Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite

Chengfei Jiang; Mingsen Lin; Ruixue Cao; Hao Wei; Lijian Shi; Bin Cheng; Yongjun Jia; Qimao Wang

doi:10.1007/s13131-022-2067-4

Volume 42 Issue 5

May 2023

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Article Navigation > Acta Oceanologica Sinica > 2023 > 42(5): 179-191

Chengfei Jiang, Mingsen Lin, Ruixue Cao, Hao Wei, Lijian Shi, Bin Cheng, Yongjun Jia, Qimao Wang. Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite[J]. Acta Oceanologica Sinica, 2023, 42(5): 179-191. doi: 10.1007/s13131-022-2067-4

Citation:

Chengfei Jiang, Mingsen Lin, Ruixue Cao, Hao Wei, Lijian Shi, Bin Cheng, Yongjun Jia, Qimao Wang. Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite[J]. Acta Oceanologica Sinica, 2023, 42(5): 179-191. doi: 10.1007/s13131-022-2067-4

Citation:

Chengfei Jiang, Mingsen Lin, Ruixue Cao, Hao Wei, Lijian Shi, Bin Cheng, Yongjun Jia, Qimao Wang. Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite[J]. Acta Oceanologica Sinica, 2023, 42(5): 179-191. doi: 10.1007/s13131-022-2067-4

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Classification of ice and water in the Arctic using radar altimeter and microwave radiometer data from HY-2B satellite

doi: 10.1007/s13131-022-2067-4

Chengfei Jiang^{1, 2, 3, 4},
Mingsen Lin^{2, 3, 4
,
,},
Ruixue Cao⁵,
Hao Wei¹,
Lijian Shi^{2, 3, 4},
Bin Cheng⁶,
Yongjun Jia^{2, 3, 4},
Qimao Wang^{2, 3, 4}

1.
School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
2.
National Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 100081, China
3.
Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
4.
Key Laboratory of Space Ocean Remote Sensing and Application, State Oceanic Administration, Beijing 100081, China
5.
College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China
6.
Finnish Meteorological Institute, Helsinki FI-00560, Finland

Funds: The National Key Research and Development Program of China under contract Nos 2021YFC2803300, 2018YFC1407200, 2016YFC1401000 and 2018YFC1407203; the Impact and Response of Antarctic Seas to Climate Change, IRASCC2020-2022 under contract No. 01-01-03; the National Natural Science Foundation of China under contract Nos 41876204, 41941008, 41941013 and 41630969; the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) under contract No. GML2019ZD0302.

More Information

Corresponding author: mslin@mail.nsoas.org.cn
Received Date: 2021-12-07
Accepted Date: 2022-06-21

Available Online: 2023-04-03

Publish Date: 2023-05-25

Abstract

Abstract

Several Chinese marine satellites have been launched in recent years. Monitoring sea ice and the ocean in the Arctic is of great importance for climate research. Sea ice in the Arctic has changed rapidly during the past few decades with respect to the extent and thickness. In this study, we applied combined passive and active microwave data from the Chinese HaiYang-2B (HY-2B) satellite to classify ice and sea water in the Arctic. We use data from a radar altimeter (RA) and a calibration microwave radiometer (CMR) to discriminate between ice and water by applying several approaches (1) the single parameter threshold criteria, (2) the multi-parameters linear segmentations and (3) the K-means clustering. The results yielded by these methods were in good agreement (classification accuracy >95%) with the Satellite Application Facility on Ocean and Sea Ice products between November and April. For other months (May–October), however, the agreement was less good (lowest classification accuracy approximate 85% in summer). A hybrid approach combined with graphical ice edges detection and microwave radar waveform analysis is therefore developed. A visual comparison with SAR images suggested the hybrid approach results greatly improved the ice and water discrimination in summer. This study demonstrated that multi-sensors (RA and CMR) configurations from HY satellites can offer comparable polar earth observation to the European Space Agency and NOAA satellite products.
- Arctic,
- active microwave data,
- passive microwave data,
- sea ice,
- seawater

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References(45)

References

Aaboe S, Breivik L A, Eastwood S. 2021. Algorithm theoretical basis document for the global sea-ice edge and type product. OSI-403-C & EUMETSAT, 250: 1–34

Aagaard K, Carmack E C. 1994. The arctic ocean and climate: a perspective. In: Johannessen O M, Muench R D, Overland J E, eds. The Polar Oceans and Their Role in Shaping the Global Environment. Washington: American Geophysical Union, 5–20

Batoula S. 2011. ENVISAT ALTIMETRY Level 2 user manual V 1.4. Paris: European Space Agency

Bernard R, Le Cornec A, Eymard L, et al. 1993. The microwave radiometer aboard ERS-1.1. Characteristics and performances. IEEE Transactions on Geoscience and Remote Sensing, 31(6): 1186–1198. doi: 10.1109/36.317444

