Précédent|Prochain

Advances in lake ice monitoring methods based on remote sensing technology

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

    School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China

  • Email：tongjie@hhu.edu.cn
  • Introduction：童洁，研究方向为湖冰遥感。E-mail： tongjie@hhu.edu.cn
TONG Jie12,  
  • Affiliation：

    School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China

GAO Yongnian2,  
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

    University of Chinese Academy of Sciences, Beijing 100049, China

ZHAN Pengfei13,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

  • Email：cqsong@niglas.ac.cn
  • Introduction：宋春桥，研究方向为湖泊—流域水文遥感、资源环境遥感与全球变化。E-mail： cqsong@niglas.ac.cn
SONG Chunqiao1*

résumé

Lake ice is not only an important part of the cryosphere but also one of the most direct indicators of global climate change. In the context of climate warming and intensified human activities, global lake ice presents a trend of delayed freeze onset date, advanced break onset date, shortened ice cover duration, and thinning ice thickness. This trend tends to last for a long time. Consequently, a series of chain reactions of lake physical hydrology, hydrochemistry, and ecosystem will inevitably be triggered, further heaving the burden of natural environment and habitat construction. Therefore, it is necessary to perform fine-scale monitoring and scientific analysis of spatiotemporal patterns on lake ice variations for further predicting the early warning of global climate change. Toward overcoming the limitation of in-situ surveys, remote sensing technique comes to play a significant role in lake ice monitoring, which can provide large-scale, long time series, and high temporal resolution data for lake ice research. Previous efforts always focus on lake ice and its response to climate change using different remote sensing sensors, parameters, and characteristics. Through reviewing pioneering research, this study presents a general review on the remote sensing data source and methods for lake ice studies as well as spatial and temporal variations of lake ice in global hotspots. This paper first reviews the development of the commonly used remote sensing data sources for lake ice monitoring, which include spaceborne and airborne remote sensing platforms and existing lake ice data products. Then, the methods of lake ice identification and retrieval of lake ice phenology and ice thickness parameters are compared and discussed. Threshold and index-based methods are commonly used in lake ice research. According to the previous studies, this review likewise summaries the research hotspots of lake ice and analyzes the spatial and temporal characteristics of lake ice variations. The research hotspots are mostly distributed in the Northern hemisphere, especially in Northern Europe, North America, and the Tibetan Plateau. In addition, influencing factors of lake ice variations, including climate factors and lake shape attributes, are discussed in this study. Finally, future development directions of lake ice study by remote sensing are discussed as follows: (1) to fully integrate multiple satellite data at medium and high spatial resolution to improve the accuracy of lake ice observations, particularly for small- and medium-sized lakes; (2) to reconstruct the long time series of lake ice phenology and thickness information and predict their future changes based on techniques such as big earth data and machine learning methods; and (3) to focus more on the research of past, present, and future of lake ice variation characteristics in the Tibetan Plateau, which is rather sensitive to climate change and remains largely unexplained. Remote sensing is an effective tool to monitor the variations of lake ice, yet what we should do imperatively is to advance the scientific understanding on climate change impacts and take immediate actions.

mots-clés

lake ice;Lake ice phenology;ice thickness;remote sensing monitoring;climate change

