{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T07:04:06Z","timestamp":1763535846073,"version":"build-2065373602"},"reference-count":80,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T00:00:00Z","timestamp":1617753600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004281","name":"Narodowe Centrum Nauki","doi-asserted-by":"publisher","award":["UMO-2018\/29\/B\/ST10\/00114"],"award-info":[{"award-number":["UMO-2018\/29\/B\/ST10\/00114"]}],"id":[{"id":"10.13039\/501100004281","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Global sensitivity analysis, like variance-based methods for massive raster datasets, is especially computationally costly and memory-intensive, limiting its applicability for commodity cluster computing. The computational effort depends mainly on the number of model runs, the spatial, spectral, and temporal resolutions, the number of criterion maps, and the model complexity. The current Spatially-Explicit Uncertainty and Sensitivity Analysis (SEUSA) approach employs a cluster-based parallel and distributed Python\u2013Dask solution for large-scale spatial problems, which validates and quantifies the robustness of spatial model solutions. This paper presents the design of a framework to perform SEUSA as a Service in a cloud-based environment scalable to very large raster datasets and applicable to various domains, such as landscape assessment, site selection, risk assessment, and land-use management. It incorporates an automated Kubernetes service for container virtualization, comprising a set of microservices to perform SEUSA as a Service. Implementing the proposed framework will contribute to a more robust assessment of spatial multi-criteria decision-making applications, facilitating a broader access to SEUSA by the research community and, consequently, leading to higher quality decision analysis.<\/jats:p>","DOI":"10.3390\/ijgi10040244","type":"journal-article","created":{"date-parts":[[2021,4,7]],"date-time":"2021-04-07T11:31:59Z","timestamp":1617795119000},"page":"244","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Framework for Cloud-Based Spatially-Explicit Uncertainty and Sensitivity Analysis in Spatial Multi-Criteria Models"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0019-607X","authenticated-orcid":false,"given":"Christoph","family":"Erlacher","sequence":"first","affiliation":[{"name":"Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria"},{"name":"Department of Engineering &amp; IT, Spatial Information Management, Carinthia University of Applied Sciences, 9524 Villach, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1168-4060","authenticated-orcid":false,"given":"Karl-Heinrich","family":"Anders","sequence":"additional","affiliation":[{"name":"Department of Engineering &amp; IT, Spatial Information Management, Carinthia University of Applied Sciences, 9524 Villach, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6303-6217","authenticated-orcid":false,"given":"Piotr","family":"Jankowski","sequence":"additional","affiliation":[{"name":"Department of Geography, San Diego State University, San Diego, CA 92182-4493, USA"},{"name":"Institute of Geoecology and Geoinformation, Adam Mickiewicz University, 61-680 Pozna\u0144, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5919-6912","authenticated-orcid":false,"given":"Gernot","family":"Paulus","sequence":"additional","affiliation":[{"name":"Department of Engineering &amp; IT, Spatial Information Management, Carinthia University of Applied Sciences, 9524 Villach, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1860-8458","authenticated-orcid":false,"given":"Thomas","family":"Blaschke","sequence":"additional","affiliation":[{"name":"Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.dss.2018.10.010","article-title":"Spatial Decision Support Systems: Three decades on","volume":"116","author":"Keenan","year":"2019","journal-title":"Decis. Support Syst."},{"key":"ref_2","unstructured":"Simon, H.A. (1977). The New Science of Management Decision, Prentice Hall PTR."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Malczewski, J., and Jankowski, P. (2020). Emerging trends and research frontiers in spatial multicriteria analysis. Int. J. Geogr. Inf. Sci., 1\u201326.","DOI":"10.1080\/13658816.2020.1712403"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Malczewski, J., and Rinner, C. (2015). Multicriteria Decision Analysis in Geographic Information Science, Springer.","DOI":"10.1007\/978-3-540-74757-4"},{"key":"ref_5","unstructured":"Thill, J.-C. (1999). Spatial Multicriteria Decision Making and Analysis, Routledge. [1st ed.]."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1508","DOI":"10.1016\/j.envsoft.2010.04.012","article-title":"How to avoid a perfunctory sensitivity analysis","volume":"25","author":"Saltelli","year":"2010","journal-title":"Environ. Model. Softw."