Spatial Data Analysis: Course Outline

Ifgi, Muenster, Fall School 2005

Gilberto CâmaraINPE, Brazil

INPE - brief description

National Institute for Space Research main civilian organization for space activities in

Brazil staff of 1,800 ( 800 Ms.C. and Ph.D.)

Areas: Space Science, Earth Observation, Meteorology

and Space Engineering

CBERS-2 Launch(21 October 2003)

CBERS-2

CBERS-2 CCD, Minas Gerais, Brazil

CBERS-2 image from Louisiana, EUA

Obtained from on-board data recorder

Amazon Deforestation 2003

Fonte: INPE PRODES Digital, 2004.Fonte: INPE PRODES Digital, 2004.

Deforestation 2002/2003Deforestation 2002/2003

Deforestation until 2002Deforestation until 2002

source: Greenpeace

Amazônia in 2005

Amazônia in 2015? fonte: Aguiar et al., 2004

R&D in GIScience at INPE

Graduate programs in Computer Science and Remote Sensing

Research areas Spatial statistics Spatial dynamical modelling Spatio-temporal databases Image databases and image processing

Technology TerraLib – open source library for ST DBMS

Course outline

Motivation: why do need spatial data analysis?

Point pattern analysis

Areal data analysis

Surface data analysis (geostatistics)

Trends in spatial data analysis

Course outline: 1st week

Monday – Introduction 10:30 – 12:00 (2)

Tuesday – Basic concepts 10:30 – 12:00 (2)

Wednesday – Areal analysis I (LAB work) 9:00 – 10:30 and 11:00 – 12:30 (4)

Thursday – Areal analysis II 9:00 – 10:30 and 11:00 – 12:30 (4)

Friday – Areal analysis III (LAB work) 9:00 – 10:30 and 11:00 – 12:30 (4)

Saturday – QUIZ 14:00 – 17:00 (LAB)

Course outline: 2nd week

Monday – Introduction to R (LAB) 10:30 – 12:00 (2)

Tuesday – Surface analysis (LAB) 9:00 – 10:30 and 11:00 – 12:30 (4)

Wednesday – Surface analysis II (LAB) 9:00 – 10:30 and 11:00 – 12:30 (4)

Thursday – Point pattern analysis (LAB) 9:00 – 10:30 and 11:00 – 12:30 (4)

Friday – Trends in spatial data analysis 10:30 – 12:00 (2)

Saturday – Quiz 14:00 – 17:00

Course material

Course homepage www.dpi.inpe.br/gilberto/tutorials.html Bailey and Gattrel, “Spatial Data Analysis by example”

Software R – statistical suite (open source)

www.r-project.org GeoDa – analysis of areal data (gratis) TerraView – visualisation and analysis (open source)

www.terralib.org TerraLib – GIS library (open source)