ISPRS Int. J. Geo-Inf., Volume 10, Issue 4 (April 2021) – 75 articles
Cover Story (view full-size image): There is an ongoing paradigm shift in geoinformatics. Cloud computing promises to provide almost unlimited availability, reliability, and scalability for memory-intensive and computational demandingspatial analysis, such as Spatially Explicit Uncertainty and Sensitivity Analysis (SEUSA), to quantify the robustness of spatial model solutions. The number of model runs, the spatial, spectral, and temporal resolutions, the number of criterion maps, and the model complexity mainly influence the computational effort. Complex spatial use cases that incorporate massive raster datasets easily exceed local cluster capacity limits by performing SEUSA. Consequently, this study focuses on designing a framework to perform SEUSA as a Service in a cloud-based environment scalable to very large raster datasets and applicable for various spatial domains. View this paper
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