Module Objectives

Spatial Analysis is a module in the scientific fields of quantitative geography and geoinformatics. The module aims to advance the student knowledge on quantitative spatial data analysis methods and their application to real data.

– Have a clear understanding of the theoretical and practical problems concerning the application of spatial analysis methods
– Have learned Tobler’s first law of Geography and the concept of spatial autocorrelation
– Have skills in the use of R and OpenGeoDa software
– Have an overview of modern methods of spatial analysis used in the industry and in research projects in which the science of geography plays an important role

Course Contents

Spatial analysis is a broad field. This module focuses on teaching quantitative methods of exploratory and explanatory spatial data analysis. The process of analysis that adds value to spatial data in order to extract information that leads to knowledge is being taught. In this way, it is possible to understand the spatial dimension of a phenomenon.

The examples / applications discussed refer primarily to human activity in space and to a lesser extent to the natural processes in space. For example, the spatial distribution, spatial inequality and spatial variation in factors affecting issues on the labour market (unemployment and income), population (aging, internal migration), public services (health, education), retail (socioeconomic profile areas) and the environment (recycling, climate conditions) are examined.

Indicative Lectures:

– Introduction to spatial analysis
– Historical trends and schools of thought (epistemology)
– The role of GIS and Remote Sensing
– The visualization of spatial data as an analysis method
– Spatial Inequalities
– Classification, Clustering and Geodemographics
– Factor and Principal Components Analysis
– Spatial Correlation and Multicollinearity
– Spatial Autocorrelation
– Linear Regression
– Generalised Linear Models
– Discussion of advanced spatial analysis methods and research issues
– Applications in public administration and private sector

Teaching and Assessment

The teaching of this module includes lectures on theory and computer lab practice in using Statistical Analysis (R) and specialist GIS software (OpenGeoDa). Typically, teaching consists of 3-hour lectures on theory on a weekly basis while for two weeks teaching consists of one hour theory and 2 hours practical training in the computer lab.

In addition, a day or two fieldtrip is organized in order to visit an organization that uses spatial analysis methods and to do fieldwork, such as data collection. The basic evaluation method is a written exam paper at the end of the semester (3 hours).

Assessment:

The mark of the exam paper is the 50% of the final mark. Students have to write and submit an essay (up to 2000 words of text) that is an application of spatial analysis with real data. The mark of the essay is the remaining 50% of the final mark. Small essays during the fieldtrip provide extra points added to the final mark.

Teaching material:

The teaching material includes lecture presentations, notes and detailed notes for the practical exercises. Optional tutorials are offered for the students to familiarize with the software (out of the teaching hours).