and Practice Describe – Explore – Explain through GIS, Cambridge University Press, 2020. ISBN: ISBN: 9781108614528
Jay Gao; Fundamentals of Spatial Analysis and Modelling, CRC Press, 2022. ISBN: 9781032115757
Jacek Malczewski , Claus Rinner; Multicriteria Decision Analysis in Geographic Information Science, Springer Berlin, Heidelberg, 2015. ISBN: 978-3-540-74757-4
Manfred M. Fischer, Arthur Getis; Handbook of Applied Spatial Analysis, Springer Berlin, Heidelberg, 2010. ISBN: 978-3-642-03647-7
Michael J De Smith, Michael F Goodchild, Paul a Longley; Geospatial Analysis: A Comprehensive Guide, Winchelsea Press, 2018. ISBN: 978-1912556038

Teaching methods and learning activities

The sessions are organized in theoretical-practical classes, alternating moments of a conceptual nature, where the key concepts, themes and working methodologies are exposed, with moments of experimentation, where the theory is put into the form of a problem/chained exercise, which can be individual or in groups, and where the solutions are discussed together. The aim is to apply theoretical knowledge and promote debate, looking for possible solutions to the problem.
Assessment consists of practical group work (50%) and an exam (50%). In the practical work, students are challenged to practice the multiple methodologies covered. The exam aims to assess the theoretical concepts and methodological approaches individually.

Software

ArcMap/ArcGis Pro
QGIS

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Trabalho prático ou de projeto	50,00
Exame	50,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	64,00
Frequência das aulas	41,00
Trabalho escrito	57,00
Total:	162,00

Eligibility for exams

Mandatory attendance of 75% of classes.

Calculation formula of final grade

Practical work - 50%
Exam - 50%

Final grade of more than 7.5 in each of the evaluation components.
The final average of the two evaluation components must be positive.

Examinations or Special Assignments

Not applicable.

Special assessment (TE, DA, ...)

Students (TE, DA, ...) who are not available to attend classes, in order to pass, in addition to the exam, will have to carry out practical work that will be monitored by the UC teachers, according to a meeting plan agreed by both parties during the first month of classes.

Classification improvement

Only the theoretical component (exam) could be improved by answering a new exam.
In other cases, according to FLUP rules.