7 documents found in 135ms
# 1
Unger, Andrea • Rabe, Daniela • Klemann, Volker • Eggert, Daniel • Dransch, Doris
Abstract: The validation of a simulation model is a crucial task in model development. It involves the comparison of simulation data to observation data and the identification of suitable model parameters. SLIVISU is a Visual Analytics framework that enables geoscientists to perform these tasks for observation data that is sparse and uncertain. Primarily, SLIVISU was designed to evaluate sea level indicators, which are geological or archaeological samples supporting the reconstruction of former sea level over the last ten thousands of years and are compiled in a postgreSQL database system. At the same time, the software aims at supporting the validation of numerical sea-level reconstructions against this data by means of visual analytics.
# 2
Unger, Andrea • Rabe, Daniela • Eggert, Daniel • Dransch, Doris
Abstract: Geoarchives are an important source to understand the interplay of climate and landscape developments in the past. One important example are sediment cores from the ground of lakes. The microfacies-explorer is a Java-based prototype, that provides a tailored combination of visual and data mining methods enabling scientists to explore categorical data from geoarchives.
# 3
Sips, Mike • Dransch, Doris • Eggert, Daniel • Freytag, Johann-Christoph • Hollstein, Andre • (et. al.)
Abstract: GeoMultiSens developed an integrated processing pipeline to support the analysis of homogenized data from various remote sensing archives. The processing pipeline has five main components: (1) visual assessment of remote sensing Earth observations, (2) homogenization of selected Earth observation, (3) efficient data management with XtreemFS, (4) Python-based parallel processing and analysis algorithms implemented in a Flink cloud environment, and (5) visual exploration of the results. GeoMultiSens currently supports the classification of land-cover for Europe.
# 4
Eggert, Daniel • Sips, Mike • Dransch, Doris
Abstract: gms-vis is a web-based implementation of our visual-analytics approach for assessing remote-sensing data. It is implemented based on the GWT framework. Once deployed through a webserver it acts as the user interface for the GeoMultiSens (GMS) platform. Within the interface users can intuitively define spatial, temporal as well as quality constraints, for remote sensing scenes. A heatmap enables the user to assess the spatial distribution of selected scenes, while a time histogram allows the user to assess their temporal distribution. Finally, users can specify a workflow which will be executed by the GeoMultiSens platform. Though gms-vis is part of the GeoMultiSens platform, it is relatively self-contained and can be attached to different analysis frameworks and platforms with reasonable effort.
# 5
Eggert, Daniel • Sips, Mike • Dransch, Doris
Abstract: Gms-index-mediator is a standalone index for spatio-temporal data acting as a mediator between an application and a database. Even modern databases need several minutes to execute a spatio-temporal query to huge tables containing several million entries. Our index-mediator speeds the execution of such queries up by several magnitues, resulting in response times around 100ms. This version is tailored towards the GeoMultiSens database, but can be adapted to work with custom table layouts with reasonable effort.
# 6
Eggert, Daniel • Köthur, Patrick • Dransch, Doris
Abstract: The processing of Persistent Scatterer Interferometry (PSI) data and the estimation of displacement is a nonlinear and user-driven procedure that can introduce large errors for noisy backscatter points. Results may differ significantly depending on chosen thresholds, filter settings, constraints and final interpretation. Thus the identification of valid PS with rather low errors in the SAR data is a crucial step in the PSI workflow. PSI-Explorer is a scientific prototype of our visual-analytics (VA) approach supporting this important task. The prototype is written in Java and operates on Matlab files.
# 7
Rawald, Tobias • Sips, Mike • Dransch, Doris
Abstract: PyRQA is a tool to conduct recurrence quantification analysis (RQA) and to create recurrence plots in a massively parallel manner using the OpenCL framework. It is designed to process very long time series consisting of hundreds of thousands of data points efficiently.
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