In recent years, the importance of EO data has been widely acknowledged by both government and science communities for Earth system science research and a variety of applications, including disaster response, environmental planning, global change, insurance, and private investment.
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A series of EO data products collected from NASA’s Atmospheric Scientific Data Center (ASDC) are used in the tests and the results prove the proposed framework is efficient to solve different problems in interpreting EO data without compromising their original content.Įarth Observing System (EOS) produces big remote sensing data, which record and capture long-term facts of land surface, solid earth, atmosphere and oceans. The research investigates four key technical aspects: (i) designing a generic plug-in framework for consuming different types of EO data (ii) implementing the framework to fix the errors in GIS when using GDAL to understand EO data and (iii) developing extension for commercial and open source GIS ( i.e., ArcGIS and QGIS) to demonstrate the usability of the proposed framework and its implementation in GDAL. To address this gap between EO data and GIS, the barriers and strategies of integrating various types of EO data with GIS are explored, especially with the popular Geospatial Data Abstraction Library (GDAL) that is used by many GISs to access EO data. However, it is challenging for GIS to understand traditional EO data formats (e.g., Hierarchical Data Format (HDF)) given the different contents and formats in the two domains. Earth Observation (EO) data are critical for many Geographic Information System (GIS)-based decision support systems to provide factual information.
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