Bronner E, Guillot A, Picot N. 2013. SARAL/AltiKa Products Handbook: SALP-MU-M-OP-15984-CN. Toulouse: Centre National d’Etudes Spatiales

Cavalieri D J, Crawford J P, Drinkwater M R, et al. 1991. Aircraft active and passive microwave validation of sea ice concentration from the defense meteorological satellite program special sensor microwave imager. Journal of Geophysical Research: Oceans, 96(C12): 21989–22008. doi: 10.1029/91JC02335

Comiso J C. 1995. SSM/I sea ice concentrations using the bootstrap algorithm. Washington: National Aeronautics and Space Administration, 4–7

Eppler D T, Farmer L D, Lohanick A W, et al. 1992. Passive microwave signatures of sea ice. In: Carsey F D, ed. Microwave Remote Sensing of Sea Ice. Washington, DC: American Geophysical Union, 47–71

Fleming H E, Grody N C, Kratz E J. 1991. The forward problem and corrections for the SSM/T satellite microwave temperature sounder. IEEE Transactions on Geoscience and Remote Sensing, 29(4): 571–583. doi: 10.1109/36.135819

Forgy E W. 1965. Cluster analysis of multivariate data: efficiency versus interpretability of classifications. Biometrics, 21: 768–769

Fu L L, Christensen E J, Yamarone C A Jr, et al. 1994. TOPEX/POSEIDON mission overview. Oceanographic Literature Review, 99(C12): 24369–24381

Gill J P S, Yackel J J. 2012. Evaluation of C-band SAR polarimetric parameters for discrimination of first-year sea ice types. Canadian Journal of Remote Sensing, 38(3): 306–323. doi: 10.5589/m12-025

Gloersen P. 1992. Arctic and Antarctic Sea Ice, 1978–1987: Satellite Passive-Microwave Observations and Analysis. Washington: Scientific and Technical Information Program, National Aeronautics and Space Administration, 306

Jiang Xingwei, Lin Mingsen, Liu Jianqiang, et al. 2012. The HY-2 satellite and its preliminary assessment. International Journal of Digital Earth, 5(3): 266–281. doi: 10.1080/17538947.2012.658685

Jiang Chengfei, Lin Mingsen, Wei Hao. 2019. A study of the technology used to distinguish sea ice and seawater on the Haiyang-2A/B (HY-2A/B) altimeter data. Remote Sensing, 11(12): 1490. doi: 10.3390/rs11121490

Jiang Maofei, Xu Ke, Jia Yongjun, et al. 2015. Evaluation of HY-2B altimeter products over ocean. In: 2020 IEEE International Geoscience and Remote Sensing Symposium. Waikoloa, HI: IEEE, 5858–5861

Keihm S J, Janssen M A, Ruf C S. 1995. TOPEX/Poseidon microwave radiometer (TMR). III. Wet troposphere range correction algorithm and pre-launch error budget. IEEE Transactions on Geoscience and Remote Sensing, 33(1): 147–161. doi: 10.1109/36.368213

Kouraev A V, Crétaux J F, Lebedev S A, et al. 2011. Satellite altimetry applications in the Caspian Sea. In: Vignudelli S, Kostianoy A, Cipollini P, et al., eds. Coastal Altimetry. Berlin: Springer, 331–366

Kouraev A V, Papa F, Mognard N M, et al. 2004a. Sea ice cover in the Caspian and Aral Seas from historical and satellite data. Journal of Marine Systems, 47(1–4): 89–100

Kouraev A V, Papa F, Mognard N M, et al. 2004b. Synergy of active and passive satellite microwave data for the study of first-year sea ice in the Caspian and Aral seas. IEEE Transactions on Geoscience and Remote Sensing, 42(10): 2170–2176. doi: 10.1109/TGRS.2004.835307

Kouraev A V, Shimaraev M N, Buharizin P I, et al. 2008. Ice and snow cover of continental water bodies from simultaneous radar altimetry and radiometry observations. Surveys in Geophysics, 29(4): 271–295

Kouraev A V, Semovski S V, Shimaraev M N, et al. 2007. Observations of Lake Baikal ice from satellite altimetry and radiometry. Remote Sensing of Environment, 108(3): 240–253. doi: 10.1016/j.rse.2006.11.010

Laxon S. 1994. Sea ice altimeter processing scheme at the EODC. International Journal of Remote Sensing, 15(4): 915–924. doi: 10.1080/01431169408954124

Lomax A S, Lubin D, Whritner R H. 1995. The potential for interpreting total and multiyear ice concentrations in SSM/I 85.5 GHz imagery. Remote Sensing of Environment, 54(1): 13–26. doi: 10.1016/0034-4257(95)00082-C

