Lecture

Spatial Dependence and Autocorrelation

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Description

This lecture explains spatial dependence, highlighting how nearby objects are more likely to interact than distant ones, and how environmental characteristics can influence certain attributes, making geographic space non-neutral. It also discusses the paradox of statistical tools requiring neutral space, and introduces the concept of spatial autocorrelation and its significance determination.

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

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