An interactive platform for the analysis of landscape patterns: a cloud-based parallel approach

References

• Adamczyk, J., and D. Tiede. 2017. “ZonalMetrics-a Python Toolbox for Zonal Landscape Structure Analysis.” Computers & Geosciences 99: 91–99. doi:10.1016/j.cageo.2016.11.005.
   Web of Science ®Google Scholar
• Amazon, E. C. 2010. “Amazon Elastic Compute Cloud (Amazon Ec2).” Amazon Elastic Compute Cloud (Amazon EC2).
   Google Scholar
• Andrienko, G., N. Andrienko, J. Dykes, M. J. Kraak, A. Robinson, and H. Schumann. 2016. “GeoVisual Analytics: Interactivity, Dynamics, and Scale.” Cartography and Geographic Information Science 43 (1): 1–2. doi:10.1080/15230406.2016.1095006.
   Web of Science ®Google Scholar
• Andrienko, G. L., and N. V. Andrienko. 1999. “Interactive Maps for Visual Data Exploration.” International Journal of Geographical Information Science 13 (4): 355–374. doi:10.1080/136588199241247.
   Web of Science ®Google Scholar
• Anselin, L. 1993. The Moran Scatterplot as an ESDA Tool to Assess Local Instability in Spatial Association. (pp. 111-125). Morgantown, WV: Regional Research Institute, West Virginia University.
   Google Scholar
• Baranski, B., T. Foerster, B. Schäffer, and K. Lange. 2011. “Matching INSPIRE Quality of Service Requirements with Hybrid Clouds.” Transactions in GIS 15: 125–142. doi:10.1111/tgis.2011.15.issue-s1.
   Web of Science ®Google Scholar
• Baranski, B., B. Schaeffer, and R. Redweik. 2010. “Geoprocessing in the Clouds.” OSGeo Journal 8 (1): 5.
   Google Scholar
• Blaschke, T., D. Tiede, and M. Heurich. 2004. “3D Landscape Metrics to Modelling Forest Structure and Diversity Based on Laser Scanning Data.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 36 (8/W2): 129–132.
   Google Scholar
• Chabot, C., C. Stolte, and P. Hanrahan. 2003. Tableau Software.
   Google Scholar
• Chertov, O., A. Komarov, A. Mikhailov, G. Andrienko, N. Andrienko, and P. Gatalsky. 2005. “Geovisualization of Forest Simulation Modelling Results: A Case Study of Carbon Sequestration and Biodiversity.” Computers and Electronics in Agriculture 49 (1): 175–191. doi:10.1016/j.compag.2005.02.010.
   Web of Science ®Google Scholar
• Delmelle, E., C. Dony, I. Casas, M. Jia, and W. Tang. 2014. “Visualizing the Impact of Space-Time Uncertainties on Dengue Fever Patterns.” International Journal of Geographical Information Science 28 (5): 1107–1127. doi:10.1080/13658816.2013.871285.
   Web of Science ®Google Scholar
• Delmelle, E., C. Kim, N. Xiao, and W. Chen. 2013. “Methods for Space-Time Analysis and Modeling: An Overview.” International Journal of Applied Geospatial Research (IJAGR) 4 (4): 1–18. doi:10.4018/IJAGR.
   Google Scholar
• Desjardins, M. R., Hohl, A., Griffith, A., & Delmelle, E. (2018a). A space–time parallel framework for fine-scale visualization of pollen levels across the Eastern United States. Cartography and Geographic Information Science, 1-13.
   Google Scholar
• Desjardins, M. R., A. Whiteman, I. Casas, and E. Delmelle. 2018b. “Space-Time Clusters and Co-Occurrence of Chikungunya and Dengue Fever in Colombia from 2015 to 2016.” Acta Tropica 185: 77–85. doi:10.1016/j.actatropica.2018.04.023.
   PubMed Web of Science ®Google Scholar
• Galster, G., R. Hanson, M. R. Ratcliffe, H. Wolman, S. Coleman, and J. Freihage. 2001. “Wrestling Sprawl to the Ground: Defining and Measuring an Elusive Concept.” Housing Policy Debate 12 (4): 681–717. doi:10.1080/10511482.2001.9521426.
   Web of Science ®Google Scholar
• Gong, J., P. Yue, and H. Zhou. 2010. “Geoprocessing in the Microsoft Cloud Computing Platform-Azure.” In Paper presented at the proceedings the joint symposium of ISPRS technical commission IV & autocarto. Orlando, Florida, USA.
