Data quality assessment of OSM datasets of Ringroad, Kathmandu, Nepal

Department of Civil and Geomatics Engineering

Kathmandu University

Dhulikhel, Kavre

DATA QUALITY ASSESSMENT OF OSM MAP OF KATHMANDU

Members (Group (5))Shaswat Kafle (11)Maheshwor Karki (14)Suresh Manandhar (17)Dipesh Suwal (29)

Project SupervisorMr. Sashish MaharjanMr. Nawaraj Shrestha

Project In chargeProf. Dr. Ramesh Kumar Maskey

Mid-Term Presentation on

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PRESENTATION OUTLINES• Background• Introduction• Rationale • Study Area• Objectives• Methodology• Resources Required• Project Schedule• Outcomes• Limitations• Conclusions• References

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BACKGROUND

• 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

• 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

• 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

• 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

• To find the accuracy of OSM map of our project site

Sub-Objective• Use of map in other projects such as disaster risk management ,

planning, tourism, navigation and others.

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METHODOLOGY

Data Validation

Data Analysis

Road Network Analysis• Positional Accuracy• Attribute Accuracy

Building Analysis• Positional Accuracy• Attribute Accuracy

Data Preparation

OSM in .shp file Coordinate system

Data Collection

OSM Digital Map

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METHODOLOGY

DATA COLLECTION• 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

http://bbbike.orgosmium2shape/

http://bbbike.orgosmium2shape/

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METHODOLOGY

Openstreetmap Survey Department MapRoad Map

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METHODOLOGY

Openstreetmap Survey Department MapBuilding Map

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METHODOLOGY

Meta Data of Survey Department Map• Topographic map of Nepal• Datum: Everest Bangladesh• projection system :MUTM

Meta Data of Openstreetmap• Volunteered geographic information• Datum:WGS84• projection System: Geographic Coordinate System

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METHODOLOGY

DATA PREPARATION• 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

Before TransformationAfter Transformation

OSM

SD

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METHODOLOGYDATA ANALYSIS

Positional Accuracy of Road• 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 Centerline in SD

Road in OSM

Road Buffer of SD

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METHODOLOGYPositional Accuracy of Building

1.Near Distance Method• distance between centroid of OSM and SD buildings is

calculated• classify the data into 5 classes (Very Good, Good, Medium,


Building in OSM

Distance Between Centroid of Buildings

Building in OSM

Fig.:

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METHODOLOGY2. Area difference

• difference of area of OSM and SD buildings is calculated• classify the data into 5 classes (Very Good, Good, Medium,


Building in OSM

Building in SD

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METHODOLOGY3. Circulatory Ratio Difference (CRD)

• 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 OSM

Building in SD

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METHODOLOGY

• Attribute Accuracy

-name, one way ,bridge of road map

-verify attributes from field survey

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RESOURCES REQUIRED

• ArcGis Software• OSM map• Survey Department Map• Microsoft Excel 2007

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WORK SCHEDULES.No Weeks

Works1 2 3 4 5 6 7 8 9 10 11 12 13

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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OUTCOMESBuilding Analysis (Ward 12)

Fig: Near Distance Analysis

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

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Fig.: Circulatory Ratio Difference Analysis

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

OUTCOMES

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VERY GOOD GOOD AVERAGE BAD VERY BAD0

10

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30

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60

54

82 2 2

Fig.: Area Difference Analysis

Area Difference

QUALITY Class(sq.m.) Frequency In %

VERY GOOD 0-0.06 54 79.41176

GOOD 0.06-0.12 8 11.76471

AVERAGE 0.12-0.18 2 2.941176

BAD 0.18-0.24 2 2.941176

VERY BAD 0.24-0.31 2 2.941176

OUTCOMES

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OUTCOMES

COMBINED RESULT

QUALITY Class(Score) Frequency in %

VERY GOOD 84-100 63 92.64706GOOD 68-84 5 7.352941

AVERAGE 52-68 0 0

BAD 36-52 0 0VERY BAD 20-36 0 0

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OUTCOMESBuilding Analysis (Ward 11)


