1) This document discusses the principles of spatial analysis in Geographic Information Systems (GIS). It covers topics like feature and attribute data, types of attribute values, patterns and processes in spatial analysis, and the principle steps in GIS spatial analysis. 2) The principle steps in GIS spatial analysis include spatial data manipulation, descriptive and exploratory spatial data analysis, spatial statistical analysis, and spatial modeling. 3) Potential pitfalls in spatial analysis that can affect results are also examined, such as spatial autocorrelation, the modifiable areal unit problem, and issues of scale and non-uniformity of space.

1. 1
SIG Pertambangan
(Theory of Spatial Analysis : Principle Steps in GIS Spatial)
Oleh :
Irvani
Universitas Bangka Belitung Jurusan Teknik Pertambangan
SKS, Penilaian & Kehadiran :
Banyaknya SKS = 2 SKS (Teori)
Penilaian :
- Absensi 10%
- Tugas 20%
- Teori (UTS & UAS) 70%
Kehadiran minimal 75% dari 14x perkualiahan
Universitas Bangka Belitung Jurusan Teknik Pertambangan

2. 2
Referensi :
Universitas Bangka Belitung Jurusan Teknik Pertambangan
• Bonham-Carter, G.F. (1994) Geographic Information System for Geoscientists: Modelling
with GIS. Delta Printing , Ontario, 398 p.
• Harris, J.R. (ed) (2006) GIS For The Earth Sciences. GAC Special Paper 44, Geological
Association of Canada, 616 p.
• de By, R.A. (ed) (2000) Principles of Geographic Information Systems. ITC educational
Texbook Series, Netherlands.
• Huisman, O. And de By, R.A. (2009) Principles of Geographic Information Systems. ITC
educational Texbook Series, Netherlands.
• Mitchel, A. (1999) The ESRI guide to GIS Analysis. Volume 1: Geographic patterns &
Relationships, ESRI Press, 186 pp.
• Kennedy, H. (ed) (2001) Dictionary of GIS terminology. ESRI Press, Redlands, 116 p.
• Longley, P.A., Goodchild, M.F., Maguire, D.J. and Rhind, D.W. (2001) Geographic
Information Systems and Science. John Wiley & Sons, 454 pp.
• Maguire, D. J., Goodchild, M. F., and Rhind, D. W. (eds) (1991) Geographical information
systems: principles and applications, Longman.
• Zeiler, M. (1999) Modeling Our World: the ESRI Guide to Geodatabase Design. ESRI Press,
Redlands, 198 p.
• ESRI Homepage ( http://esri.com/index.html ) : understanding GIS, industry applications,
user conference, virtual campus, ESRI Press books
Materi/Pokok Bahasan
I Pendahuluan (P.1)
II Overview of GIS (P.2)
III Map Projection and
Coordinate System (P.3-4)
IV GIS for Geoscience (P.5)
V GIS Database (P.6)
VI Theory of Spatial Analysis (P.7-9)
a. Metode AHP
b. Principle Steps
in GIS Spatial
c. GIS Processing
VII Introduction to ArcGIS or
MapInfo (P.10) (Option)
VIII Case Studies/Latihan (P.11-14)
Universitas Bangka Belitung Jurusan Teknik Pertambangan

3. 3
Thematic Layers and Datasets
2
Feature vs. Attribute Data
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4. 4
Types of Attribute Values
1.
2.
Text
Data measurements:
1.
2.
3.
4.
Ratio
Interval
Ordinal
Nominal
4
Types of Attribute Data
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5. 5
Types of AttributeData
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Types of Attribute Data
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6. 6
Types of Attribute Data
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Pattern, Process and Spatial Analysis
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Process, Pattern and Analysis
• Processes operating in space
patterns
produce
• Spatial Analysis is aimed at:
describing the
understanding
–
–
Identifying
Identifying
and
and
pattern
the process
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Spatial Analysis: successive levels of sophistication
1. Spatial data manipulation: classic GIS capabilities
– Spatial queries & measurement, buffering, map layer
overlay
Spatial data analysis: descriptive and exploratory2.
– Visualization through data manipulation and mapping
• John Snow’s maps of cholera in 1850s London
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8. 8
Spatial Analysis: successive levels of sophistication
3. Spatial statistical analysis: hypothesis testing
– Are data “to be expected” or are they “unexpected”
relative to some statistical model, usually of a random
process
Spatial modeling: prediction4.
– Constructing models
outcomes (patterns)
(of processes) to predict spatial
– What if analyses
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The Pitfalls of Spatial Analysis
Spatial autocorrelation•
–
–
Data from location near to each other are more likely to be similar than data from location remote from
each other
Causes serious problems with traditional statistical models
• Spatial statistical models are essential
• Modifiable areal unit problem (MAUP)
– Results may depend on the areal unit used
•
•
Census tracts versus counties (scale issue)
Census tracts versus zip codes (not a scale issue)
• Ecological fallacy
–
–
–
Results obtained from aggregated data (e.g. census tracts) cannot be assumed to apply to individual
people
A special case of the MAUP problem
Encountered in spatial and non-spatial analysis
• Scale affects representation and results
–
–
Cities may be points or polygons
MAUP may be viewed as a scale issue
• Non-uniformity of Space and Edge Issues
–
–
Phenomena is not distributed evenly in space
Edges, beyond which there is no data, can significantly effect results
• Bank robberies cluster ‘because banks are clustered in space
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9. 9
Principle Steps
in GIS Spatial Analysis
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