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Remote sensing has evolved into a multidisciplinary field involving many different areas such as sensor technology, computing, and advanced applications. Information extraction now plays a fundamental role in the exploitation of the massive amount of data collected by earth observation instruments....

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Bibliographic Details
Published in:Proceedings of the IEEE 2019-12, Vol.107 (12), p.2306-2307
Main Authors: Zhang, B., Zeng, Y., Wu, Q., Zhang, R., Magoun, A. B., Chen, Z., Peng, D., Benediktsson, J. A., Liu, B., Zou, L., Li, J., Plaza, A., Shenai, K.
Format: Article
Language:English
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Summary:Remote sensing has evolved into a multidisciplinary field involving many different areas such as sensor technology, computing, and advanced applications. Information extraction now plays a fundamental role in the exploitation of the massive amount of data collected by earth observation instruments. In this Point of View, the authors analyze the evolution of this field, identifying three main phases in its development. The first period, which was marked by advances in digital signal processing, led to a significant development of statistical processing methods. The second phase was based on advances in physical models and brought an era of quantitative remote sensing which lasted until the first decade of this century. In the third and current period, information extraction techniques are gradually adopting advanced artificial intelligence models in an effort to cope with the tremendous increase in data volume. This article describes some of these recent advances and addresses challenges caused by the 4Vs (volume, velocity, variety, and veracity) of big data. Finally, the authors offer insight into future directions in this multidisciplinary field.
ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2019.2953434