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Figure 9 An Android application using Leaflet, GeoJSON, and OpenStreetMap was used to assist riders in the annual Sea Gull Century ride. 4. OUTREACH 4.1 The Eastern Shore Regional GIS Cooperative The original goal of Salisbury University’sEastern Shore Regional GIS Cooperative (ESRGC)was to provide GIS and other high tech services to under-served markets on the Eastern Shore of Maryland. Over the years, the ESRGC has expanded to include larger work assignments, and now have a staff of 14 full time employees including geographers, computer scientists, and database analysts. As these work assignments grew into more IT related endeavors, our work transitioned from cartography and basic spatial analysis tasks to greater use of database technology, Internet mapping, and spatial analysis. As part of the educational experience, the ESRGC hires undergraduate Computer Science and Geography students to work collaboratively to develop IT based applications. Early efforts at using commercial based GIS software for Internet delivery proved frustrating, as the commercial products inhibited the creativity the staff desired. So, while commercial GIS software did exist to support many of our projects, a decision was made to migrate almost all of the development work into a FOSS4G paradigm, as the open source solutions allowed us to provide greater flexibility and responsiveness to the application. In addition, the FOSS4G solutions allowed our clients to enter into Internet based IT solutions for a minimal cost. Examples of some of the ESRGC activities with FOSS4G include our use of GeoDashboards for the State of Maryland, Oklahoma, and the Federal Government, the GNAPPWorks Initiative, and municipal applications for local and regional organizations. 4.1.1 GeoDashboards Although each geodashboard we create are different, they follow the same general architecture: 1. Data is stored in PostGRES with PostGIS 2. The web server is node.js 3. Front end web pages are written in leaflet.js Lembo 194
4. Data is sent to the web pages either as GeoJSON directly from PostGIS, or as WMS services from TileMill. The use of Leaflet allows us to create a very responsive GUI, and our connection with PostGRES/PostGIS allows us to issue virtually any kind of SQL or spatial SQL query. PostGres Node.js web server Node.js rest API Html web pages Map Leaflet.js Figure 10 The general architecture of the ESRGC dashboards include the use of node.js as a web server, PostGRES as the back end database, and Leaflet.js for the client-side interface. Examples The ESRGC completed geodashboards for Maryland’s BayStat program, the Maryland Department of Labor, Licensing, and Regulation (DLLR), the State of Oklahoma Licensing and Regulation, and the National Broadband Mapping Initiative, all using the architecture described in Figure 8. Figure 11 Example of Open Source Dashboards for the Maryland Department of Labor, Licensing, and Regulation, and the Maryland BayStat Program. FOSS4G Seoul, South Korea | September 14 th – 19 th , 2015 195
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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
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: Figure 8 The USDA Foodshed project
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
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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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