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the grid-based algorithm shows an inconsistency due to the impact of the missing points. A more suitable cell size is suggested to resolve this problem. Since the alpha-shape algorithm performs consistently for all sample buildings, it is considered a suitable algorithm for most of the general extraction work. However, the efficiency of this algorithm is questionable when dealing with a huge dataset of high density since it will extract every possible boundary points. In that case, a grid-based algorithm with a large cell size can be used for initial extraction, followed by the alpha-shape algorithm. 4. CONCLUDING REMARKS In this paper, three algorithms for building boundary extraction are assessed in an object-by-object basis. The alpha-shape algorithm generates reliable boundaries for most of sample buildings, while the grid-based algorithm shows a little inconsistency in some cases. The concave hull algorithm performs moderately with a few limitations. The alpha-shape algorithm is suggested for general building boundary extraction for its consistency and reliability. Future work is required to increase the efficiency of the alpha-shape algorithm because the basic principle of alpha-shape formation is to extract every possible boundary points which can be redundant for a high-density dataset. REFERENCES Awrangjeb, M., M. Ravanbakhsh and C. S. Fraser (2010). "Automatic detection of residential buildings using LIDAR data and multispectral imagery." ISPRS Journal of Photogrammetry and Remote Sensing 65(5): 457-467. Edelsbrunner, H. and E. P. Mucke (1994). "Three-dimensional alpha shapes." ACM Transactions on Graphics 13(1): 43-72. Oliver, W., S. K. Lodha and D. P. Helmbold (2006). A Bayesian approach to building footprint extraction from aerial LIDAR data. Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06), 14-16 June 2006, Piscataway, NJ, USA, IEEE. Qihong, Z., L. Jiazhen, L. Xianhua, M. Jianhua and L. Xuefeng (2008). Simple building reconstruction from LIDAR point cloud. 2008 International Conference on Audio, Language and Image Processing, 7-9 July 2008, Piscataway, NJ, USA, IEEE. Sampath, A. and J. Shan (2007). "Building boundary tracing and regularization from airborne lidar point clouds." Photogrammetric Engineering and Remote Sensing 73(7): 805-812. Verma, V., R. Kumar and S. Hsu (2006). 3D building detection and modeling from aerial LIDAR data. 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006, June 17, 2006 - June 22, 2006, New York, NY, United states, Institute of Electrical and Electronics Engineers Computer Society. Wehr, A. and U. Lohr (1999). "Airborne laser scanning - An introduction and overview." ISPRS Journal of Photogrammetry and Remote Sensing 54(2-3): 68-82. Wei, S., Z. Jin and Y. Feng (2011). A new algorithm of building boundary extraction based on LIDAR data. 2011 19th International Conference on Geoinformatics, 24-26 June 2011, Piscataway, NJ, USA, IEEE. Zhou, Q.-Y. and U. Neumann (2008). Fast and extensible building modeling from airborne LiDAR data. 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM GIS 2008, November 5, 2008 - November 7, 2008, Irvine, CA, United states, Association for Computing Machinery. Object-Based Building Boundary Extraction from Lidar Data 96
The Development of Web3D-based Open-pit Mine Monitoring System Se-Yul Kim 1 , Dong-Gook Lee 2 , Jung-Bin Lee 3 Byung-Jin Jang 4 , Ji-Ho You 5 , Hyun-Jik, Lee 6 1 Master`s Course, Dept. of Civil Engineering, Sangji University 83 Sangjidae-gil Wonju-si 220-702, Rep. of Korea Email: winwopon@naver.com 2 Master`s Course, Dept. of Civil Engineering, Sangji University Email: leedg1210@naver.com 3 Bachelor of Arts in Landscape Studies, The University of Hong Kong Email: tomtem130@naver.com 4 Team Leader, Gaia3D, Inc., 702, SJ Techno Ville, Gasan-dong, Geumcheon-gu, Seoul-si 153-769, Rep. of Korea Email: bjjang@gaia3d.com 5 Part time Lecturer(Ph.D.), Dept. of Civil Engineering, Sangji University Email: sjce96@hanmail.net 6 Professor(Ph.D.), Corresponding Author, Dept. of Civil Engineering, Sangji University Email: hjiklee@sangji.ac.kr ABSTRACT Large-scale open-pit mines are critical infrastructure for acquiring natural resources. However, this type of mine can experience environmental and safety problems during operations and thus requires continuous monitoring. In this study, a web three-dimensional(3D)-based monitoring system is constructed using geospatial information open platform and open-source geospatial information software which targets open-pit mines in Gangwon-do, Korea. The purpose is to develop a monitoring system of open-pit mines that enables any person to monitor the topographic and environmental changes caused by mine operations and to develop and restore the area’s ecology. Open-pit mines were classified into active or inactive mines and monitoring items and methodologies were established for each type of mine. Cesium which is a WebGL-based open-source platform was chosen as it supports dynamic data visualization and hardware-accelerated graphics related to elapsed time which is the essential factor in the monitoring. The open-pit mine monitoring system was developed based on the geospatial database which contains information required for mine monitoring as time elapses, and by developing the open-source-based system software. The geospatial information database for monitoring consists of digital imagery and terrain data and also includes vector data and the restoration plan datas. The basic geospatial information used in the monitoring includes high resolution ortho image(GSD 0.5 m or above) for all areas of the mines. This is acquired by periodically using an airborne laser scanning system and a LiDAR DEM (grid size 1m × 1 m). In addition, geospatial information data were acquired by using an UAV and terrestrial LiDAR for small-scale areas; these tools are frequently used for rapid and irregular data acquisition. The geospatial information acquired for the monitoring of the open-pit mines represents various spatial resolutions and different terrain data. The database was constructed by converging this geospatial information with the Cesium-based geospatial information open platform of the ESRI World Imagery map and with SDK World Terrain meshes. The problems that resulted from the process of fusing aerial imagery and terrain data were solved in the Cesium-based open source environment. The prototype menu for the monitoring system was designed according to the monitoring item which was determined by the type of mine. The scene of the mine and changes in terrain were controlled and analyzed using the raster function of PostGIS according to the elapsed time. Using the GeoServer, the aerial imagery, terrain and restoration information for each period were serviced using the web standard interface, and the monitoring system was completed by visualizing these elements in Cesium in 3D format according to the elapsed time. This study has established a monitoring methodology for open-pit mines according to the type of mine and proposes a method for upgrading the imagery and terrain data required for monitoring. The study also showed the possibility of developing a Web3D-based open-pit mine monitoring system that is applicable to a wide range of mashup service developments. 1. INTRODUCTION FOSS4G Seoul, South Korea | September 14 th – 19 th , 2015 97
