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Preprocessed sentinel-1 data via a web service focused on agricultural field monitoring

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ESA provides Sentinel-1 synthetic aperture radar satellite data freely for research and industry. The Sentinel-1 data have shown the potential for remotely monitoring conditions in individual agricultural fields on a weekly basis. Researchers have access to the same Sentinel-1 dataset, so independent validation should be possible. Well documented studies performed with Sentinel-1 will allow other researchers the ability to reproduce the experiments and either validate or repudiate the presented findings. Based on the current state-of-the-art study, a web service was provided for the agricultural domain, which can be downloaded freely from Github. The running web service provides the ability to monitor local conditions by using the recorded Sentinel-1 information, combined with a priori knowledge from broad acre fields. Correlating the Sentinel-1 data to actual conditions related to a specific application is still a task that individual researchers must perform to utilize the service. In this paper, we present our methodology for converting the Sentinel-1 data to a form that is more accessible to researchers in the agricultural domain. Therefore, the goal of the current study was to make the Sentinel-1 data available efficiently, so that the experts in this field can focus on correlating and comparing it to reference data and measurements collected in the field. The function of the web service is illustrated with concrete application examples in the agricultural domain.
Original languageEnglish
Article number8715769
JournalIEEE Access
Pages (from-to)65139-65149
Number of pages11
Publication statusPublished - 31 May 2019

    Research areas

  • data acquisition, image classification, machine learning, Synthetic aperture radar

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