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

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

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

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

  • 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
  • 1/9/2014 PRESENTATION OUTLINES • • • • • • • • • • • • Background Introduction Rationale Study Area Objectives Methodology Resources Required Project Schedule Outcomes Limitations Conclusions References 2
  • 1/9/2014 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. 3
  • 1/9/2014 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) 4
  • 1/9/2014 RATIONALE • • The use of OSM map has been increasing day by day. But we aren’t aware about the quality of map. 5
  • 1/9/2014 STUDY AREA 6
  • 1/9/2014 STUDY AREA 7
  • 1/9/2014 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. 8
  • 1/9/2014 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. 9
  • 1/9/2014 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 10
  • 1/9/2014 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 11
  • 1/9/2014 METHODOLOGY Openstreetmap Survey Department Map Road Map 12
  • 1/9/2014 METHODOLOGY Openstreetmap Survey Department Map Building Map 13
  • 1/9/2014 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 14
  • 1/9/2014 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) 15
  • 1/9/2014 METHODOLOGY OSM SD Before Transformation After Transformation 16
  • 1/9/2014 METHODOLOGY DATA 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 in OSM Road Buffer of SD Road Centerline in SD 17
  • 1/9/2014 METHODOLOGY Positional 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, Bad and Very Bad) using equal interval. Building in OSM Distance Between Centroid of Buildings Building in OSM Fig.: 18
  • 1/9/2014 METHODOLOGY 2. Area difference • • 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 19
  • 1/9/2014 METHODOLOGY 3. 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 SD Building in OSM 20
  • 1/9/2014 METHODOLOGY • Attribute Accuracy -name, one way ,bridge of road map -verify attributes from field survey 21
  • 1/9/2014 RESOURCES REQUIRED • • • • ArcGis Software OSM map Survey Department Map Microsoft Excel 2007 22
  • 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 23
  • 1/9/2014 OUTCOMES 24
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  • 1/9/2014 PROVISIONAL OUTCOMES 26
  • 1/9/2014 27
  • 1/9/2014 PROVISIONAL OUTCOMES 28
  • 1/9/2014 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 29
  • 1/9/2014 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 30
  • 1/9/2014 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 31
  • 1/9/2014 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 32
  • 1/9/2014 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 33
  • 1/9/2014 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 34
  • 1/9/2014 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 35
  • 1/9/2014 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 36
  • 1/9/2014 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 37
  • 1/9/2014 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 38
  • 1/9/2014 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 39
  • 1/9/2014 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 40
  • 1/9/2014 OUTCOMES 41
  • 1/9/2014 WORKS REMAINING • Analysis of positional accuracy of building on other wards 42
  • 1/9/2014 LIMITATIONS • Accuracy of OSM depends on the map of Survey Department. 43
  • 1/9/2014 SNAPSHOTS DURING PROJECTS 44
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  • 1/9/2014 Building Overlap in Ward 12 47
  • 1/9/2014 District Road Intersection of OSM and SD 48
  • 1/9/2014 12 11 10 Building Map of Kathmandu ward no. 10,11 &12 49
  • 1/9/2014 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), 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 50
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