   Google Scholar
• Gong, P., J. Wang, L. Yu, Y. Zhao, Y. Zhao, L. Liang, Z. Niu, et al. 2013. “Finer Resolution Observation and Monitoring of Global Land Cover: First Mapping Results with Landsat TM and ETM+ Data.” International Journal of Remote Sensing 34 (7): 2607–2654. doi:10.1080/01431161.2012.748992.
   Web of Science ®Google Scholar
• Gong, Z., W. Tang, and J.-C. Thill. 2012. “Parallelization of Ensemble Neural Networks for Spatial Land-Use Modeling.” In Paper Presented at the Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks. Redondo Beach, CA, USA.
   Google Scholar
• Gustafson, E. J. 1998. “Quantifying Landscape Spatial Pattern: What Is the State of the Art?” Ecosystems 1 (2): 143–156. doi:10.1007/s100219900011.
   Web of Science ®Google Scholar
• Hargis, C. D., J. A. Bissonette, and J. L. David. 1998. “The Behavior of Landscape Metrics Commonly Used in the Study of Habitat Fragmentation.” Landscape Ecology 13 (3): 167–186. doi:10.1023/A:1007965018633.
   Web of Science ®Google Scholar
• Hazen, B. C., and M. W. Berry. 1997. “The Simulation of Land-Cover Change Using a Distributed Computing Environment.” Simulation Practice and Theory 5 (6): 489–514. doi:10.1016/S0928-4869(96)00026-2.
   Google Scholar
• Hohl, A., E. M. Delmelle, and W. Tang. 2015. “Spatiotemporal Domain Decomposition for Massive Computation of Space-Time Kernel Density.” ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences 2 (4).
   Google Scholar
• Hohl, A., E. Delmelle, W. Tang, and I. Casas. 2016. “Accelerating the Discovery of Space-Time Patterns of Infectious Diseases Using Parallel Computing.” Spatial and Spatio-Temporal Epidemiology 19: 10–20. doi:10.1016/j.sste.2016.05.002.
   PubMed Web of Science ®Google Scholar
• Huang, Q., C. Yang, K. Benedict, S. Chen, A. Rezgui, and J. Xie. 2013. “Utilize Cloud Computing to Support Dust Storm Forecasting.” International Journal of Digital Earth 6 (4): 338–355. doi:10.1080/17538947.2012.749949.
   Web of Science ®Google Scholar
• Irwin, E. G., and N. E. Bockstael. 2007. “The Evolution of Urban Sprawl: Evidence of Spatial Heterogeneity and Increasing Land Fragmentation.” Proceedings of the National Academy of Sciences 104 (52): 20672–20677. doi:10.1073/pnas.0705527105.
   PubMed Web of Science ®Google Scholar
• Ji, W., M. Jia, R. W. Twibell, and K. Underhill. 2006. “Characterizing Urban Sprawl Using Multi-Stage Remote Sensing Images and Landscape Metrics.” Computers, Environment and Urban Systems 30 (6): 861–879. doi:10.1016/j.compenvurbsys.2005.09.002.
   Web of Science ®Google Scholar
• Jolliffe, I. 2002. Principal Component Analysis (pp. 1094-1096). Springer Berlin Heidelberg.
   Google Scholar
• Kalluri, S. N. V., J. Jájá, D. A. Bader, Z. Zhang, J. R. G. Townshend, and H. Fallah-Adl. 2000. “High Performance Computing Algorithms for Land Cover Dynamics Using Remote Sensing Data.” International Journal of Remote Sensing 21 (6–7): 1513–1536. doi:10.1080/014311600210290.
   Web of Science ®Google Scholar
• Kinkeldey, C. 2014. “A Concept for Uncertainty-Aware Analysis of Land Cover Change Using Geovisual Analytics.” ISPRS International Journal of Geo-Information 3 (3): 1122–1138. doi:10.3390/ijgi3031122.
   Web of Science ®Google Scholar
• Kulawiak, M., A. Prospathopoulos, L. Perivoliotis, S. Kioroglou, and A. Stepnowski. 2010. “Interactive Visualization of Marine Pollution Monitoring and Forecasting Data via a Web-Based GIS.” Computers & Geosciences 36 (8): 1069–1080. doi:10.1016/j.cageo.2010.02.008.
   Web of Science ®Google Scholar
• MacEachren, A. M., M. Gahegan, W. Pike, I. Brewer, G. Cai, E. Lengerich, and F. Hardistry. 2004. “Geovisualization for Knowledge Construction and Decision Support.” IEEE Computer Graphics and Applications 24 (1): 13–17.
