Ifgi, Muenster, Fall School 2005
Spatial Data Analysis:
Course Outline
Gilberto Câmara
INPE, 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
CBERS-2 Launch
(21 October 2003)
CBERS-2 CCD, Minas Gerais, Brazil

CBERS-2
image from
Louisiana, EUA

Obtained from
on-board data
recorder
Amazon Deforestation 2003
Deforestation 2002/2003
Deforestation until 2002
Fonte: INPE PRODES Digital, 2004.
Amazônia in 2005
source: Greenpeace
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


Tuesday – Basic concepts


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)
Thursday – Areal analysis II


10:30 – 12:00 (2)
Wednesday – Areal analysis I (LAB work)


10:30 – 12:00 (2)
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)


Tuesday – Surface analysis (LAB)


9:00 – 10:30 and 11:00 – 12:30 (4)
Friday – Trends in spatial data analysis


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)
Wednesday – Surface analysis II (LAB)


10:30 – 12:00 (2)
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)



GeoDa – analysis of areal data (gratis)
TerraView – visualisation and analysis (open source)


www.r-project.org
www.terralib.org
TerraLib – GIS library (open source)