Report based on the project conducted by the students of Kathmandu University on the Open Street Map datasets.

1. Mid-Term Presentation on
DATA QUALITY ASSESSMENT OF OSM MAP OF
KATHMANDU
Department of Civil and Geomatics Engineering
Kathmandu University
Dhulikhel, Kavre
Members (Group (5))
Shaswat Kafle (11)
Maheshwor Karki (14)
Suresh Manandhar (17)
Dipesh Suwal (29)
Project Supervisor
Mr. Sashish Maharjan
Mr. Nawaraj Shrestha
Project In charge
Prof. Dr. Ramesh Kumar Maskey

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PRESENTATION OUTLINES
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Background
Introduction
Rationale
Study Area
Objectives
Methodology
Resources Required
Project Schedule
Outcomes
Limitations
Conclusions
References
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BACKGROUND
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OSM is open source map can be prepared by anybody
Higher the accuracy of map, higher the use of that map
On the basis of quality of map they are used in various
project
In Nepal the accuracy of OSM map has not been mentioned.
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INTRODUCTION
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Data quality assessment means to check the accuracy in various
quality aspects of the map and gives the knowledge how much that
map can be trusted.
Aspects
• Positional accuracy
• Logical consistency
• Temporal accuracy
• Thematic accuracy
• Purpose
• Usage
• Lineage(how data was collected and evolved)
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RATIONALE
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The use of OSM map has been increasing day by day.
But we aren’t aware about the quality of map.
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STUDY AREA
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STUDY AREA
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STUDY AREA
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Kathmandu is the capital and largest metropolitan
city of Nepal
Our project deals within Ringroad of Kathmandu
valley.
Length of ringroad is approximately 27 km.
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OBJECTIVES
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To find the accuracy of OSM map of our project site
Sub-Objective
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Use of map in other projects such as disaster risk management
, planning, tourism, navigation and others.
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METHODOLOGY
Data Collection
OSM
Digital Map
Data Preparation
OSM in .shp file
Road Network Analysis
• Positional Accuracy
• Attribute Accuracy
Coordinate system
Data Analysis
Building Analysis
• Positional Accuracy
• Attribute Accuracy
Data Validation
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METHODOLOGY
DATA COLLECTION
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Openstreesmap and Survey Department map
Downloaded map from Openstreetmap Bulidings and Road
shape file from http://BBBike.orgosmium2shape on Wed Apr
3 2013 08:19:41
Survey Department map from Survey Department of Nepal
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METHODOLOGY
Openstreetmap
Survey Department Map
Road Map
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METHODOLOGY
Openstreetmap
Survey Department Map
Building Map
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METHODOLOGY
Meta Data of Survey Department Map
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Topographic map of Nepal
Datum: Everest Bangladesh
projection system :MUTM
Meta Data of Openstreetmap
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Volunteered geographic information
Datum:WGS84
projection System: Geographic Coordinate System
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METHODOLOGY
DATA PREPARATION
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Change of projection system of OSM from WGS_84 to MUTM.
Parameters used in transformation are
ΔX=-293.17m
ΔY=-726.18m
ΔZ=-245.36m
(obtained from Survey department document)
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METHODOLOGY
OSM
SD
Before Transformation
After Transformation
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METHODOLOGY
DATA ANALYSIS
Positional Accuracy of Road
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Calculate the percentage intersect with the buffer of SD map.
Classify the data into 5 classes (Very
Good, Good, Medium, Bad and Very Bad) using equal interval.
Road in OSM
Road Buffer of SD
Road Centerline in SD
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METHODOLOGY
Positional Accuracy of Building
1.Near Distance Method
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distance between centroid of OSM and SD buildings is calculated
classify the data into 5 classes (Very Good, Good, Medium, Bad
and Very Bad) using equal interval.
Building in OSM
Distance Between Centroid of Buildings
Building in OSM
Fig.:
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METHODOLOGY
2. Area difference
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difference of area of OSM and SD buildings is calculated
classify the data into 5 classes (Very Good, Good, Medium, Bad
and Very Bad) using equal interval.
Building in SD
Building in OSM
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METHODOLOGY
3. Circulatory Ratio Difference (CRD)
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CRD=4*pi*Area /Perimeter2
Difference of ratio of OSM and SD buildings is calculated
Checks the variation in shape
Classify the data into 5 classes (Very Good, Good, Medium, Bad and
Very Bad) using equal interval.
