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4.4 Apgujeong-dong The primary cellular phone subscribers registered to the cell towers around Apgujeongdong are those from country N01. Numerous hospitals for plastic surgery in Apgujeongdonghave promoted medical tourism in Korea. Hence, the call records of foreign visitors for medical purposes are evenly distributed from 8AM to 20PM. Figure 14. Spatial call activity pattern of Apgujeong-dong displayed on a map with QGIS 4.5 Itaewon Figure 15. The number of foreign tourists in Apgujeong-dong sorted by country code and time of the day Itaewon shows disparity from other areas in that the tourists from N06 primarily is consisted of mobile phone subscribers. The accommodations, shopping area, and nightlife establishments contribute to mild differences in call traffic from 8AM to 12AM. Analysis of Spatial Density Utilizing the Big Data of Floating Population of Seoul City 246
Figure 16. Spatial call activity pattern of Itaewon displayed on a map with QGIS 4.6 Hongik University Figure 17. The number of foreign tourists in Itaewon sorted by country code and time of the day Variousnationalities of cellular phone subscribers around Hongik University are notable. Its shopping district and nightlife establishments contribute to mild differences in call traffic from 10AM to 12AM. Figure 18. Spatial call activity pattern of Hongik University displayed on a map with QGIS Analysis of Spatial Density Utilizing the Big Data of Floating Population of Seoul City 247
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PROCEEDINGS Honil Gangni Yeokdae Gu
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C O N T E N T S Welcome Messages Lo
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A Week of Sharing, Learning, and Fu
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ACADEMIC TRACKS 7
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September 17, Thursday 11:00-12:15
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September 16 (Wed) & 18 (Fri) 15:05
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AUTOMATIC IMPROVEMENT OF POINT-OF-I
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In the following, we will list
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and specify their relations manuall
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Conducting a cross-validation on th
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81%. For cuisine=german, the precis
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4.3 Tourism and Leisure Tags We ide
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GENERATING GEOSPATIAL FOOTPRINTS FO
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quality assessment of geocrowdsourc
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Figure 2: The first simple case of
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Figure 5: The footprint of walkways
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say instead “Between 1st Street a
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4. DISCUSSION AND CONCLUSIONS The G
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Performance Analysis of MongoDB Vs.
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2. REVIEW OF SPATIAL DATABASES Simi
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4.2 Point Containment Problem Like
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If we observe the results above we
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esolution data (RapidEye and Landsa
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and used for calibration and coeffi
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scatter plot of RapidEye (Global (C
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is efficient to extrapolate depth f
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DYNAMIC STYLING FOR THEMATIC MAPPIN
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all) datasets on offer or applying
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3.2.1 Data inputs The styler accept
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determine the radius (both in the x
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Figure 5: Map classification of blo
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4.3 Point data Figure 8: Diverging
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4.4 Non-spatial visualisations Figu
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6 ACKNOWLEDGEMENTS The Cooperative
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educational resources (OER) and mod
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workshops have revealed that microc
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300 250 200 150 100 50 0 Figure 4.