References

  1. 1.
    Arcone S A and Delaney A J. 1987. Airborne river-ice thickness profiling with helicopter-borne UHF short-pulse radar. Journal of Glaciology, 33(115): 330-340
  2. 2.
    Beckers J F, Casey J A and Haas C. 2017. Retrievals of lake ice thickness from Great Slave Lake and Great Bear Lake using CryoSat-2. IEEE Transactions on Geoscience and Remote Sensing, 55(7): 3708-3720
  3. 3.
    Brown L C and Duguay C R. 2010. The response and role of ice cover in lake-climate interactions. Progress in Physical Geography: Earth and Environment, 34(5): 671-704
  4. 4.
    Brown L C and Duguay C R. 2011a. A comparison of simulated and measured lake ice thickness using a Shallow Water Ice Profiler. Hydrological Processes, 25(19): 2932-2941
  5. 5.
    Brown L C and Duguay C R. 2011b. The fate of lake ice in the North American Arctic. The Cryosphere, 5(4): 869-892
  6. 6.
    Brown L C and Duguay C R. 2012. Modelling lake ice phenology with an examination of satellite-detected subgrid cell variability. Advances in Meteorology, 2012: 529064
  7. 7.
    Cai Y, Ke C Q and Duan Z. 2017. Monitoring ice variations in Qinghai Lake from 1979 to 2016 using passive microwave remote sensing data. Science of the Total Environment, 607-608: 120-131
  8. 8.
    Cai Y, Ke C Q, Li X G, Zhang G Q, Duan Z and Lee H. 2019. Variations of lake ice phenology on the Tibetan Plateau from 2001 to 2017 based on MODIS data. Journal of Geophysical Research: Atmospheres, 124(2): 825-843
  9. 9.
    Caldwell T J, Chandra S, Albright T P, Harpold A A, Dilts T E, Greenberg J A, Sadro S and Dettinger M D. 2021. Drivers and projections of ice phenology in mountain lakes in the western United States. Limnology and Oceanography, 66(3): 995-1008
  10. 10.
    Cao M S. 2006. Remote Sensing of Cryosphere. Beijing: Science Press
  11. 11.
    Cao X W. 2021. Observation and Simulation Research on Growth and Decay Processes of Ice Cover on Lake Wuliangsuhai. Dalian: Dalian University of Technology
  12. 12.
    Cavalieri D J, Crawford J P, Drinkwater M R, Eppler D T, Farmer L D, Jentz R R and Wackerman C C. 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
  13. 13.
    Chen X Z, Wang G Y, Li W J, Zeng Q Z, Jin D H and Wang L H. 1995. Lake ice and its remote sensing monitoring in the Tibetan Plateau. Journal of Glaciology and Geocryology, 17(3): 241-246
  14. 14.
    Choiński A, Ptak M, Skowron R and Strzelczak A. 2015. Changes in ice phenology on polish lakes from 1961 to 2010 related to location and morphometry. Limnologica, 53: 42-49
  15. 15.
    Crétaux J F, Merchant C J, Duguay C, Simis S, Calmettes B, Bergé-Nguyen M, Wu Y, Zhang D, Carrea L, Liu X, Selmes N and Warren M. 2020. ESA Lakes Climate Change Initiative (Lakes_cci): lake products, Version 1.0. Centre for Environmental Data Analysis
  16. 16.
    Dauginis A A and Brown L C. 2021. Recent changes in Pan-Arctic sea ice, lake ice, and snow-on/off timing. The Cryosphere, 15(10): 4781-4805
  17. 17.
    Dibike Y, Prowse T, Bonsal B, Rham L D and Saloranta T. 2012. Simulation of North American lake-ice cover characteristics under contemporary and future climate conditions. International Journal of Climatology, 32(5): 695-709
  18. 18.
    Dibike Y, Prowse T, Saloranta T and Ahmed R. 2011. Response of Northern Hemisphere lake-ice cover and lake-water thermal structure patterns to a changing climate. Hydrological Processes, 25(19): 2942-2953