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.envsoft.2015.10.001","article-title":"A modified Sobol\u2032 sensitivity analysis method for decision-making in environmental problems","volume":"75","author":"Ganji","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.envsoft.2014.03.007","article-title":"Spatially-explicit integrated uncertainty and sensitivity analysis of criteria weights in multicriteria land suitability evaluation","volume":"57","author":"Jankowski","year":"2014","journal-title":"Environ. Model. Softw."},{"key":"ref_9","first-page":"217","article-title":"A Framework for Sensitivity Analysis in Spatial Multiple Criteria Evaluation","volume":"Volume LNCS 5266","author":"Cova","year":"2008","journal-title":"GIScience 2008"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1016\/j.scitotenv.2016.02.133","article-title":"Trends in sensitivity analysis practice in the last decade","volume":"568","author":"Ferretti","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2699","DOI":"10.1007\/s00477-018-1535-z","article-title":"Analysis of the influence of parameter and scale uncertainties on a local multi-criteria land use evaluation model","volume":"32","author":"Jankowski","year":"2018","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1080\/13658810802094995","article-title":"Sensitivity analysis of spatial models","volume":"23","author":"Lilburne","year":"2009","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1016\/j.ress.2005.11.014","article-title":"Sensitivity analysis practices: Strategies for model-based inference","volume":"91","author":"Saltelli","year":"2006","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0951-8320(96)00002-6","article-title":"Importance measures in global sensitivity analysis of nonlinear models","volume":"52","author":"Homma","year":"1996","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1080\/13875868.2015.1137578","article-title":"Integrating local multi-criteria evaluation with spatially explicit uncertainty-sensitivity analysis","volume":"16","author":"Jankowski","year":"2016","journal-title":"Spat. Cogn. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.cageo.2013.11.009","article-title":"A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis","volume":"64","author":"Feizizadeh","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_17","unstructured":"Erlacher, C., \u015ealap-Ay\u00e7a, S., Jankowski, P., Anders, K.-H., and Paulus, G. (2016, January 5\u20138). A GPU-based Solution for Accelerating Spatially-Explicit Uncertainty- and Sensitivity Analysis in Multi-Criteria Decision Making. Proceedings of the Spatial Accuracy, Montpellier, France."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1553\/giscience2017_01_s44","article-title":"A GPU-based Parallelization Approach to conduct Spatially-Explicit Uncertainty and Sensitivity Analysis in the Application Domain of Landscape Assessment","volume":"2017","author":"Erlacher","year":"2017","journal-title":"Gi_Forum J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1553\/giscience2019_01_s69","article-title":"Parallel and Distributed Computing for large raster-based Spatial Multicriteria Decision Analysis Problems: A Computational Performance Comparison","volume":"2019","author":"Erlacher","year":"2019","journal-title":"GI_Forum J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"100409","DOI":"10.1016\/j.softx.2020.100409","article-title":"GeoRocket: A scalable and cloud-based data store for big geospatial files","volume":"11","year":"2020","journal-title":"SoftwareX"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.future.2017.11.007","article-title":"A versatile data-intensive computing platform for information retrieval from big geospatial data","volume":"81","author":"Soille","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.compenvurbsys.2016.10.010","article-title":"Utilizing Cloud Computing to address big geospatial data challenges","volume":"61","author":"Yang","year":"2017","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1080\/17538947.2016.1239771","article-title":"Big Data and cloud computing: Innovation opportunities and challenges","volume":"10","author":"Yang","year":"2017","journal-title":"Int. J. Digit. Earth"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"100517","DOI":"10.1016\/j.softx.2020.100517","article-title":"torcpy: Supporting task parallelism in Python","volume":"12","author":"Hadjidoukas","year":"2020","journal-title":"SoftwareX"},{"key":"ref_25","unstructured":"Matthew, R. (2015, January 6\u201312). Dask: Parallel Computation with Blocked algorithms and Task Scheduling. Proceedings of the 14th Python in Science Conference (SciPy 2015), Austin, TX, USA."},{"key":"ref_26","unstructured":"Daniel, J.C. (2019). Data Science with Python and Dask, Manning Publications Co."