Lecture

Geospatial Data Analysis: GeoDa Software

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture covers the main functions of the GeoDa software for exploratory analysis of vector data attributes. Students learn to create thematic maps, histograms, box plots, scatter plots, and perform spatial autocorrelation and regression calculations. The unique feature of GeoDa is its dynamic interaction, known as brushing, which allows combining different representation tools during analysis.

In MOOC

Geographical Information Systems 2

The second part of the course deals with spatial analysis methods and georeferenced information representation techniques. In particular, you will learn how to:

Analyze the spatial properties of discrete variables, for example by quantifying spatial autocorrelation;
Work with continuous variables (sampling, interpolation and construction of isolines)
Use digital elevation models (DEMs) and their derivatives (slope, orientation, etc.);
Use geodata superposition techniques;
Produce cartographic docu

Official source

Related concepts (10)

Data analysis

Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.

Thematic map

A thematic map is a type of map that portrays the geographic pattern of a particular subject matter (theme) in a geographic area. This usually involves the use of map symbols to visualize selected properties of geographic features that are not naturally visible, such as temperature, language, or population. In this, they contrast with general reference maps, which focus on the location (more than the properties) of a diverse set of physical features, such as rivers, roads, and buildings.

Exploratory data analysis

In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts traditional hypothesis testing. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments.

Spatial analysis

Spatial analysis is any of the formal techniques which studies entities using their topological, geometric, or geographic properties. Spatial analysis includes a variety of techniques using different analytic approaches, especially spatial statistics. It may be applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, or to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures.

Geographic data and information

Geographic data and information is defined in the ISO/TC 211 series of standards as data and information having an implicit or explicit association with a location relative to Earth (a geographic location or geographic position). It is also called geospatial data and information, georeferenced data and information, as well as geodata and geoinformation. Approximately 90% of government sourced data has a location component. Location information (known by the many names mentioned here) is stored in a geographic information system (GIS).

Related lectures (45)

Geoda Software: Geospatial Data Analysis

Covers the GeoDa software for geospatial data analysis and thematic mapping.

Structuring exploratory spatial data analysis

Explores the structured approach to exploratory spatial data analysis, emphasizing the importance of analytical frameworks and the Visual Seeking Mantra.

Analysis of Geographic Information: GeoDa MOOC: Geographical Information Systems 2

Covers the main functions of the GeoDa software for exploratory analysis.

Introduction: ESDA in environmental health

Introduces exploratory data analysis in environmental health, covering its definition, techniques, and applications in georeferenced health data analysis.

Thematic Attributes and Classification