Lecture

Autocorrelation and Spatial Dependence

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Description

This lecture explains spatial dependence, emphasizing how nearby objects interact more than distant ones, influencing certain attributes. It discusses the non-neutrality of geographic space, a paradox for statistical tools that assume neutrality. The instructor demonstrates implementing a spatial autocorrelation measure and determining its significance.

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 (7)

Autocorrelation

Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations of a random variable as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies.

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.

Partial autocorrelation function

In time series analysis, the partial autocorrelation function (PACF) gives the partial correlation of a stationary time series with its own lagged values, regressed the values of the time series at all shorter lags. It contrasts with the autocorrelation function, which does not control for other lags. This function plays an important role in data analysis aimed at identifying the extent of the lag in an autoregressive (AR) model.

Geography

Geography (from Greek: γεωγραφία, geographia. Combination of Greek words 'Geo' (The Earth) and 'Graphien' (to describe), literally "earth description") is a field of science devoted to the study of the lands, features, inhabitants, and phenomena of Earth. Geography is an all-encompassing discipline that seeks an understanding of Earth and its human and natural complexities—not merely where objects are, but also how they have changed and come to be.

Geographical feature

A feature (also called an object or entity), in the context of geography and geographic information science, is a discrete phenomenon that exists at a location in the space and scale of relevance to geography; that is, at or near the surface of Earth, at a moderate to global scale. It is one of the primary types of phenomena represented in geographic information, such as that represented in maps, geographic information systems, remote sensing imagery, statistics, and other forms of geographic discourse.

Related lectures (8)

Spatial Entities and Geographic Information Systems MOOC: Geographical Information Systems 1

Explores spatial entities, vector mode, and spatial information in GIS.

Spatial Dependence: Autocorrelation and Analysis

Introduces spatial dependence, the paradox of classical statistics, and the bias in linear regression.

Discrete Variables: Geometric Properties MOOC: Geographical Information Systems 2

Covers discrete geographic variables and their geometric properties, including form indices like the Gravelius index.

Spatial Dependence and Autocorrelation MOOC: Geographical Information Systems 2

Explores spatial dependence, the paradox of neutral space, and spatial autocorrelation.

Spatial Autocorrelation: Moran's I