Multisensor Earth observation systems: data fusion

Valentin Atanassov; Denitsa Borisova; Doyno Petkov; Ventzeslav Dimitrov; Hristina Vasileva; Margarita Goranova

doi:10.1117/12.2325731

25 September 2018 Multisensor Earth observation systems: data fusion

Valentin Atanassov, Denitsa Borisova, Doyno Petkov, Ventzeslav Dimitrov, Hristina Vasileva, Margarita Goranova

Proceedings Volume 10785, Sensors, Systems, and Next-Generation Satellites XXII; 107851R (2018) https://doi.org/10.1117/12.2325731
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Advancements in modern technologies, such as remote sensing systems and instruments have led to rapid developments in the field of Earth observation /EO/. As a result, enormous volumes of EO data with various spatial and spectral resolutions are obtained. However, the expected enhancements in the classification accuracy still have not been reached, due to the complexity of the remote sensing measurements and the big volume of data that need to be processed. The last leads to the necessity of development and improvement of methods and techniques for data obtaining and analysis. The methods include the validation multi-sensor systems, the processing technique of big data, and the object identification and classification methods for improving information quality through data fusion. To achieve correct information with highest accuracy in data analyzing and interpreting, researchers have to apply these methods and to create technologies for obtaining and integrating data from different Earth Observation Systems /EOS/. For gathering and using all of the information a local and regional EOS of Systems needs to be established. By creating such local EOS of Systems more extensive information could be collected, analyzed and retrieved. In this paper a local system is presented, focusing on the description of the ground component. The main sensors embedded in the system are spectrometers. The working range of the multi-sensor system is VIS-NIR-SWIR. Thus, by applying the data fusion methods, combining images and spectral information, a more accurate thematic interpretation is achieved. Example illustrating the benefits of a multisensor system data fusing is presented and discussed.

Citation Download Citation

Valentin Atanassov, Denitsa Borisova, Doyno Petkov, Ventzeslav Dimitrov, Hristina Vasileva, and Margarita Goranova "Multisensor Earth observation systems: data fusion", Proc. SPIE 10785, Sensors, Systems, and Next-Generation Satellites XXII, 107851R (25 September 2018); https://doi.org/10.1117/12.2325731

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KEYWORDS

Image fusion

Data fusion

Sensors

Data acquisition

Remote sensing

Spectrometers

Spectral resolution

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