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Spatial Data Analysis: Course Outline

This course provides an in-depth exploration of spatial data analysis techniques. Delivered as part of the Fall School 2005 at INPE, Brazil, it covers fundamental concepts such as point pattern analysis, areal data analysis, surface data analysis using geostatistics, and emerging trends in spatial analysis. Participants engage in hands-on laboratory work, introducing tools like R, GeoDa, and TerraLib. Key objectives include understanding the significance of spatial data and acquiring practical skills in spatial statistics and visualization.

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Spatial Data Analysis: Course Outline

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  1. Ifgi, Muenster, Fall School 2005 Spatial Data Analysis: Course Outline 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 CBERS-2 Launch (21 October 2003)

  4. CBERS-2 CCD, Minas Gerais, Brazil

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

  6. Amazon Deforestation 2003 Deforestation 2002/2003 Deforestation until 2002 Fonte: INPE PRODES Digital, 2004.

  7. Amazônia in 2005 source: Greenpeace

  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: 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)

  12. 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

  13. 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)

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