PROCEEDINGS

Recommendations

Info

Figure 2. Visualization of multiple typed geo-based data using mobile UX/UI on the e- government web framework. Figure 3. Attribute visualizationof public geo-based data: (a) Seoul and (b) Busan. Figure 4. Visualization results using open API on the e-government web framework: (a) on-line mapping and (b) bar chart. FOSS4G Seoul, South Korea | September14 th – 19 th , 2015 306
5. CONCLUDING REMARKS Open source stack was developed for open data application. This project focuses on mobile web visualization of geo-based data and other typed open data. While, the e- government web framework and the mobile extension are also applied as important implementation specifications. For the actual application implementation, geo-spatially specific open sources such as GeoServer and OpenLayers and mobile visualization open sources such as jQuery and D3.js were used. The e-government mobile standards framework was used for mobile UX/UI components. It is expected that this approach provides practical reference and technological basis to develop target-oriented mobile application business models using open data and the e-government mobile web framework. 6. ACKNOWLEDGMENTS This research was supported by National Land Space Information Research Program by Ministry of Land, Infrastructure and Transport of Korean government (No. 14NSIP- B080144-01). 7. REFERENCES Kim, K. and K. Lee, 2015. Visualization of Geo-spatial Data and Public Data using Mobile Operating Environment in the eGovernment Standard Framework, Journal of Korea Spatial Information Society 23, 9-17. Kwakkel, J. H.,C. Stephen, C. John, and C. Scott W., 2014. Visualizing Geo-spatial Data in Science, Technology and Innovation, Technological Forecasting & Social Change81, 67-81. W3C, 2015.Standards for Web Applications on Mobile: Current State and Roadmap, http://www.w3.org/Mobile/mobile-web-app-state (Accessed July 22, 2015). Mobile application of open source stack to geo-based data visualizatione-government web framework 307
Page 1 and 2:
PROCEEDINGS Honil Gangni Yeokdae Gu
Page 3 and 4:
C O N T E N T S Welcome Messages Lo
Page 5 and 6:
A Week of Sharing, Learning, and Fu
Page 7 and 8:
ACADEMIC TRACKS 7
Page 9 and 10:
September 17, Thursday 11:00-12:15
Page 11 and 12:
September 16 (Wed) & 18 (Fri) 15:05
Page 13 and 14:
AUTOMATIC IMPROVEMENT OF POINT-OF-I
Page 15 and 16:
In the following, we will list
Page 17 and 18:
and specify their relations manuall
Page 19 and 20:
Conducting a cross-validation on th
Page 21 and 22:
81%. For cuisine=german, the precis
Page 23 and 24:
4.3 Tourism and Leisure Tags We ide
Page 25 and 26:
GENERATING GEOSPATIAL FOOTPRINTS FO
Page 27 and 28:
quality assessment of geocrowdsourc
Page 29 and 30:
Figure 2: The first simple case of
Page 31 and 32:
Figure 5: The footprint of walkways
Page 33 and 34:
say instead “Between 1st Street a
Page 35 and 36:
4. DISCUSSION AND CONCLUSIONS The G
Page 37 and 38:
Performance Analysis of MongoDB Vs.
Page 39 and 40:
2. REVIEW OF SPATIAL DATABASES Simi
Page 41 and 42:
4.2 Point Containment Problem Like
Page 43 and 44:
If we observe the results above we
Page 45 and 46:
esolution data (RapidEye and Landsa
Page 47 and 48:
and used for calibration and coeffi
Page 49 and 50:
scatter plot of RapidEye (Global (C
Page 51 and 52:
is efficient to extrapolate depth f
Page 53 and 54:
DYNAMIC STYLING FOR THEMATIC MAPPIN
Page 55 and 56:
all) datasets on offer or applying
Page 57 and 58:
3.2.1 Data inputs The styler accept
Page 59 and 60:
determine the radius (both in the x
Page 61 and 62:
Figure 5: Map classification of blo
Page 63 and 64:
4.3 Point data Figure 8: Diverging
Page 65 and 66:
4.4 Non-spatial visualisations Figu
Page 67 and 68:
6 ACKNOWLEDGEMENTS The Cooperative
Page 69 and 70:
educational resources (OER) and mod