   PubMed Web of Science ®Google Scholar
• Masek, J. G., F. E. Lindsay, and S. N. Goward. 2000. “Dynamics of Urban Growth in the Washington DC Metropolitan Area, 1973-1996, from Landsat Observations.” International Journal of Remote Sensing 21 (18): 3473–3486. doi:10.1080/014311600750037507.
   Web of Science ®Google Scholar
• McAlpine, C. A., and T. J. Eyre. 2002. “Testing Landscape Metrics as Indicators of Habitat Loss and Fragmentation in Continuous Eucalypt Forests (Queensland, Australia).” Landscape Ecology 17 (8): 711–728. doi:10.1023/A:1022902907827.
   Web of Science ®Google Scholar
• McGarigal, K. (2014). Landscape pattern metrics. Wiley StatsRef: Statistics Reference Online.
   Google Scholar
• McGarigal, K., S. A. Cushman, M. C. Neel, and E. Ene. 2002. FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps.
   Google Scholar
• McGarigal, K., and B. J. Marks. 1994. “Spatial Pattern Analysis Program for Quantifying Landscape Structure.” Dolores (CO): PO Box 606: 67.
   Google Scholar
• Mladenoff, D. J., and B. DeZonia. 1997. APACK 2.0 User’s Guide. Madison, WI, USA: Department of Forest Ecology and Management, University of Wisconsin-Madison.
   Google Scholar
• Mladenoff, D. J., and B. DeZonia. 2004. “APACK 2.23 Analysis Software: User’s Guide.” Published on Internet server http://www.landscape.forest.wisc.edu/projects/apack
   Google Scholar
• Murray, D. G. 2013. Tableau Your Data!: Fast and Easy Visual Analysis with Tableau Software. Indianapolis, IN: John Wiley & Sons.
   Google Scholar
• Nagendra, H., D. K. Munroe, and J. Southworth. 2004. “From Pattern to Process: Landscape Fragmentation and the Analysis of Land Use/Land Cover Change.” Agriculture, Ecosystems & Environment 101 (2): 111–115. doi:10.1016/j.agee.2003.09.003.
   Web of Science ®Google Scholar
• Neene, V., and M. Kabemba. 2017. “Development of a Mobile GIS Property Mapping Application Using Mobile Cloud Computing.” Development 8 (10): 57-68.
   Google Scholar
• Plexida, S. G., A. I. Sfougaris, I. P. Ispikoudis, and V. P. Papanastasis. 2014. “Selecting Landscape Metrics as Indicators of Spatial heterogeneity—A Comparison among Greek Landscapes.” International Journal of Applied Earth Observation and Geoinformation 26: 26–35. doi:10.1016/j.jag.2013.05.001.
   Web of Science ®Google Scholar
• Porta, J., J. Parapar, R. Doallo, F. F. Rivera, I. Santé, and R. Crecente. 2013. “High Performance Genetic Algorithm for Land Use Planning.” Computers, Environment and Urban Systems 37: 45–58. doi:10.1016/j.compenvurbsys.2012.05.003.
   Web of Science ®Google Scholar
• Rempel, R. S., D. Kaukinen, and A. P. Carr. 2012. “Patch Analyst and Patch Grid.” In Ontario Ministry of Natural Resources. Thunder Bay, Ontario: Centre for Northern Forest Ecosystem Research.
   Google Scholar
• Riitters, K. H., R. V. O’neill, C. T. Hunsaker, J. D. Wickham, D. H. Yankee, S. P. Timmins, K. B. Jones, and B. L. Jackson. 1995. “A Factor Analysis of Landscape Pattern and Structure Metrics.” Landscape Ecology 10 (1): 23–39. doi:10.1007/BF00158551.
   Web of Science ®Google Scholar
• Santé, I., F. F. Rivera, R. Crecente, M. Boullón, M. Suárez, J. Porta, J. Parapar, and R. Doallo. 2016. “A Simulated Annealing Algorithm for Zoning in Planning Using Parallel Computing.” Computers, Environment and Urban Systems 59: 95–106. doi:10.1016/j.compenvurbsys.2016.05.005.
   Web of Science ®Google Scholar
• Schiewe, J. 2018. “Task-Oriented Visualization Approaches for Landscape and Urban Change Analysis.” ISPRS International Journal of Geo-Information 7 (8): 288. doi:10.3390/ijgi7080288.
   Web of Science ®Google Scholar
• Schumann, H., and C. Tominski. 2011. “Analytical, Visual and Interactive Concepts for Geo-Visual Analytics.” Journal of Visual Languages & Computing 22 (4): 257–267. doi:10.1016/j.jvlc.2011.03.002.
