1. TOWARDS INTELLIGENT GEO-DATABASE SUPPORT FOR EARTH SYSTEM OBSERVATION: IMPROVING THE PREPARATION AND ANALYSIS OF BIG SPATIO-TEMPORAL RASTER DATA
- Author
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Martin Breunig, Alexandra Heck, Mulhim Al-Doori, Hansjoerg Kutterer, Paul Vincent Kuper, and N. Mazroob Semnani
- Subjects
lcsh:Applied optics. Photonics ,010504 meteorology & atmospheric sciences ,Computer science ,Remote sensing application ,Real-time computing ,0211 other engineering and technologies ,Geo database ,02 engineering and technology ,Intelligent Geospatial Data Analysis ,01 natural sciences ,lcsh:Technology ,Raster data ,Interferometric synthetic aperture radar ,ddc:550 ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,lcsh:T ,lcsh:TA1501-1820 ,Term (time) ,Earth system science ,Earth sciences ,Big Geospatial Raster Data ,Remote sensing (archaeology) ,lcsh:TA1-2040 ,Data quality ,Spatio-Temporal Data Management ,Spatio-Temporal Data Processing ,lcsh:Engineering (General). Civil engineering (General) - Abstract
The European COPERNICUS program provides an unprecedented breakthrough in the broad use and application of satellite remote sensing data. Maintained on a sustainable basis, the COPERNICUS system is operated on a free-and-open data policy. Its guaranteed availability in the long term attracts a broader community to remote sensing applications. In general, the increasing amount of satellite remote sensing data opens the door to the diverse and advanced analysis of this data for earth system science.However, the preparation of the data for dedicated processing is still inefficient as it requires time-consuming operator interaction based on advanced technical skills. Thus, the involved scientists have to spend significant parts of the available project budget rather on data preparation than on science. In addition, the analysis of the rich content of the remote sensing data requires new concepts for better extraction of promising structures and signals as an effective basis for further analysis.In this paper we propose approaches to improve the preparation of satellite remote sensing data by a geo-database. Thus the time needed and the errors possibly introduced by human interaction are minimized. In addition, it is recommended to improve data quality and the analysis of the data by incorporating Artificial Intelligence methods. A use case for data preparation and analysis is presented for earth surface deformation analysis in the Upper Rhine Valley, Germany, based on Persistent Scatterer Interferometric Synthetic Aperture Radar data. Finally, we give an outlook on our future research.
- Published
- 2020