the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Rock and snow differentiation from colour (RGB) images
Abstract. We present a new method for differentiating snow and rock in colour imagery for application (including by remote sensing non-specialists) to multidisciplinary geospatial analyses in the Polar Regions (e.g. glaciology, geology, and biology). Existing methods for differentiating rock from snow and ice for land cover analysis in the Polar Regions rely on infrared or near-infrared imagery (e.g. the Normalised Difference Snow Index, NDSI). However, colour images are more abundant and higher resolution. To enable application of this resource, we present and review supervised and unsupervised methods for differentiating rock and snow from colour images. Whilst the unsupervised methods (fuzzy membership and a normalised difference index) are unable to accurately differentiate snow and rock from colour images, supervised classification (Maximum Likelihood Classification (MLC) and a new approach, Polynomial Thresholding (PT)) do achieve high classification accuracies (95 ± 2 % for PT and 94 ± 3 % for MLC, compared with manual delineation). The greater user control of PT achieves better accuracies than MLC in shaded areas (a challenge in high latitudes) and less extensive outcrops. We present the workflow for the new PT method, and provide a calibration tool for its implementation. This approach improves the possible resolution of Polar land cover analysis, and the increases the volume of data that can be utilised.
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Interactive discussion
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RC1: 'Review', Anonymous Referee #1, 02 Sep 2020
- AC1: 'Reply to Anonymous Reviewer RC1', Alex Burton-Johnson, 13 Nov 2020
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RC2: 'Comments on 'tc-2020-115'', Anonymous Referee #2, 02 Sep 2020
- AC2: 'Reply to Anonymous Reviewer RC2', Alex Burton-Johnson, 13 Nov 2020
Interactive discussion
-
RC1: 'Review', Anonymous Referee #1, 02 Sep 2020
- AC1: 'Reply to Anonymous Reviewer RC1', Alex Burton-Johnson, 13 Nov 2020
-
RC2: 'Comments on 'tc-2020-115'', Anonymous Referee #2, 02 Sep 2020
- AC2: 'Reply to Anonymous Reviewer RC2', Alex Burton-Johnson, 13 Nov 2020
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Cited
3 citations as recorded by crossref.
- Image analysis and LSTM methods for forecasting surficial displacements of a landslide triggered by snowfall and rainfall Y. Liu et al. 10.1007/s10346-024-02328-3
- Comparison of Automatic Classification Methods for Identification of Ice Surfaces from Unmanned-Aerial-Vehicle-Borne RGB Imagery J. Jech et al. 10.3390/app132011400
- A low-cost and open-source approach for supraglacial debris thickness mapping using UAV-based infrared thermography J. Messmer & A. Groos 10.5194/tc-18-719-2024
Alex Burton-Johnson
Nina Sofia Wyniawskyj
This preprint has been withdrawn.
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Supplement
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