干旱区生态环境知识资源中心(Arid): Exploratory Mapping of Blue Ice Regions in Antarctica Using Very High-Resolution Satellite Remote Sensing Data

Arid

DOI	10.3390/rs15051287
	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; Fretwell, Peter T.
通讯作者	Jawak, SD
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2023
卷号	15 期号:5
英文摘要	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 m(2)), followed by TD (average RMSE = 987.81 +/- 55.05 m(2)), SP (average RMSE = 1327.09 +/- 127.83 m(2)) and PSC (average RMSE = 2259.43 +/- 115.36 m(2)) 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 km(2), 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 similar to 31% (similar to 33.40 km(2)). Finally, we discussed the practical challenges and future directions in mapping BIRs across Antarctica.
英文关键词	semi-automated classification blue ice WorldView-2 Antarctica normalized spectral index ratio very high-resolution remote sensing supraglacial features blue ice index
类型	Article
语种	英语
开放获取类型	Green Accepted, gold
收录类别	SCI-E
WOS记录号	WOS:000948169800001
WOS关键词	EAST ANTARCTICA ; LAMBERT GLACIER ; BYRD GLACIER ; ETM PLUS ; AREAS ; CLASSIFICATION ; EXTRACTION ; IMAGERY ; EXTENT
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/398247
推荐引用方式 GB/T 7714	Jawak, Shridhar D.,Luis, Alvarinho J.,Pandit, Prashant H.,et al. Exploratory Mapping of Blue Ice Regions in Antarctica Using Very High-Resolution Satellite Remote Sensing Data[J],2023,15(5).
APA	Jawak, Shridhar D.,Luis, Alvarinho J.,Pandit, Prashant H.,Wankhede, Sagar F.,Convey, Peter,&Fretwell, Peter T..(2023).Exploratory Mapping of Blue Ice Regions in Antarctica Using Very High-Resolution Satellite Remote Sensing Data.REMOTE SENSING,15(5).
MLA	Jawak, Shridhar D.,et al."Exploratory Mapping of Blue Ice Regions in Antarctica Using Very High-Resolution Satellite Remote Sensing Data".REMOTE SENSING 15.5(2023).