Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Weber, Helga; Riffler, Michael; Nõges, T.; Wunderle, Stefan (2016). Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method. Remote sensing of environment, 174, pp. 329-340. Elsevier 10.1016/j.rse.2015.12.014

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Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Item Type:

Journal Article (Original Article)


08 Faculty of Science > Institute of Geography > Physical Geography > Unit Remote Sensing
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography
08 Faculty of Science > Institute of Geography > Physical Geography

Graduate School:

Graduate School of Climate Sciences

UniBE Contributor:

Weber, Helga, Riffler, Michael, Wunderle, Stefan


900 History > 910 Geography & travel
500 Science > 550 Earth sciences & geology








Monika Wälti-Stampfli

Date Deposited:

28 Jan 2016 15:24

Last Modified:

05 Dec 2022 14:51

Publisher DOI:





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