  19. 19.
    Du J Y, Kimball J S, Duguay C, Kim Y and Watts J D. 2017. Satellite microwave assessment of northern hemisphere lake ice phenology from 2002 to 2015. The Cryosphere, 11(1): 47-63
  20. 20.
    Duguay C R, Bernier M, Gauthier Y and Kouraev A. 2015. Remote sensing of lake and river ice//Tedesco M, ed. Remote Sensing of the Cryosphere. New York: John Wiley and Sons: 273-306
  21. 21.
    Duguay C R, Flato G M, Jeffries M O, Ménard P, Morris K and Rouse W R. 2003. Ice-cover variability on shallow lakes at high latitudes: model simulations and observations. Hydrological Processes, 17(17): 3465-3483
  22. 22.
    Gafurov A and Bárdossy A. 2009. Cloud removal methodology from MODIS snow cover product. Hydrology and Earth System Sciences, 13(7): 1361-1373
  23. 23.
    Gatto L W. 1990. Monitoring river ice with landsat images. Remote Sensing of Environment, 32(1): 1-16
  24. 24.
    Geldsetzer T, van der Sanden J and Brisco B. 2010. Monitoring lake ice during spring melt using RADARSAT-2 SAR. Canadian Journal of Remote Sensing, 36(S2): S391-S400
  25. 25.
    Ghanbari R N, Bravo H R, Magnuson J J, Hyzer W G and Benson B J. 2009. Coherence between lake ice cover, local climate and teleconnections (Lake Mendota, Wisconsin). Journal of Hydrology, 374(3/4): 282-293
  26. 26.
    Gherboudj I, Bernier M and Leconte R. 2010. A backscatter modeling for river ice: analysis and numerical results. IEEE Transactions on Geoscience and Remote Sensing, 48(4): 1788-1798
  27. 27.
    Gou P, Ye Q H, Che T, Feng Q, Ding B H, Lin C G and Zong J B. 2017. Lake ice phenology of Nam Co, Central Tibetan Plateau, China, derived from multiple MODIS data products. Journal of Great Lakes Research, 43(6): 989-998
  28. 28.
    Gou P, Ye Q H and Wei Q F. 2015. Lake ice change at the Nam Co Lake on the Tibetan Plateau during 2000-2013 and influencing factors. Progress in Geography, 34(10): 1241-1249
  29. 29.
    Guo L N, Zheng H X, Wu Y H, Zhang T Q, Wen M X, Fan L X and Zhang B. 2020. Responses of lake ice phenology to climate change at Tibetan Plateau. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 3856-3861
  30. 30.
    Hall D K, Fagre D B, Klasner F, Linebaugh G and Liston G E. 1994. Analysis of ERS 1 synthetic aperture radar data of frozen lakes in northern Montana and implications for climate studies. Journal of Geophysical Research: Oceans, 99(C11): 22473-22482
  31. 31.
    Hall D K and Riggs G A. 2007. Accuracy assessment of the MODIS snow products. Hydrological Processes, 21(12): 1534-1547
  32. 32.
    Hall D K, Riggs G A and Salomonson V V. 1995. Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data. Remote Sensing of Environment, 54(2): 127-140
  33. 33.
    Han W X, Huang C L, Duan H T, Gu J and Hou J L. 2020. Lake Phenology of freeze-thaw cycles using random forest: a case study of Qinghai Lake. Remote Sensing, 12(24): 4098
  34. 34.
    Hodgkins G A. 2013. The importance of record length in estimating the magnitude of climatic changes: an example using 175 years of lake ice-out dates in New England. Climatic Change, 119(3): 705-718
  35. 35.
    Howell S E L, Brown L C, Kang K K and Duguay C R. 2009. Variability in ice phenology on Great Bear Lake and Great Slave Lake, Northwest Territories, Canada, from SeaWinds/QuikSCAT: 2000–2006. Remote Sensing of Environment, 113(4): 816-834
  36. 36.