Page 71 and 72:
workshops have revealed that microc
Page 73 and 74:
300 250 200 150 100 50 0 Figure 4.
Page 75 and 76:
H 27 Male Student Maths / Geography
Page 77 and 78:
5. CONCLUSIONS AND FUTURE WORK We h
Page 79 and 80:
DEVELOPMENT OF DATA ARCHIVING AND D
Page 81 and 82:
2. RELATED WORK Recent developments
Page 83 and 84:
3. Significance and Objectives With
Page 85 and 86:
Figure 3. Map Tiles Grid Selection
Page 87 and 88:
The Ceph architecture comprises of
Page 89 and 90:
Boundless, 2015. GeoExplorer — Ge
Page 91 and 92:
Object-Based Building Boundary Extr
Page 93 and 94:
2.2. A Grid-Based Algorithm A grid-
Page 95 and 96:
3.1 Boundary Extraction The extract
Page 97 and 98:
The Development of Web3D-based Open
Page 99 and 100:
Singh et al.(2012) have utilized op
Page 101 and 102:
Monitoring concept on operating asp
Page 103 and 104:
(a) Mining area (Left:2007, Right:2
Page 105 and 106:
geospatial information open platfor
Page 107 and 108:
open platform utilized in open-pit
Page 109 and 110:
Data Acquisition Methods Acquisitio
Page 111 and 112:
(a) Ecological Restoring Area 1 (Le
Page 113 and 114:
possibility of development of open-
Page 115 and 116:
2. DATA ACQUISITION 2.1 Image gathe
Page 117 and 118:
Hugin Pix4Dmapper Pablo d'Angelo et
Page 119 and 120:
utit may be improved using many ste
Page 121 and 122:
Wójcicka, A., and Wróbel, Z., 201
Page 123 and 124:
platforms, which are easy to use an
Page 125 and 126:
SWE framework proposes the followin
Page 127 and 128:
Steenkamp et al. (2009) state that
Page 129 and 130:
technology and are published under
Page 131 and 132:
Measurement value yes Measurement s
Page 133 and 134:
4.3.1 Explore The explore view allo
Page 135 and 136:
Figure 8. Registration of a generic
Page 137 and 138:
participants completely agree with
Page 139 and 140:
467 - 471. Sohraby, K., Minoli, D.,
Page 141 and 142:
In augmented reality a live view of
Page 143 and 144:
Figure 4. Dwellings in an informal
Page 145 and 146:
1. Gen eral crite ria 1.1. Platform
Page 147 and 148:
matching, 3D engine, image tracking
Page 149 and 150:
1.4. Implemented standards OGC ARML
Page 151 and 152:
2.3. Object events 2.4. Display rad
Page 153 and 154:
instructional videos, and basic exa
Page 155 and 156:
application for addressing, the pre
Page 157 and 158:
Environments, 6(4), 355-385. Carmig
Page 159 and 160:
1. INTRODUCTION Use of landmarks in
Page 161 and 162:
the junctions which made with major
Page 163 and 164:
4. IMPLEMENTATION 4.1 Technology Se
Page 165 and 166:
Figure 3: Linear map output with si
Page 167 and 168:
AN OPEN SOURCE WEB SERVICE FOR REGI
Page 169 and 170:
2. IGSN OVERVIEW Figure 1 shows the
Page 171 and 172:
types (e.g., dateType and relationT
Page 173 and 174:
REST API(Fielding, 2000). The servi
Page 175 and 176:
An Open Source Web Service for Regi
Page 177 and 178:
Research Centre (ARRC) and the Nati
Page 179 and 180:
Developing a land use database of t
Page 181 and 182:
Figure 3. Land use input applicatio
Page 183 and 184:
Paddy 19.4 23.7 Upland field, orcha
Page 185 and 186:
Figure 6. Overlay point based land
Page 187 and 188:
Integrating Open Source GIS Softwar
Page 189 and 190:
Advanced GIS course, we recognized
Page 191 and 192:
for undergraduates. Research take t
Page 193 and 194:
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
Page 209 and 210:
at each stage of the exercise: · l
Page 211 and 212:
differentmitigationmeasuresaccordin
Page 213 and 214:
students before the exercise. 5 4 3
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 and 246:
Figure 9. The number of foreign tou
Page 247 and 248:
Figure 16. Spatial call activity pa
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
Page 265 and 266: technologies becomes irrelevant in
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