Near DistanceQuality Class(m) Frequency In %

VERY GOOD 0.06 - 4.64 117 71.34GOOD 4.64 - 9.21 34 20.73

AVERAGE 9.21 - 13.78 9 5.49BAD 13.78 - 18.35 2 1.22

VERY BAD 18.35 - 22.92 2 1.22

VERY GOOD

GOOD AVERAGE BAD VERY BAD0

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40

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80

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120

117

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92 2

Near Distance Bar Diagram

Quality

Fre

quen

cy

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OUTCOMES


Circulatory Ratio Difference

Quuality Class Frequency In %VERY GOOD 0.00 - 0.08 114 69.51

GOOD 0.08 - 0.17 34 20.73

AVERAGE 0.17 - 0.25 8 4.88

BAD 0.25 - 0.33 6 3.66

VERY BAD 0.33 - 0.42 2 1.22

VERY GOOD


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40

60

80

100

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114

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Circulatory Ratio Bar Diagram

Quality

Freq

uenc

y

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OUTCOMES


Area Difference

Quality Class(m2) Frequency in %

VERY GOOD 0.19 - 133.88 134 81.71

GOOD 133.88 - 267.57 14 8.54

AVERAGE 267.57 - 401.26 9 5.49

BAD 401.26 - 534.96 4 2.44

VERY BAD 534.96 - 668.65 3 1.83


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40

60

80

100

120

140

134

14 9 4 3

Area Difference Bar Diagram

Quality

Fre

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cy

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OUTCOMES


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40

60

80

100

120

140

140

155 1 3

Combined Result Bar Diagram

Quality

Freq

uenc

y

Combined Result

QUALITY Class(Score) Frequency In %

VERY GOOD 84-100 140 85.366

GOOD 68-84 15 9.146

AVERAGE 52-68 5 3.049

BAD 36-52 1 0.610

VERY BAD 20-36 3 1.829

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OUTCOMES


Building Analysis (Ward 10)

Near Distance

QUALITY Class(m) Frequency In %

VERY GOOD 0.12 - 2.29 366 44.80

GOOD 2.29 - 4.45 383 46.88

AVERAGE 4.45 - 6.61 62 7.59

BAD 6.61 - 8.77 5 0.61

VERY BAD 8.77 - 10.94 1 0.12


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100

150

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366 383

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Near Distance Bar Diagram

Quality

Fre

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OUTCOMES


Circulatory Ratio Difference

QUALITY Class Frequency In %

VERY GOOD 0.00 - 0.05 554 67.81

GOOD 0.05 - 0.11 144 17.63

AVERAGE 0.11 - 0.16 63 7.71

BAD 0.16 - 0.22 35 4.28

VERY BAD 0.22 - 0.27 21 2.57


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200

300

400

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600

554

144

6335 21

Circulatory Ratio Difference Bar Diagram

Quality

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OUTCOMES


Area Difference

QUALITY Class(m2) Frequency In %

VERY GOOD 0.02 - 43.61 639 78.21

GOOD 43.61 - 87.19 145 17.75

AVERAGE 87.19 - 130.78 24 2.94

BAD 130.78 - 174.36 7 0.86

VERY BAD 174.36 - 217.95 2 0.24


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200

300

400

500

600

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639

145

24 7 2

Area Difference Bar Diagram

Quality

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OUTCOMES

VERY GOOD


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200

300

400

500

600

700

649

151

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Combined Rseult Bar Diagram

Quality

Freq

uenc

y COMBINED RESULTQUALITY Class(Score) Frequency In %

VERY GOOD 84-100 649 79.43696GOOD 68-84 151 18.48225

AVERAGE 52-68 14 1.713586BAD 36-52 2 0.244798

VERY BAD 20-36 1 0.122399

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OUTCOMES

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• Analysis of positional accuracy of building on other wards

WORKS REMAINING

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LIMITATIONS

• 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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1110

Building Map of Kathmandu ward no. 10,11 &12

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REFERENCES• 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),

Comparative 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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THANK YOU

Data quality assessment of OSM datasets of Ringroad, Kathmandu, Nepal

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