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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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Page 75 and 76: H 27 Male Student Maths / Geography
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Page 81 and 82: 2. RELATED WORK Recent developments
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Page 85 and 86: Figure 3. Map Tiles Grid Selection
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Page 91 and 92: Object-Based Building Boundary Extr
Page 93 and 94: 2.2. A Grid-Based Algorithm A grid-
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Page 117 and 118: Hugin Pix4Dmapper Pablo d'Angelo et
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Page 125 and 126: SWE framework proposes the followin
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Page 133 and 134: 4.3.1 Explore The explore view allo
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Page 141 and 142: In augmented reality a live view of
Page 143 and 144: Figure 4. Dwellings in an informal
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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
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4. Data is sent to the web pages ei
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Advances in Civic Co-management wit
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2. JAKARTA'S DISASTER RISK MANAGEME
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The aim of the system is to improve
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8. REFERENCES Baker, J. L., 2012. (
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EVALUATION OF AN OPEN-SOURCE COLLAB
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therelevant stakeholderswith differ
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at each stage of the exercise: · l
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differentmitigationmeasuresaccordin
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students before the exercise. 5 4 3
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the third stage of the exercise in
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doi:10.1016/j.envsoft.2003.12.019.
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e integrated directly in the Web-GI
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3. Implementation The main features
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Phase 1: Earthquake data Input Data
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Figure 4 . Magnitude 7.8 Earthquake
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After adding all the layer maps, th
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EVALUATING FLOOD HAZARD POTENTIAL I
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σ 0 = 10*log 10 (DN 2 ) + CF (1) W
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Figure 4. The geomorphological feat
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from water class in land cover map
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ANALYSIS OF SPATIAL DENSITY UTILIZI
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demographic data. He also states th
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Table 1. The combination of COUNTRY
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NUMBER OF SUBSCRIBERS 300,000 250,0
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Figure 9. The number of foreign tou
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Figure 16. Spatial call activity pa
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Recently, additional tourist inform
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country. It uses R-Studio, a statis
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Geosocial Big Data Analysis Using P
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AN ON-BOARD VISUAL-BASED ATTITUDE E
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3.1 Keypoints detection and matchin
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complete the process. This has been
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Fleet, D., & Weiss, Y. (2006). Opti
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technologies in Geoinformation Scie
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technologies becomes irrelevant in
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Figure 2. Server (upper block) and
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Name Presence Description Table 1.
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SampleExtraApp sampleExtraApp annot
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4. RESULTS Summing up, we should no
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Paradigms. John Wiley & Sons Inc.,
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FREEWAT: FREE and open source tools
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An Evaluation of Open Source Geogra
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2. DATA AND METHOD The approach ado
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the beginning and end of each trip
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Table 4 - GIS Routing Tools S/N GIS
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State cold store- Hungu Primary Hea
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Figure 3 - Comparing Discrepancy in
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nations based on human per capita i
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investigating metropolitan traffic.
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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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