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Spatial Data Analysis: Course Outline Ifgi, Muenster, Fall School 2005 Gilberto Câmara INPE, Brazil.

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Presentation on theme: "Spatial Data Analysis: Course Outline Ifgi, Muenster, Fall School 2005 Gilberto Câmara INPE, Brazil."— Presentation transcript:

1 Spatial Data Analysis: Course Outline Ifgi, Muenster, Fall School 2005 Gilberto Câmara INPE, Brazil

2 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

3 CBERS-2 Launch (21 October 2003) CBERS-2

4 CBERS-2 CCD, Minas Gerais, Brazil

5 CBERS-2 image from Louisiana, EUA Obtained from on-board data recorder

6 Amazon Deforestation 2003 Fonte: INPE PRODES Digital, Deforestation 2002/2003 Deforestation until 2002

7 source: Greenpeace Amazônia in 2005

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

9 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

10 Course outline Motivation: why do need spatial data analysis? Point pattern analysis Areal data analysis Surface data analysis (geostatistics) Trends in spatial data analysis

11 Course outline: 1 st 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)

12 Course outline: 2 nd 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

13 Course material Course homepage   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)  TerraLib – GIS library (open source)


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