Louet J, Bruzzi S. 1999. ENVISAT mission and system. In: IEEE 1999 International Geoscience and Remote Sensing Symposium. Hamburg: IEEE, 1680–1682

Markus T, Cavalieri D J. 2000. An enhancement of the NASA Team sea ice algorithm. IEEE Transactions on Geoscience and Remote Sensing, 38(3): 1387–1398. doi: 10.1109/36.843033

Obligis E, Eymard L, Tran N, et al. 2006. First three years of the microwave radiometer aboard Envisat: in-flight calibration, processing, and validation of the geophysical products. Journal of Atmospheric and Oceanic Technology, 23(6): 802–814. doi: 10.1175/JTECH1878.1

Ochilov S, Clausi D A. 2012. Operational SAR sea-ice image classification. IEEE Transactions on Geoscience and Remote Sensing, 50(11): 4397–4408. doi: 10.1109/TGRS.2012.2192278

Pol S L C, Ruf C S, Keihm S J. 1998. Improved 20- to 32-GHz atmospheric absorption model. Radio Science, 33(5): 1319–1333. doi: 10.1029/98RS01941

Przybylak R. 2007. Recent air-temperature changes in the Arctic. Annals of Glaciology, 46: 316–324. doi: 10.3189/172756407782871666

Remund Q P, Long D G. 1999. Sea ice extent mapping using Ku band scatterometer data. Journal of Geophysical Research: Oceans, 104(C5): 11515–11527. doi: 10.1029/98JC02373

Remund Q P, Long D G, Drinkwater M R. 2000. An iterative approach to multisensor sea ice classification. IEEE Transactions on Geoscience and Remote Sensing, 38(4): 1843–1856. doi: 10.1109/36.851768

Scheuchl B, Caves R, Cumming I, et al. 2001. Automated sea ice classification using spaceborne polarimetric SAR data. In: IEEE 2001 International Geoscience and Remote Sensing Symposium. Sydney: IEEE, 3117–3119

Screen J A, Simmonds I. 2010. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature, 464(7293): 1334–1337. doi: 10.1038/nature09051

Shokr M, Sinha N K. 2015. Sea Ice: Physics and Remote Sensing. Washington, DC: American Geophysical Union, 615

Swan A M, Long D G. 2012. Multiyear Arctic sea ice classification using QuikSCAT. IEEE Transactions on Geoscience and Remote Sensing, 50(9): 3317–3326. doi: 10.1109/TGRS.2012.2184123

Tandon N F, Kushner P J, Docquier D, et al. 2018. Reassessing sea ice drift and its relationship to long-term Arctic sea ice loss in coupled climate models. Journal of Geophysical Research: Oceans, 123(6): 4338–4359. doi: 10.1029/2017JC013697

Woodhouse I H. 2017. Introduction to Microwave Remote Sensing. Boca Raton: CRC Press, 400

Xu Ke, Jiang Jingshan, Liu Heguang. 2007. A new tracker for ocean-land compatible radar altimeter. In: 2007 IEEE International Geoscience and Remote Sensing Symposium. Barcelona: IEEE, 3825–3828

Xu Ke, Jiang Jingshan, Liu Heguang. 2013. HY-2A radar altimeter design and in flight preliminary results. In: 2013 IEEE International Geoscience and Remote Sensing Symposium. Melbourne: IEEE, 1680–1683

Xu Ke, Liu Heguang, Liu Peng, et al. 2014. System techniques and capabilities of the HY-2A altimeter. In: 2014 IEEE Geoscience and Remote Sensing Symposium. Quebec City, QC: IEEE, 5171–5174

Xu Ke, Liu Peng, Tang Yueying, et al. 2017. The improved design for HY-2B radar altimeter. In: 2017 IEEE International Geoscience and Remote Sensing Symposium. Fort Worth, TX: IEEE, 534–537

Zhang Dehai, Wang Zhenzhan, Li Yun, et al. 2015. Preliminary analysis of HY-2 ACMR data. In: 2015 IEEE International Geoscience and Remote Sensing Symposium. Milan: IEEE, 177–180

Zhang Zhilun, Yu Yining, Li Xinqing, et al. 2019. Arctic sea ice classification using microwave scatterometer and radiometer data during 2002–2017. IEEE Transactions on Geoscience and Remote Sensing, 57(8): 5319–5328. doi: 10.1109/TGRS.2019.2898872

Zygmuntowska M, Khvorostovsky K, Helm V, et al. 2013. Waveform classification of airborne synthetic aperture radar altimeter over Arctic sea ice. The Cryosphere, 7(4): 1315–1324. doi: 10.5194/tc-7-1315-2013

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