    Huang X D, Li X B, Liu C Y, Zhou M Q and Wang J S. 2019. Remote sensing inversion of snow cover extent and snow depth/snow water equivalent on the Qinghai-Tibet Plateau: advance and challenge. Journal of Glaciology and Geocryology, 41(5): 1138-1149
  37. 37.
    Hvidegaard S M and Forsberg R. 2002. Sea-ice thickness from airborne laser altimetry over the Arctic Ocean north of Greenland. Geophysical Research Letters, 29(20): 1952
  38. 38.
    Jia W, Wang J A, Shi P J and Ma W D. 2021. The progress and prospect of remote sensing monitoring of rocky desert dynamic changes in the ice and snow melting area of the Qinghai-Tibet Plateau. Journal of Geo-Information Science, 23(10): 1715-1727
  39. 39.
    Jin H A. 2021. Ice Thickness Monitoring of Gahai Lake based on Airborne Radar and Sentinel-1 SAR. Lanzhou: Northwest Normal University.
  40. 40.
    Johannessen O M, Campbell W J, Shuchman R, Sandven S, Gloersen P, Johannessen J A, Josberger E G and Haugan P M. 1992. Microwave study programs of air-ice-ocean interactive processes in the seasonal ice zone of the Greenland and Barents seas//Carsey F D, ed. Microwave Remote Sensing of Sea Ice, Volume 68. Washington: American Geophysical Union: 261-289
  41. 41.
    Johnson S L and Stefan H G. 2006. Indicators of climate warming in Minnesota: lake ICE covers and snowmelt runoff. Climatic Change, 75(4): 421-453
  42. 42.
    Kang K K, Duguay C R, Lemmetyinen J and Gel Y. 2014. Estimation of ice thickness on large northern lakes from AMSR-E brightness temperature measurements. Remote Sensing of Environment, 150: 1-19
  43. 43.
    Ke C Q, Tao A Q and Jin X. 2013. Variability in the ice phenology of Nam Co Lake in central Tibet from scanning multichannel microwave radiometer and special sensor microwave/imager: 1978 to 2013. Journal of Applied Remote Sensing, 7(1): 073477
  44. 44.
    Korhonen J. 2006. Long-term changes in lake ice cover in Finland. Hydrology Research, 37(4/5): 347-363
  45. 45.
    Kouraev A V, Kostianoy A G and Lebedev S A. 2009. Ice cover and sea level of the Aral Sea from satellite altimetry and radiometry (1992-2006). Journal of Marine Systems, 76(3): 272-286
  46. 46.
    Kouraev A V, Semovski S V, Shimaraev M N, Mognard N M, Legrésy B and Rémy F. 2007a. The ice regime of Lake Baikal from historical and satellite data: relationship to air temperature, dynamical, and other factors. Limnology and Oceanography, 52(3): 1268-1286
  47. 47.
    Kouraev A V, Semovski S V, Shimaraev M N, Mognard N M, Légresy B and Remy F. 2007b. Observations of Lake Baikal ice from satellite altimetry and radiometry. Remote Sensing of Environment, 108(3): 240-253
  48. 48.
    Kropáček J, Maussion F, Chen F, Hoerz S and Hochschild V. 2013. Analysis of ice phenology of lakes on the Tibetan Plateau from MODIS data. The Cryosphere, 7(1): 287-301
  49. 49.
    Kuusisto E. 1994. The thickness and volume of lake ice in Finland. National Board of Waters and the Environment
  50. 50.
    Kwok R and Cunningham G F. 2008. ICESat over Arctic sea ice: estimation of snow depth and ice thickness. Journal of Geophysical Research: Oceans, 113(C8): C08010
  51. 51.
    Kwok R, Zwally H J and Yi D H. 2004. ICESat observations of Arctic sea ice: a first look. Geophysical Research Letters, 31(16): L16401
  52. 52.
    Lang J H, Ma Y M, Li Z G and Su D S. 2021. The impact of climate warming on lake surface heat exchange and ice phenology of different types of lakes on the Tibetan Plateau. Water, 13(5): 634
  53. 53.
