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Open AccessArticle

Retrieval of Similar Evolution Patterns from Satellite Image Time Series

Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, Bulevardul Iuliu Maniu 1-3, Bucharest 061071, Romania
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This paper is an extended version of our paper published in 2018 41st International Conference on Telecommunications and Signal Processing (TSP) Held in Athens, Greece, 4–6 July 2018.
Appl. Sci. 2018, 8(12), 2435; https://doi.org/10.3390/app8122435
Received: 29 October 2018 / Revised: 16 November 2018 / Accepted: 22 November 2018 / Published: 1 December 2018
Technological evolution in the remote sensing domain has allowed the acquisition of large archives of satellite image time series (SITS) for Earth Observation. In this context, the need to interpret Earth Observation image time series is continuously increasing and the extraction of information from these archives has become difficult without adequate tools. In this paper, we propose a fast and effective two-step technique for the retrieval of spatio-temporal patterns that are similar to a given query. The method is based on a query-by-example procedure whose inputs are evolution patterns provided by the end-user and outputs are other similar spatio-temporal patterns. The comparison between the temporal sequences and the queries is performed using the Dynamic Time Warping alignment method, whereas the separation between similar and non-similar patterns is determined via Expectation-Maximization. The experiments, which are assessed on both short and long SITS, prove the effectiveness of the proposed SITS retrieval method for different application scenarios. For the short SITS, we considered two application scenarios, namely the construction of two accumulation lakes and flooding caused by heavy rain. For the long SITS, we used a database formed of 88 Landsat images, and we showed that the proposed method is able to retrieve similar patterns of land cover and land use. View Full-Text
Keywords: pattern recognition; dynamic time warping; maximum likelihood criterion; similarity measure; multitemporal data; multispectral information pattern recognition; dynamic time warping; maximum likelihood criterion; similarity measure; multitemporal data; multispectral information
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Radoi, A.; Burileanu, C. Retrieval of Similar Evolution Patterns from Satellite Image Time Series. Appl. Sci. 2018, 8, 2435.

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