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H 27 Male Student Maths / Geography
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5. CONCLUSIONS AND FUTURE WORK We h
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DEVELOPMENT OF DATA ARCHIVING AND D
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2. RELATED WORK Recent developments
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3. Significance and Objectives With
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Figure 3. Map Tiles Grid Selection
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The Ceph architecture comprises of
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Boundless, 2015. GeoExplorer — Ge
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Object-Based Building Boundary Extr
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2.2. A Grid-Based Algorithm A grid-
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3.1 Boundary Extraction The extract
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The Development of Web3D-based Open
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Singh et al.(2012) have utilized op
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Monitoring concept on operating asp
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(a) Mining area (Left:2007, Right:2
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geospatial information open platfor
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open platform utilized in open-pit
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Data Acquisition Methods Acquisitio
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(a) Ecological Restoring Area 1 (Le
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possibility of development of open-
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2. DATA ACQUISITION 2.1 Image gathe
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Hugin Pix4Dmapper Pablo d'Angelo et
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utit may be improved using many ste
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Wójcicka, A., and Wróbel, Z., 201
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platforms, which are easy to use an
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SWE framework proposes the followin
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Steenkamp et al. (2009) state that
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technology and are published under
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Measurement value yes Measurement s
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4.3.1 Explore The explore view allo
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Figure 8. Registration of a generic
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participants completely agree with
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467 - 471. Sohraby, K., Minoli, D.,
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In augmented reality a live view of
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Figure 4. Dwellings in an informal
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1. Gen eral crite ria 1.1. Platform
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matching, 3D engine, image tracking
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1.4. Implemented standards OGC ARML
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2.3. Object events 2.4. Display rad
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instructional videos, and basic exa
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application for addressing, the pre
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Environments, 6(4), 355-385. Carmig
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1. INTRODUCTION Use of landmarks in
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the junctions which made with major
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4. IMPLEMENTATION 4.1 Technology Se
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Figure 3: Linear map output with si
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AN OPEN SOURCE WEB SERVICE FOR REGI
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2. IGSN OVERVIEW Figure 1 shows the
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types (e.g., dateType and relationT
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REST API(Fielding, 2000). The servi
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An Open Source Web Service for Regi
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Research Centre (ARRC) and the Nati
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Developing a land use database of t
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Figure 3. Land use input applicatio
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Paddy 19.4 23.7 Upland field, orcha
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Figure 6. Overlay point based land
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Integrating Open Source GIS Softwar
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Advanced GIS course, we recognized
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for undergraduates. Research take t
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Figure 8 The USDA Foodshed project
Page 195 and 196: 4. Data is sent to the web pages ei
Page 197 and 198: Advances in Civic Co-management wit
Page 199 and 200: 2. JAKARTA'S DISASTER RISK MANAGEME
Page 201 and 202: The aim of the system is to improve
Page 203 and 204: 8. REFERENCES Baker, J. L., 2012. (
Page 205 and 206: EVALUATION OF AN OPEN-SOURCE COLLAB
Page 207 and 208: therelevant stakeholderswith differ
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Page 215 and 216: the third stage of the exercise in
Page 217 and 218: doi:10.1016/j.envsoft.2003.12.019.
Page 219 and 220: e integrated directly in the Web-GI
Page 221 and 222: 3. Implementation The main features
Page 223 and 224: Phase 1: Earthquake data Input Data
Page 225 and 226: Figure 4 . Magnitude 7.8 Earthquake
Page 227 and 228: After adding all the layer maps, th
Page 229 and 230: EVALUATING FLOOD HAZARD POTENTIAL I
Page 231 and 232: σ 0 = 10*log 10 (DN 2 ) + CF (1) W
Page 233 and 234: Figure 4. The geomorphological feat
Page 235 and 236: from water class in land cover map
Page 237 and 238: ANALYSIS OF SPATIAL DENSITY UTILIZI
Page 239 and 240: demographic data. He also states th
Page 241 and 242: Table 1. The combination of COUNTRY
Page 243 and 244: NUMBER OF SUBSCRIBERS 300,000 250,0
Page 245: Figure 9. The number of foreign tou
Page 249 and 250: Recently, additional tourist inform
Page 251 and 252: country. It uses R-Studio, a statis
Page 253 and 254: Geosocial Big Data Analysis Using P
Page 255 and 256: AN ON-BOARD VISUAL-BASED ATTITUDE E
Page 257 and 258: 3.1 Keypoints detection and matchin
Page 259 and 260: complete the process. This has been
Page 261 and 262: Fleet, D., & Weiss, Y. (2006). Opti
Page 263 and 264: technologies in Geoinformation Scie
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Page 267 and 268: Figure 2. Server (upper block) and
Page 269 and 270: Name Presence Description Table 1.