Building in SD
Building in OSM
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METHODOLOGY
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Attribute Accuracy
-name, one way ,bridge of road map
-verify attributes from field survey
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RESOURCES REQUIRED
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ArcGis Software
OSM map
Survey Department Map
Microsoft Excel 2007
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23. WORK SCHEDULE
S.No
Weeks 1
1/9/2014
2
3
4 5
6 7
8
9
10 11 12 13
Works
1
Concept paper
2
Proposal Defense
3
Data Collection
4
Data Preparation
4
Data Analysis
5
Mid term Presentation
6
Report preparation and Final
Presentation
Proposed schedule
Work Accomplished
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OUTCOMES
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PROVISIONAL OUTCOMES
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PROVISIONAL OUTCOMES
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OUTCOMES
Building Analysis (Ward 12)
Near Distance
QUALITY
Class(m)
Frequency
In %
VERY GOOD
0-6.4
56
82.35294
GOOD
6.4-12.8
8
11.76471
AVERAGE
12.8-19.2
2
2.941176
BAD
19.2-25.6
0
0
VERY BAD
25.6-32
2
2.941176
Fig: Near Distance Analysis
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OUTCOMES
Ciculatory Ratio Difference
QUALITY
Class
Frequency
In %
VERY GOOD
0-0.06
56
82.35294
GOOD
0.06-0.12
7
10.29412
AVERAGE
0.12-0.18
3
4.411765
BAD
0.18-0.24
0
0
VERY BAD
0.24-0.31
2
2.941176
Fig.: Circulatory Ratio Difference Analysis
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OUTCOMES
60
50
40
30
Area Difference
QUALITY
8
2
2
2
0
VERY GOOD
GOOD
AVERAGE
BAD
VERY BAD
In %
0-0.06
54
79.41176
0.06-0.12
8
11.76471
AVERAGE
10
Frequency
GOOD
20
Class(sq.m.)
VERY GOOD
54
0.12-0.18
2
2.941176
BAD
0.18-0.24
2
2.941176
VERY BAD
0.24-0.31
2
2.941176
Fig.: Area Difference Analysis
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OUTCOMES
COMBINED RESULT
QUALITY
Class(Score)
Frequency
in %
VERY GOOD
GOOD
AVERAGE
84-100
68-84
52-68
63
5
0
92.64706
7.352941
0
BAD
VERY BAD
36-52
20-36
0
0
0
0
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OUTCOMES
Building Analysis (Ward 11)
Near Distance Bar Diagram
120
100
Near Distance
Quality
Frequency
80
Class(m)
Frequency
In %
VERY GOOD
20
9
0
VERY GOOD
GOOD
AVERAGE
2
BAD
71.34
4.64
-
9.21
34
20.73
9.21
- 13.78
9
5.49
13.78 - 18.35
2
1.22
VERY BAD
34
117
BAD
40
4.64
GOOD
117
-
AVERAGE
60
0.06
18.35 - 22.92
2
1.22
2
VERY BAD
Quality
Fig: Near Distance Analysis
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OUTCOMES
Circulatory Ratio Bar Diagram
120
100
Circulatory Ratio Difference
Frequency
80
60
Quuality
VERY GOOD
114
Class
0.00 - 0.08
Frequency
114
In %
69.51
GOOD
8
6
0
VERY
GOOD
GOOD
AVERAGE
BAD
34
20.73
0.17
-
0.25
8
4.88
0.25
-
0.33
6
3.66
VERY BAD
34
0.17
BAD
20
-
AVERAGE
40
0.08
0.33
-
0.42
2
1.22
2
VERY BAD
Quality
Fig.: Circulatory Ratio Difference Analysis
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OUTCOMES
Area Difference Bar Diagram
140
120
Area Difference
Frequency
100
Quality
Class(m2)
Frequency
in %
- 133.88
134
81.71
GOOD
133.88 - 267.57
14
8.54
40
AVERAGE
267.57 - 401.26
9
5.49
20
BAD
401.26 - 534.96
4
2.44
VERY BAD
534.96 - 668.65
3
1.83
80
134
VERY GOOD
60
14
9
0
VERY
GOOD
GOOD
AVERAGE
4
BAD
3
0.19
VERY BAD
Quality
Fig.: Area Difference Analysis
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OUTCOMES
Combined Result Bar Diagram
140
120
Combined Result
Frequency
100
QUALITY
80
140
Class(Score) Frequency
In %
VERY GOOD
84-100
140
85.366
GOOD
68-84
15
9.146
40
AVERAGE
52-68
5
3.049
20
BAD
36-52
1
0.610
VERY BAD
20-36
3
1.829
60
15
0
VERY GOOD
GOOD
5
AVERAGE