},{"key":"ref_27","first-page":"407","article-title":"Sensitivity Estimates for Nonlinear Mathematical Models","volume":"1","author":"Sobol","year":"1993","journal-title":"Math. Model. Comput. Exp."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Schmidt, D.C., and Buschmann, F. (2003, January 3\u201310). Patterns, frameworks, and middleware: Their synergistic relationships. Proceedings of the 25th International Conference on Software Engineering, Portland, OR, USA.","DOI":"10.1109\/ICSE.2003.1201256"},{"key":"ref_29","unstructured":"Chapin, L. (2002, January 25\u201330). Research Advances in Middleware for Distributed Systems: State of the Art. Proceedings of the Communication Systems: The State of the Art IFIP 17th World Computer Congress\u2014TC6 Stream on Communication Systems, Montr\u00e9al, QC, Canada."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.cpc.2019.03.018","article-title":"ProIO: An event-based I\/O stream format for protobuf messages","volume":"241","author":"Blyth","year":"2019","journal-title":"Comput. Phys. Commun."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"F\u00fcrhoff, L. (2020). Rethinking the Usage and Experience of Clustering in Web Mapping, Springer.","DOI":"10.7287\/peerj.preprints.27858v1"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"105251","DOI":"10.1016\/j.compag.2020.105251","article-title":"A secure fish farm platform based on blockchain for agriculture data integrity","volume":"170","author":"Hang","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s00354-008-0081-5","article-title":"Cloud Computing: A Perspective Study","volume":"28","author":"Wang","year":"2010","journal-title":"New Gener. Comput."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Mell, P., and Grance, T. (2011). The NIST definition of cloud computing. Recomm. Natl. Inst. Stand. Technol.","DOI":"10.6028\/NIST.SP.800-145"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1145\/1496091.1496100","article-title":"A break in the clouds: Towards a cloud definition","volume":"39","author":"Vaquero","year":"2009","journal-title":"SIGCOMM Comput. Commun. Rev."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Odun-Ayo, I., Ananya, M., Agono, F., and Goddy-Worlu, R. (2018, January 2\u20135). Cloud Computing Architecture: A Critical Analysis. Proceedings of the 2018 18th International Conference on Computational Science and Applications (ICCSA), Melbourne, VIC, Australia.","DOI":"10.1109\/ICCSA.2018.8439638"},{"key":"ref_37","unstructured":"Bokhari, M.U., Shallal, Q.M., and Tamandani, Y.K. (2016, January 16\u201318). Cloud computing service models: A comparative study. Proceedings of the 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1080\/17538947.2011.587547","article-title":"Spatial cloud computing: How can the geospatial sciences use and help shape cloud computing?","volume":"4","author":"Yang","year":"2011","journal-title":"Int. J. Digit. Earth"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"101188","DOI":"10.1016\/j.ijdrr.2019.101188","article-title":"Cloud Computing in natural hazard modeling systems: Current research trends and future directions","volume":"38","author":"Ujjwal","year":"2019","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"55","DOI":"10.5194\/isprsannals-II-4-W2-55-2015","article-title":"Building Spatiotemporal Cloud Platform for Supporting GIS Application","volume":"II-4\/W2","author":"Song","year":"2015","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1007\/s12517-017-3296-2","article-title":"Web GIS and its architecture: A review","volume":"10","author":"Agrawal","year":"2017","journal-title":"Arab. J. Geosci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Yao, X., Li, G., Xia, J., Ben, J., Cao, Q., Zhao, L., Ma, Y., Zhang, L., and Zhu, D. (2020). Enabling the Big Earth Observation Data via Cloud Computing and DGGS: Opportunities and Challenges. Remote Sens., 12.","DOI":"10.3390\/rs12010062"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.comcom.2020.03.017","article-title":"Unmanned aerial vehicle for internet of everything: Opportunities and challenges","volume":"155","author":"Liu","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Cahalane, C., McCarthy, T., and McElhinney, C.P. (2012, January 1\u20133). MIMIC: Mobile mapping point density calculator. Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications, Washington, DC, USA.","DOI":"10.1145\/2345316.2345335"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Shang, S., Shen, J., Wen, J.