Lecture

Structuring exploratory spatial data analysis

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In course

ENV-444: Exploratory data analysis in environmental health

This course teaches how to apply exploratory spatial data analysis to health information. Teaching focuses on the role of GIS and spatial statistics in spatial epidemiology. It proposes a context to investigate the relationship between health, quality of l ...

Description

This lecture explores the components of exploratory spatial data analysis (ESDA), focusing on tools, tasks, and data. It delves into the structured approach developed by geoscientists to formalize ESDA, emphasizing the importance of analytical frameworks in investigating spatial data. The lecture covers reference and descriptive sub-components, elementary and synoptic tasks, as well as cognitive and perceptive abilities, data visualization, display manipulation, data manipulation, queries, and computation. It also discusses question types, levels of reading, combinations of reading levels, and the principles guiding ESDA. The presentation concludes by highlighting the significance of levels of readings and the Visual Seeking Mantra as guidelines for effective exploratory analysis.

Instructors (2)

Stéphane Joost

Expertise Geographic Information Science and spatial statisticsMolecular ecology, Landscape genomics, Seascape genomicsSpatial epidemiology, Health geographics Publications Publications- List of publications Teaching & PhD PhD Students Marco André Vieira Ruas, Manon Laetitia Pribille, Martine Valérie Besse Past EPFL PhD Students Estelle Rochat, Solange Catherine Gaillard, Oliver Michele Selmoni, Anaïs Ladoy, Annie Sandrine Guillaume Past EPFL PhD Students as codirector Sylvie Stucki, Kevin Leempoel, Martí

Idris Guessous

Official source

Related concepts (32)

Data and information visualization

Data and information visualization (data viz or info viz) is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items.

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.

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.

Scientific visualization

Scientific visualization (also spelled scientific visualisation) is an interdisciplinary branch of science concerned with the visualization of scientific phenomena. It is also considered a subset of computer graphics, a branch of computer science. The purpose of scientific visualization is to graphically illustrate scientific data to enable scientists to understand, illustrate, and glean insight from their data.

Visualization (graphics)

Visualization or visualisation (see spelling differences) is any technique for creating s, diagrams, or animations to communicate a message. Visualization through visual imagery has been an effective way to communicate both abstract and concrete ideas since the dawn of humanity. from history include cave paintings, Egyptian hieroglyphs, Greek geometry, and Leonardo da Vinci's revolutionary methods of technical drawing for engineering and scientific purposes. Visualization today has ever-expanding applications in science, education, engineering (e.

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