The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 485–492, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-485-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 485–492, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B4-2020-485-2020

  25 Aug 2020

25 Aug 2020

TOWARDS INTELLIGENT GEO-DATABASE SUPPORT FOR EARTH SYSTEM OBSERVATION: IMPROVING THE PREPARATION AND ANALYSIS OF BIG SPATIO-TEMPORAL RASTER DATA

N. Mazroob Semnani1, M. Breunig1, M. Al-Doori2, A. Heck1, P. Kuper1, and H. Kutterer1 N. Mazroob Semnani et al.
  • 1Geodetic Institute, Karlsruhe Institute of Technology, Germany
  • 2College of Information Technology, University of Fujairah, United Arab Emirates

Keywords: Spatio-Temporal Data Management, Spatio-Temporal Data Processing, Big Geospatial Raster Data, Intelligent Geospatial Data Analysis

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.