    Latifovic R and Pouliot D. 2007. Analysis of climate change impacts on lake ice phenology in Canada using the historical satellite data record. Remote Sensing of Environment, 106(4): 492-507
  54. 54.
    Leconte R, Daly S, Gauthier Y, Yankielun N, Bérubé F and Bernier M. 2009. A controlled experiment to retrieve freshwater ice characteristics from an FM-CW radar system. Cold Regions Science and Technology, 55(2): 212-220
  55. 55.
    Lei R B, Li Z J, Zhang Z H and Cheng Y F. 2011. Comparisons of thermodynamic processes between lake ice and landfast sea ice around Zhongshan Station, East Antarctica. Chinese Journal of Polar Research, 23(4): 289-298
  56. 56.
    Lemmetyinen J, Derksen C, Pulliainen J, Strapp W, Toose P, Walker A, Tauriainen S, Pihlflyckt J, Karna J P and Hallikainen M T. 2009. A comparison of airborne microwave brightness temperatures and snowpack properties across the boreal forests of Finland and western Canada. IEEE Transactions on Geoscience and Remote Sensing, 47(3): 965-978
  57. 57.
    Lemmetyinen J, Kontu A, Kärnä J P, Vehviläinen J, Takala M and Pulliainen J. 2011. Correcting for the influence of frozen lakes in satellite microwave radiometer observations through application of a microwave emission model. Remote Sensing of Environment, 115(12): 3695-3706
  58. 58.
    Leppäranta M. 2014. Interpretation of statistics of lake ice time series for climate variability. Hydrology Research, 45(4/5): 673-683
  59. 59.
    Li X D, Long D, Huang Q and Zhao F Y. 2022. The state and fate of lake ice thickness in the Northern Hemisphere. Science Bulletin, 67(5): 537-546
  60. 60.
    Li Z J, Han M, Qin J M, Xi Y Z and Lu P. 2005. States and advances in monitor of ice thickness change. Advances in Water Science, 16(5): 753-757
  61. 61.
    Lillesand T M, Kiefer R W and Chipman J W. 2015. Remote Sensing and Image Interpretation. 7th ed. Hoboken: John Wiley and Sons
  62. 62.
    Liu H, Ji H L, Mou X Y, Gao G M and Zhang B S. 2020. Experimental study on Yellow River ice thickness monitoring test based on UAV Radar technology. South-to-North Water Transfers and Water Science Technology, 18(3): 217-224
  63. 63.
    Liu Y, Chen H P, Wang H J and Qiu Y B. 2018. The impact of the NAO on the Delayed Break-up date of Lake Ice over the Southern Tibetan Plateau. Journal of Climate, 31(22): 9073-9086
  64. 64.
    Liu Y, Chen H P, Wang H J, Sun J Q, Li H and Qiu Y B. 2019. Modulation of the Kara sea ice variation on the ice freeze-up time in Lake Qinghai. Journal of Climate, 32(9): 2553-2568
  65. 65.
    Liu Y and Wu H D. 2018. Sea ice thermodynamics. Marine Forecasts, 35(3): 88-97
  66. 66.
    Liu Z P, Fu H, Guo X L, Wang T and Cui H T. 2017. Double frequency radar system for ice thickness and water depth measurement. Journal of Hydraulic Engineering, 48(11): 1341-1347
  67. 67.
    Lü Z M. 2021. Effects of Lake Processes on Regional and Global Climate Forecasts. Yangling: Northwest A&F University
  68. 68.
    Ma Z G, Liu Z H, Pu J B, Xu L L, Li K, Wangqu L L, Wu R, Ma Y Y, Chen Y and Duguay C. 2021. Deep convolutional neural network with random field model for lake ice mapping from Sentinel-1 imagery. International Journal of Remote Sensing, 42(24): 9351-9375
  69. 69.
    Magnuson J J, Robertson D M, Benson B J, Wynne R H, Livingstone D M, Arai T, Assel R A, Barry R G, Card V, Kuusisto E, Granin N G, Prowse T D, Stewart K M and Vuglinski V S. 2000. Historical trends in lake and river ice cover in the Northern Hemisphere. Science, 289(5485): 1743-1746