Page 271 and 272: SampleExtraApp sampleExtraApp annot
Page 273 and 274: 4. RESULTS Summing up, we should no
Page 275 and 276: Paradigms. John Wiley & Sons Inc.,
Page 277 and 278: FREEWAT: FREE and open source tools
Page 279 and 280: An Evaluation of Open Source Geogra
Page 281 and 282: 2. DATA AND METHOD The approach ado
Page 283 and 284: the beginning and end of each trip
Page 285 and 286: Table 4 - GIS Routing Tools S/N GIS
Page 287 and 288: State cold store- Hungu Primary Hea
Page 289 and 290: Figure 3 - Comparing Discrepancy in
Page 291 and 292: nations based on human per capita i
Page 293 and 294: investigating metropolitan traffic.
Page 295 and 296: A Cross National Comparison on the
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in 1980(Saaty, 1980). It assesses t
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ex or current government officials
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Herold, S., & Sawada, M. C. (2012).
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frameworkwhich covers an infrastruc
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The architecture of the application
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5. CONCLUDING REMARKS Open source s
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cloud environment, so that end-user
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Figure 2 represents user interface
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geo-science application. Also the o
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PO-04 GeoDjango-Framwork-based Popu
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pH of 5.5 to 7.0; forest loam, rock
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Figure 4. Study Area (Davao Region)
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Figure 6. Topographic Map of Mindan
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Figure 8. Land Areas suitable for C
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It is respectfully recommended that
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ECDIS through introduction of Open
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to adopt development using open sou
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3. Conclusion ECDIS is navigation e
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PO-08 Development of an Agent Based
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1. INTRODUCTION 1.1 Background of t
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Figure 2. Workflow of the semi-auto
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threshold set. GRASS 7.0 is used in
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Figure 7. Result of the application
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Ming, D. M. D., Luo, J. L. J., Shen
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PO-10 3D Visualization of City GML
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As A Service (PAAS) and Infrastruct
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Figure 2: System Architecture and D
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The resulted crowd source data cont
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Table 1: Confusion Matrix Crowd sou
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PO-12 House Number Interpolation Fo
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(DOE) has awarded a total of 82 Gri
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Most solar radiation models compute
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2. OBJECTIVES, SCOPE, AND LIMITATIO
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Figure 4. BSWM Solar Sensors for Va
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4.2 Site Suitability Analysis Inter
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5. RESULTS AND DISCUSSION 5.1 Month
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Figure 8. Monthly Average Real-sky
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Figure 19. GHI for November Figure
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Figure 26. Non-Resource Criteria Su
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Kryza, M. et al. 2010. “Spatial i
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example coordinates agents, based o
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A benefit of using multiple agents
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A local GeoServer instance was set
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Figure 3. Screen captures of search
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In combination with ranking of resu
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INTRODUCTION TO A NEW GEO-REFERENCE
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Figure 2. ‘Click-to-go’ functio
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Figure 5. The conceptual structure
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Figure 6. Software architecture of
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GIS ORIENTED SERVICE OPTIMIZATION T
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Vehicle Routing Problem (VRP) refer
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So, buffer of 2 meters was created
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log data which was the actual dista
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was being served by three vehicles.
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Analyzing the number of customers,
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PO-17 A Study of the Development an
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MODELING OF TERMINOLOGY DATABASE IN
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3.2 Interpretation of the terms 4 I
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Figure 4 shows the result of SWOT a
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Add terms in the database: Super us
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6. REFERENCES Damdinsuren A., 2013.
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PO-20 Vulnerability Assessment Usin
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LEIGHTWEIGHT URBAN COMPUTATION INTE
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where events are instantly propagat
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not be conceived as responsive by a
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3.5. Remote Services Among a few
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4. USE CASES 4.1. Transition Worksh
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to display the rank of the player i
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PO-23 Development of Opensource-bas
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Author Index Aburizaiza, Ahmad O. 2
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