-R., and Kalnis, P. (2020). Deep understanding of big geospatial data for self-driving cars. Neurocomputing, 308\u2013309.","DOI":"10.1016\/j.neucom.2020.06.119"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"134540","DOI":"10.1016\/j.scitotenv.2019.134540","article-title":"Mapping human\u2019s digital footprints on the Tibetan Plateau from multi-source geospatial big data","volume":"711","author":"Yi","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1080\/15230406.2018.1496036","article-title":"A graph-based approach to detecting tourist movement patterns using social media data","volume":"46","author":"Hu","year":"2019","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Gonzalez, H., Halevy, A., Jensen, C.S., Langen, A., Madhavan, J., Shapley, R., and Shen, W. (2010, January 10\u201311). Google fusion tables: Data management, integration and collaboration in the cloud. Proceedings of the 1st ACM symposium on Cloud computing, Indianapolis, IN, USA.","DOI":"10.1145\/1807128.1807158"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1080\/17538947.2013.769783","article-title":"Redefining the possibility of digital Earth and geosciences with spatial cloud computing","volume":"6","author":"Yang","year":"2013","journal-title":"Int. J. Digit. Earth"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2648","DOI":"10.4304\/jcp.8.10.2648-2655","article-title":"K-Means Method for Grouping in Hybrid MapReduce Cluster","volume":"8","author":"Yang","year":"2013","journal-title":"J. Comput."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.compenvurbsys.2015.04.003","article-title":"Performance improvement techniques for geospatial web services in a cyberinfrastructure environment\u2014A case study with a disaster management portal","volume":"54","author":"Li","year":"2015","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Guo, H., Goodchild, M.F., and Annoni, A. (2020). Geospatial Information Processing Technologies. Manual of Digital Earth, Springer.","DOI":"10.1007\/978-981-32-9915-3"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.cag.2015.02.005","article-title":"A modular software architecture for processing of big geospatial data in the cloud","volume":"49","author":"Senner","year":"2015","journal-title":"Comput. Graph."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.envsoft.2016.07.001","article-title":"Agent-as-a-service-based geospatial service aggregation in the cloud: A case study of flood response","volume":"84","author":"Tan","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.compenvurbsys.2014.06.004","article-title":"Building Model as a Service to support geosciences","volume":"61","author":"Li","year":"2017","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Bordel, B., Alcarria, R., Hern\u00e1ndez, M., and Robles, T. (2019). People-as-a-Service Dilemma: Humanizing Computing Solutions in High-Efficiency Applications. Proceedings, 31.","DOI":"10.3390\/proceedings2019031039"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Guo, H., Goodchild, M.F., and Annoni, A. (2020). Big Data and Cloud Computing. Manual of Digital Earth, Springer.","DOI":"10.1007\/978-981-32-9915-3"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.tra.2019.09.025","article-title":"Collaboration as a service (CaaS) to fully integrate public transportation\u2014Lessons from long distance travel to reimagine mobility as a service","volume":"131","author":"Merkert","year":"2020","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1111\/j.1467-9671.2011.01275.x","article-title":"Local Weighted Linear Combination","volume":"15","author":"Malczewski","year":"2011","journal-title":"Trans. GIS"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"100103","DOI":"10.1016\/j.patter.2020.100103","article-title":"Tackling the Challenges of 21st-Century Open Science and Beyond: A Data Science Lab Approach","volume":"1","author":"Hollaway","year":"2020","journal-title":"Patterns"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Huang, W., Zhang, W., Zhang, D., and Meng, L. (2017). Elastic Spatial Query Processing in OpenStack Cloud Computing Environment for Time-Constraint Data Analysis. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6030084"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Iosifescu-Enescu, I., Matthys, C., Gkonos, C., Iosifescu-Enescu, C.M., and Hurni, L. (2017). Cloud-Based Architectures for Auto-Scalable Web Geoportals towards the Cloudification of the GeoVITe Swiss Academic Geoportal. Isprs Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6070192"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Gomes, V.C.F., Queiroz, G.R., and Ferreira, K.R. (2020). An Overview of Platforms for Big Earth Observation Data Management and Analysis. Remote Sens., 12.","DOI":"10.3390\/rs12081253"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Liu, L., and \u00d6zsu, M.T. (2018). Array Databases. Encyclopedia of Database Systems, Springer.","DOI":"10.1007\/978-1-4614-8265-9"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Mathieu, P.