  70. 70.
    Marko J R and Jasek M. 2010. Sonar detection and measurement of ice in a freezing river II: observations and results on frazil ice. Cold Regions Science and Technology, 63(3): 135-153
  71. 71.
    Morris K, Jeffries M O and Weeks W F. 1995. Ice processes and growth history on Arctic and sub-Arctic lakes using ERS-1 SAR data. Polar Record, 31(177): 115-128
  72. 72.
    Murfitt J and Brown L C. 2017. Lake ice and temperature trends for Ontario and Manitoba: 2001 to 2014. Hydrological Processes, 31(21): 3596-3609
  73. 73.
    Murfitt J and Duguay C R. 2021. 50 years of lake ice research from active microwave remote sensing: progress and prospects. Remote Sensing of Environment, 264: 112616
  74. 74.
    Nakamura K, Wakabayashi H, Uto S, Ushio S and Nishio F. 2009. Observation of sea-ice thickness using ENVISAT data from Lützow-Holm Bay, East Antarctica. IEEE Geoscience and Remote Sensing Letters, 6(2): 277-281
  75. 75.
    Nõges P and Nõges T. 2014. Weak trends in ice phenology of Estonian large lakes despite significant warming trends. Hydrobiologia, 731(1): 5-18
  76. 76.
    Nonaka T, Matsunaga T and Hoyano A. 2007. Estimating ice breakup dates on Eurasian lakes using water temperature trends and threshold surface temperatures derived from MODIS data. International Journal of Remote Sensing, 28(10): 2163-2179
  77. 77.
    Pang Y W, Huang Y X, Gong Z, Wen J Y and Xu J F. 2020. Advances in phenological monitoring of lake ice based on multi-spectral remote sensing. Transactions of Oceanology and Limnology, (2): 90-99
  78. 78.
    Pociask-Karteczka J and Choiński A. 2012. Recent trends in ice cover duration for Lake Morskie Oko (Tatra Mountains, East-Central Europe). Hydrology Research, 43(4): 500-506
  79. 79.
    Qi M M, Liu S Y, Yao X J, Xie F M and Gao Y P. 2020. Monitoring the ice phenology of Qinghai Lake from 1980 to 2018 using multisource remote sensing data and Google earth engine. Remote Sensing, 12(14): 2217
  80. 80.
    Qi M M, Yao X J, Li X F and Gao Y P. 2018. A dataset of lake ice phenology in Qinghai Lake from 2000 to 2018. China Scientific Data, 3(4): 17-27
  81. 81.
    Qu B, Kang S C, Chen F, Zhang Y J and Zhang G S. 2012. Lake ice and its effect factors in the Nam Co Basin, Tibetan Plateau. Progressus Inquisitiones de Mutatione Climatis, 8(5): 327-333
  82. 82.
    Ramsay B H. 1998. The interactive multisensor snow and ice mapping system. Hydrological Processes, 12(10/11): 1537-1546 [DOI: (199808/09)12:10/11<1537::AID-HYP679>3.0.CO;2-A]
  83. 83.
    Ruan Y J. 2017. Passive Microwave Remote Sensing of Lake ice Freeze-Thaw Monitoring over High Asia. Ganzhou: Jiangxi University of Science and Technology (阮永俭. 2017. 被动微波高亚洲湖冰冻融监测研究. 赣州: 江西理工大学) [DOI: 10.7666/d.D01237698]
  84. 84.
    Sharma S, Richardson D C, Woolway R I, Imrit M A, Bouffard D, Blagrave K, Daly J, Filazzola A, Granin N, Korhonen J, Magnuson J, Marszelewski W, Matsuzaki S I S, Perry W, Robertson D M, Rudstam L G, Weyhenmeyer G A and Yao H X. 2021. Loss of ice cover, shifting phenology, and more extreme events in northern hemisphere lakes. Journal of Geophysical Research: Biogeosciences, 126(10): e2021JG006348
  85. 85.
    Su L, Che T and Dai L Y. 2021. Variation in ice phenology of large lakes over the Northern Hemisphere based on passive microwave remote sensing data. Remote Sensing, 13(7): 1389
