Exploratory mapping of blue ice regions in Antarctica using very high resolution satellite remote sensing data

Jawak, Shridhar D.; Luis, Alvarinho J.; Pandit, Prashant H.; Wankhede, Sagar F.; Convey, Peter ORCID: https://orcid.org/0000-0001-8497-9903; Fretwell, Peter T. ORCID: https://orcid.org/0000-0002-1988-5844. 2023 Exploratory mapping of blue ice regions in Antarctica using very high resolution satellite remote sensing data [in special issue: Satellite Earth Observation of Climate Change Effects on Glaciers and Ice Sheets] Remote Sensing, 15 (5), 1287. 40, pp. https://doi.org/10.3390/rs15051287

Before downloading, please read NORA policies.

Preview

Text (Open Access)
© 2023 by the authors. Licensee MDPI, Basel, Switzerland.
remotesensing-15-01287-v2.pdf - Published Version
Available under License Creative Commons Attribution 4.0.
Download (7MB) | Preview

Official URL: https://doi.org/10.3390/rs15051287

Abstract/Summary

Mapping spatiotemporal changes in the distribution of blue ice regions (BIRs) in Antarctica requires repeated, precise, and high-resolution baseline maps of the blue ice extent. This study demonstrated the design and application of a newly-developed semi-automatic method to map BIRs in the Antarctic environment using very high-resolution (VHR) WorldView-2 (WV-2) satellite images. We discussed the potential of VHR satellite data for the mapping of BIRs in the Antarctic environment using a customized normalized-difference blue-ice index (NDBI) method devised using yellow, green, and near-infrared spectral bands of WV-2 data. We compared the viability of the newly developed customized NDBI approach against state-of-the-art target detection (TD), spectral processing (SP) and pixel-wise supervised (PSC) feature extraction (FE) approaches. Four semi-automatic FE approaches (three existing plus one newly developed) consisting of 16 standalone FE methods (12 existing + four customized) were evaluated using an extensive quantitative and comparative assessment for mapping BIRs in the vicinity of Schirmacher Oasis, on the continental Antarctic coastline. The results suggested that the customized NDBI approach gave a superior performance and the highest statistical stability when compared with existing FE techniques. The customized NDBI generally rendered the lowest level of misclassification (average RMSE = 654.48 ± 58.26 m2), followed by TD (average RMSE = 987.81 ± 55.05 m2), SP (average RMSE = 1327.09 ± 127.83 m2) and PSC (average RMSE = 2259.43 ± 115.36 m2) for mapping BIRs. Our results indicated that the use of the customized NDBI approach can greatly improve the semi-automatic mapping of BIRs in the Antarctic environment. This study presents the first refined map of distribution of BIRs around the Schirmacher Oasis. The total area of blue ice in the study area was estimated to be 106.875 km2, approximately 61% of the study area. The WV-2 derived BIR map area presented in this study locally refined the existing BIR map derived using Landsat Enhanced Thematic Mapper Plus (ETM+) and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based mosaic of Antarctica (MOA) dataset by ~31% (~33.40 km2). Finally, we discussed the practical challenges and future directions in mapping BIRs across Antarctica.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.3390/rs15051287
ISSN:	20724292
Additional Keywords:	semi-automated classification; blue ice; WorldView-2; Antarctica; normalized spectral index ratio; very high resolution remote sensing; supraglacial features; blue ice index
Date made live:	02 Mar 2023 13:48 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533762

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.3390/rs15051287

ISSN:

20724292

Additional Keywords:

semi-automated classification; blue ice; WorldView-2; Antarctica; normalized spectral index ratio; very high resolution remote sensing; supraglacial features; blue ice index

Date made live:

02 Mar 2023 13:48 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/533762