-P., and Aubrecht, C. (2018). Fostering Cross-Disciplinary Earth Science Through Datacube Analytics. Earth Observation Open Science and Innovation, Springer International Publishing.","DOI":"10.1007\/978-3-319-65633-5"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Reiner, B., Hahn, K., H\u00f6fling, G., and Baumann, P. (2002). Hierarchical Storage Support and Management for Large-Scale Multidimensional Array Database Management Systems, Springer.","DOI":"10.1007\/3-540-46146-9_68"},{"key":"ref_67","first-page":"2","article-title":"Vergleich von PostGIS und Rasdaman als Geodatenbanken f\u00fcr gro\u00dfvolumige Bilddatenbest\u00e4nde eines mobilen Mappingsystems","volume":"3","author":"Hein","year":"2017","journal-title":"AGIT J. Angew. Geoinform."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.envsoft.2015.12.002","article-title":"Spatial Global Sensitivity Analysis of High Resolution classified topographic data use in 2D urban flood modelling","volume":"77","author":"Abily","year":"2016","journal-title":"Environ. Model. Softw."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"107522","DOI":"10.1016\/j.ress.2021.107522","article-title":"Functional principal component analysis for global sensitivity analysis of model with spatial output","volume":"211","author":"Perrin","year":"2021","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"107464","DOI":"10.1016\/j.ecolind.2021.107464","article-title":"Ecological vulnerability assessment based on AHP-PSR method and analysis of its single parameter sensitivity and spatial autocorrelation for ecological protection\u2014A case of Weifang City, China","volume":"125","author":"Hu","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"104857","DOI":"10.1016\/j.envsoft.2020.104857","article-title":"Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources","volume":"134","author":"Koo","year":"2020","journal-title":"Environ. Model. Softw."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Thill, J.-C., and Dragicevic, S. (2018). \u2018Can You Fix It?\u2019 Using Variance-Based Sensitivity Analysis to Reduce the Input Space of an Agent-Based Model of Land Use Change. GeoComputational Analysis and Modeling of Regional Systems, Springer International Publishing.","DOI":"10.1007\/978-3-319-59511-5"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.compenvurbsys.2019.02.006","article-title":"Using multiple scale space-time patterns in variance-based global sensitivity analysis for spatially explicit agent-based models","volume":"75","author":"Kang","year":"2019","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Ghanem, R., Higdon, D., and Owhadi, H. (2017). SIMLAB Software for Uncertainty and Sensitivity Analysis. Handbook of Uncertainty Quantification, Springer International Publishing.","DOI":"10.1007\/978-3-319-12385-1"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"97","DOI":"10.21105\/joss.00097","article-title":"SALib: An open-source Python library for Sensitivity Analysis","volume":"2","author":"Herman","year":"2017","journal-title":"J. Open Source Softw."},{"key":"ref_76","unstructured":"Iooss, B., Veiga, S.D., Janon, A., and Pujol, G. (2021, March 30). Sensitivity: Global Sensitivity Analysis of Model Outputs, R (\u22653.0.0) Package Version 1.25.0. Available online: https:\/\/cran.r-project.org\/web\/packages\/sensitivity\/index.html."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"104800","DOI":"10.1016\/j.envsoft.2020.104800","article-title":"A cloud-based framework for sensitivity analysis of natural hazard models","volume":"134","author":"Kc","year":"2020","journal-title":"Environ. Model. Softw."},{"key":"ref_78","unstructured":"Erlacher, C., Jankowski, P., \u015ealap-Ay\u00e7a, S., Anders, K.-H., and Paulus, G. (December, January 30). Development of a High Performance Capabilities for Supporting Spatially-Explicit Uncertainty- and Sensitivity Analysis in Multi-Criteria Decision Making. Proceedings of the Eighth International Conference on Sensitivity Analysis of Model Output, Le Tampon (R\u00e9union), France."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Jankowski, P., Najwer, A., Zwoli\u0144ski, Z., and Niesterowicz, J. (2020). Geodiversity Assessment with Crowdsourced Data and Spatial Multicriteria Analysis. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9120716"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1080\/13658816.2017.1406944","article-title":"A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: An application for a cellular automata-based Urban growth and land-use change model","volume":"32","author":"Jankowski","year":"2018","journal-title":"Int. J. Geogr. Inf. Sci."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/4\/244\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:58:49Z","timestamp":1760363929000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/10\/4\/244"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,7]]},"references-count":80,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["ijgi10040244"],"URL":"https:\/\/doi.org\/10.3390\/ijgi10040244","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2021,4,7]]}}}