1
BAD
3
VERY BAD
Quality
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OUTCOMES
Building Analysis (Ward 10)
Near Distance Bar Diagram
400
350
300
Near Distance
QUALITY
Frequency]
250
Class(m)
Frequency
In %
100
50
62
5
0
VERY GOOD
GOOD
AVERAGE
BAD
366
44.80
2.29
- 4.45
383
46.88
4.45
- 6.61
62
7.59
6.61
- 8.77
5
0.61
VERY BAD
150
- 2.29
BAD
383
0.12
GOOD
366
VERY GOOD
AVERAGE
200
8.77
- 10.94
1
0.12
1
VERY BAD
Quality
Fig: Near Distance Analysis
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OUTCOMES
Circulatory Ratio Difference Bar Diagram
600
500
Circulatory Ratio Difference
400
Frequency
QUALITY
Class
Frequency
In %
VERY GOOD
100
63
35
67.81
0.05
- 0.11
144
17.63
0.11
- 0.16
63
7.71
0.16
- 0.22
35
4.28
VERY BAD
144
554
BAD
200
- 0.05
AVERAGE
554
0.00
GOOD
300
0.22
- 0.27
21
2.57
21
0
VERY
GOOD
GOOD
AVERAGE
BAD
VERY BAD
Quality
Fig.: Circulatory Ratio Difference Analysis
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OUTCOMES
Area Difference Bar Diagram
700
600
Area Difference
500
Frequency
QUALITY
400
Class(m2)
Frequency
In %
VERY GOOD
100
24
0
VERY
GOOD
GOOD
Quality
AVERAGE
7
BAD
78.21
43.61
- 87.19
145
17.75
87.19
- 130.78
24
2.94
130.78 - 174.36
7
0.86
VERY BAD
145
639
BAD
200
- 43.61
AVERAGE
300
0.02
GOOD
639
174.36 - 217.95
2
0.24
2
VERY BAD
Fig.: Area Difference Analysis
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OUTCOMES
Combined Rseult Bar Diagram
700
600
Frequency
500
QUALITY
400
COMBINED RESULT
Class(Score) Frequency
In %
VERY GOOD
100
14
0
VERY GOOD
GOOD
AVERAGE
2
BAD
1
79.43696
68-84
151
18.48225
52-68
14
1.713586
BAD
151
649
AVERAGE
200
84-100
GOOD
649
300
36-52
2
0.244798
VERY BAD
20-36
1
0.122399
VERY BAD
Quality
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OUTCOMES
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WORKS REMAINING
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Analysis of positional accuracy of building on other wards
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LIMITATIONS
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Accuracy of OSM depends on the map of Survey
Department.
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SNAPSHOTS DURING PROJECTS
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Building Overlap in Ward 12
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District Road Intersection of OSM and SD
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12
11
10
Building Map of Kathmandu ward no. 10,11 &12
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REFERENCES
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Koundai, Quorinia.(2009), Assessing the quality of OpenStreetMap data, Msc
thesis, London, University College London.
O’Brien.Oliver.(2010).Openstreet map Quality issue
(http://www.oliverobrien.co.uk/ )
Helbitch,Marco,Amelunxen,Christof.Neis,Pascal.Zipf.Alexnader(2010), Compa
rative Spatial Analysis of Positional Accuracy of OpenStreetMap and
Proprietary Geodata
Haklay, M. (2010), datasets.Environment anHow good is volunteered
geographical information? A comparative study of OpenStreetMap and
Ordnance Survey d Planning B, 37, 682-703.
OpenStreetMap (2013), The free wiki world map.
http://www.openstreetmap.org/ (last date accessed June, 2013).
Zielstra, D. & Zipf, A. (2010), A comparative study of proprietary geodata and
volunteered geographic information for Germany. 13th AGILE International
Conference On Geographic Information Science. Guimaraes, Portugal.
Humanitarian Openstreetmap Team (2012), Evaluation of OpenstreetMap Data
in Indonesia (A Final Report), Department of Geodetic & Geomatics
Engineering, Faculty of Engineering UGM
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