Lecture

Spatial Autocorrelation: An Introduction to GIS

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Description

This lecture introduces the concept of spatial autocorrelation in Geographic Information Systems (GIS), covering topics such as global spatial autocorrelation, weighting schemes, Moran's I as a regression coefficient, and contiguity ratio. It explains how to determine appropriate spatial weighting schemes, calculate global Moran's I, and evaluate its significance. The lecture also delves into the contiguity ratio and statistical mapping, exploring the use of a single index to quantify spatial autocorrelation. Additionally, it discusses neighborhood definitions for points and polygons, spatial weighting schemes, and the visualization of spatial structure through natural breaks.

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

Quiz

Related concepts (32)

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 information system

A geographic information system (GIS) consists of integrated computer hardware and software that store, manage, analyze, edit, output, and visualize geographic data. Much of this often happens within a spatial database, however, this is not essential to meet the definition of a GIS. In a broader sense, one may consider such a system also to include human users and support staff, procedures and workflows, the body of knowledge of relevant concepts and methods, and institutional organizations.

Geographic information science

Geographic information science (GIScience, GISc) or geoinformation science is a scientific discipline at the crossroads of computational science, social science, and natural science that studies geographic information, including how it represents phenomena in the real world, how it represents the way humans understand the world, and how it can be captured, organized, and analyzed. It is a sub-field of geography, specifically part of technical geography.

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).

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.

Related lectures (64)

Spatial Autocorrelation: Moran's I

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Discrete variables: Geometric properties MOOC: Geographical Information Systems 2

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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 variables in geographic information systems and their geometric properties, including spatial arrangement and autocorrelation.

Spatial Autocorrelation: Spatial Weighting