Impact of window size in remote sensing based glacier feature tracking - a study on Chhota Shigri Glacier, Western Himalayas, India

Sangita Kumari, RAAJ. Ramsankaran, Jeffrey P. Walker

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

2 Citations (Scopus)


Knowledge of glacier surface velocity distribution is crucial for many glaciological applications. Among available methods, feature tracking methods are considered the most efficient way to derive glacier surface velocity from remote sensing datasets. However, window size is an inherent parameter of the feature tracking method, which has not been well explored in terms of its impact on the feature tracking performance. This study has investigated the effect of window size on glacier feature tracking accuracy, which is based on an algorithm that seeks offsets of the maximum likelihood of the SAR speckle distribution on repeated satellite images. Here the feature tracking has been performed with window sizes of 8 x 8, 16 x 16 and 32 x 32. The results show that varying the window size can affect the accuracy of estimated velocity by up to 44% of the observed mean velocity. This study suggests that a spatially distributed window size should be used for more accurate feature tracking.

Original languageEnglish
Title of host publicationIGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781538691540
Publication statusPublished - 2019
EventIEEE International Geoscience and Remote Sensing Symposium 2019 - Yokohama, Japan
Duration: 28 Jul 20192 Aug 2019
Conference number: 39th (Website) (Proceedings)


ConferenceIEEE International Geoscience and Remote Sensing Symposium 2019
Abbreviated titleIGARSS 2019
Internet address


  • Glacier surface velocity
  • Himalayan glaciers
  • Image matching
  • Maximum Likelihood
  • Synthetic Aperture Radar

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