   Web of Science ®Google Scholar
• Szewrański S., Kazak J., Sylla M., Świąder M. 2017. Spatial Data Analysis with the Use of ArcGIS and Tableau Systems. In: Ivan I., Singleton A., Horák J., Inspektor T. (eds) The Rise of Big Spatial Data. Lecture Notes in Geoinformation and Cartography. Springer, Cham.
   Google Scholar
• Tang, W., D. A. Bennett, and S. Wang. 2011. “A Parallel Agent-Based Model of Land Use Opinions.” Journal of Land Use Science 6 (2–3): 121–135. doi:10.1080/1747423X.2011.558597.
   Google Scholar
• Tang, W., and W. Feng. 2017. “Parallel Map Projection of Vector-Based Big Spatial Data: Coupling Cloud Computing with Graphics Processing Units.” Computers, Environment and Urban Systems 61: 187–197. doi:10.1016/j.compenvurbsys.2014.01.001.
   Web of Science ®Google Scholar
• Tsai, Y.-H. 2005. “Quantifying Urban Form: Compactness Versus’ Sprawl’.” Urban Studies 42 (1): 141–161. doi:10.1080/0042098042000309748.
   Web of Science ®Google Scholar
• Turner, M. G. 1990. “Spatial and Temporal Analysis of Landscape Patterns.” Landscape Ecology 4 (1): 21–30. doi:10.1007/BF02573948.
   Web of Science ®Google Scholar
• Turner, M. G. 1989. “Landscape Ecology: The Effect of Pattern on Process.” Annual Review of Ecology and Systematics 171–197. doi:10.1146/annurev.es.20.110189.001131.
   Google Scholar
• Turner, M. G., and C. Lynn Ruscher. 1988. “Changes in Landscape Patterns in Georgia, USA.” Landscape Ecology 1 (4): 241–251. doi:10.1007/BF00157696.
   Web of Science ®Google Scholar
• Wade, T. G., J. D. Wickham, M. S. Nash, A. C. Neale, K. H. Riitters, and K. Bruce Jones. 2003. “A Comparison of Vector and Raster GIS Methods for Calculating Landscape Metrics Used in Environmental Assessments.” Photogrammetric Engineering & Remote Sensing 69 (12): 1399–1405. doi:10.14358/PERS.69.12.1399.
   Web of Science ®Google Scholar
• Wan, J., D. Zhang, Y. Sun, K. Lin, C. Zou, and H. Cai. 2014. “VCMIA: A Novel Architecture for Integrating Vehicular Cyber-Physical Systems and Mobile Cloud Computing.” Mobile Networks and Applications 19 (2): 153–160. doi:10.1007/s11036-014-0499-6.
   Web of Science ®Google Scholar
• Wang Y., Wang S., Zhou D. 2009. Retrieving and Indexing Spatial Data in the Cloud Computing Environment. In: Jaatun M.G., Zhao G., Rong C. (eds) Cloud Computing. CloudCom 2009. Lecture Notes in Computer Science, vol 5931. Springer, Berlin, Heidelberg.
   Google Scholar
• Wilkinson, B., and C. Allen. 2005. Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers. Upper Saddle River, NJ: Pearson/Prentice Hall.
   Google Scholar
• Wilkinson, B., and M. Allen. 1999. Parallel Programming. Prentice-Hall, Inc. Upper Saddle River, NJ, USA.
   Google Scholar
• Xie, J., C. Yang, B. Zhou, and Q. Huang. 2010. “High-Performance Computing for the Simulation of Dust Storms.” Computers, Environment and Urban Systems 34 (4): 278–290. doi:10.1016/j.compenvurbsys.2009.08.002.
   Web of Science ®Google Scholar
• Yang, C., M. Goodchild, Q. Huang, D. Nebert, R. Raskin, X. Yan, M. Bambacus, and D. Fay. 2011. “Spatial Cloud Computing: How Can the Geospatial Sciences Use and Help Shape Cloud Computing?” International Journal of Digital Earth 4 (4): 305–329. doi:10.1080/17538947.2011.587547.
   Web of Science ®Google Scholar
• Yue, P., H. Zhou, J. Gong, and H. Lei. 2013. “Geoprocessing in Cloud Computing Platforms–A Comparative Analysis.” International Journal of Digital Earth 6 (4): 404–425. doi:10.1080/17538947.2012.748847.
   Web of Science ®Google Scholar