Page 297 and 298: in 1980(Saaty, 1980). It assesses t
Page 299 and 300: ex or current government officials
Page 301 and 302: Herold, S., & Sawada, M. C. (2012).
Page 303 and 304: frameworkwhich covers an infrastruc
Page 305: The architecture of the application
Page 309 and 310: cloud environment, so that end-user
Page 311 and 312: Figure 2 represents user interface
Page 313 and 314: geo-science application. Also the o
Page 315 and 316: PO-04 GeoDjango-Framwork-based Popu
Page 317 and 318: pH of 5.5 to 7.0; forest loam, rock
Page 319 and 320: Figure 4. Study Area (Davao Region)
Page 321 and 322: Figure 6. Topographic Map of Mindan
Page 323 and 324: Figure 8. Land Areas suitable for C
Page 325 and 326: It is respectfully recommended that
Page 327 and 328: ECDIS through introduction of Open
Page 329 and 330: to adopt development using open sou
Page 331 and 332: 3. Conclusion ECDIS is navigation e
Page 333 and 334: PO-08 Development of an Agent Based
Page 335 and 336: 1. INTRODUCTION 1.1 Background of t
Page 337 and 338: Figure 2. Workflow of the semi-auto
Page 339 and 340: threshold set. GRASS 7.0 is used in
Page 341 and 342: Figure 7. Result of the application
Page 343 and 344: Ming, D. M. D., Luo, J. L. J., Shen
Page 345 and 346: PO-10 3D Visualization of City GML
Page 347 and 348: As A Service (PAAS) and Infrastruct
Page 349 and 350: Figure 2: System Architecture and D
Page 351 and 352: The resulted crowd source data cont
Page 353 and 354: Table 1: Confusion Matrix Crowd sou
Page 355 and 356: PO-12 House Number Interpolation Fo
Page 357 and 358:
(DOE) has awarded a total of 82 Gri
Page 359 and 360:
Most solar radiation models compute
Page 361 and 362:
2. OBJECTIVES, SCOPE, AND LIMITATIO
Page 363 and 364:
Figure 4. BSWM Solar Sensors for Va
Page 365 and 366:
4.2 Site Suitability Analysis Inter
Page 367 and 368:
5. RESULTS AND DISCUSSION 5.1 Month
Page 369 and 370:
Figure 8. Monthly Average Real-sky
Page 371 and 372:
Figure 19. GHI for November Figure
Page 373 and 374:
Figure 26. Non-Resource Criteria Su
Page 375 and 376:
Kryza, M. et al. 2010. “Spatial i
Page 377 and 378:
example coordinates agents, based o
Page 379 and 380:
A benefit of using multiple agents
Page 381 and 382:
A local GeoServer instance was set
Page 383 and 384:
Figure 3. Screen captures of search
Page 385 and 386:
In combination with ranking of resu
Page 387 and 388:
INTRODUCTION TO A NEW GEO-REFERENCE
Page 389 and 390:
Figure 2. ‘Click-to-go’ functio
Page 391 and 392:
Figure 5. The conceptual structure
Page 393 and 394:
Figure 6. Software architecture of
Page 395 and 396:
GIS ORIENTED SERVICE OPTIMIZATION T
Page 397 and 398:
Vehicle Routing Problem (VRP) refer
Page 399 and 400:
So, buffer of 2 meters was created
Page 401 and 402:
log data which was the actual dista
Page 403 and 404:
was being served by three vehicles.
Page 405 and 406:
Analyzing the number of customers,
Page 407 and 408:
PO-17 A Study of the Development an
Page 409 and 410:
MODELING OF TERMINOLOGY DATABASE IN
Page 411 and 412:
3.2 Interpretation of the terms 4 I
Page 413 and 414:
Figure 4 shows the result of SWOT a
Page 415 and 416:
Add terms in the database: Super us
Page 417 and 418:
6. REFERENCES Damdinsuren A., 2013.
Page 419 and 420:
PO-20 Vulnerability Assessment Usin
Page 421 and 422:
LEIGHTWEIGHT URBAN COMPUTATION INTE
Page 423 and 424:
where events are instantly propagat
Page 425 and 426:
not be conceived as responsive by a
Page 427 and 428:
3.5. Remote Services Among a few
Page 429 and 430:
4. USE CASES 4.1. Transition Worksh
Page 431 and 432:
to display the rank of the player i
Page 433 and 434:
PO-23 Development of Opensource-bas
Page 435 and 436:
Author Index Aburizaiza, Ahmad O. 2
show all

PROCEEDINGS

Create successful ePaper yourself

Delete template?

Save as template?