  86. 86.
    Sun H, Li C H and Yao X J. 2021. Extraction and analysis of lake ice in typical lakes on the northern slopes of the Himalayas based on NPP-VIIRS data. Journal of Glaciology and Geocryology, 43(1): 70-79
  87. 87.
    Surdu C M, Duguay C R, Brown L C and Prieto D F. 2014. Response of ice cover on shallow lakes of the North Slope of Alaska to contemporary climate conditions (1950–2011): radar remote-sensing and numerical modeling data analysis. The Cryosphere, 8(1): 167-180
  88. 88.
    Surdu C M, Duguay C R and Prieto D F. 2016. Evidence of recent changes in the ice regime of lakes in the Canadian High Arctic from spaceborne satellite observations. The Cryosphere, 10(3): 941-960
  89. 89.
    Tai X N, Wang N L, Wu Y W and Zhang Y J. 2022. Lake ice phenology variations and influencing factors of Selin Co from 2000 to 2020. Journal of Lake Sciences, 34(1): 334-348
  90. 90.
    Tedesco M, Derksen C, Deems J S and Foster J L. 2014. Remote sensing of snow depth and snow water equivalent//Tedesco M, ed. Remote Sensing of the Cryosphere. New York: John Wiley and Sons: 73-98
  91. 91.
    Tekeli A E, Sönmez I and Erdi E. 2016. Snow-covered area determination based on satellite-derived probabilistic snow cover maps. Arabian Journal of Geosciences, 9(3): 198
  92. 92.
    Tom M, Aguilar R, Imhof P, Leinss S, Baltsavias E and Schindler K. 2020. Lake ice detection from sentinel-1 SAR with deep learning. arXiv preprint arXiv: 2002.07040
  93. 93.
    Verpoorter C, Kutser T, Seekell D A and Tranvik L J. 2014. A global inventory of lakes based on high-resolution satellite imagery. Geophysical Research Letters, 41(18): 6396-6402
  94. 94.
    Wakabayashi H, Weeks W F and Jeffries M O. 1993. A C-band backscatter model for lake ice in ALASKA//IEEE International Geoscience and Remote Sensing Symposium. Tokyo: IEEE: 1264-1266
  95. 95.
    Walker A E and Davey M R. 1993. Observation of Great Slave Lake ice freeze-up and break-up processes using passive microwave satellite data//Proceedings of the 16th Canadian Symposium on Remote Sensing, Sherbrooke, Quebec, Canada. 233-238
  96. 96.
    Wang G X, Zhang T J, Yang R M, Zhong X Y and Li X D. 2020. Lake ice changes in the Third Pole and the Arctic. Journal of Glaciology and Geocryology, 42(1): 124-139
  97. 97.
    Wang Q, Wang J B, Guo J Y and Liang J. 2019. Lake ice extraction of Selin Co and its space-time distribution based on support vector machine. Manned Spaceflight, 25(6): 789-798
  98. 98.
    Wang X C, Feng L, Gibson L, Qi W, Liu J G, Zheng Y, Tang J, Zeng Z Z and Zheng C M. 2021. High-resolution mapping of ice cover changes in over 33, 000 lakes across the North Temperate Zone. Geophysical Research Letters, 48(18): e2021GL095614
  99. 99.
    Wang X J, Key J R and Liu Y H. 2010. A thermodynamic model for estimating sea and lake ice thickness with optical satellite data. Journal of Geophysical Research: Oceans, 115(C12): C12035
  100. 100.
    Wang Z Y, Wu Y H, Chang J, Zhang X and Pei D L. 2017. Temporal and spatial variation of lake ice phenology and its influencing factors in the Tibetan Plateau. Journal of Beijing University of Technology, 43(5): 701-709
  101. 101.
    Warne C P K, McCann K S, Rooney N, Cazelles K and Guzzo M M. 2020. Geography and morphology affect the ice duration dynamics of Northern Hemisphere lakes worldwide. Geophysical Research Letters, 47(12): e2020GL087953
  102. 102.
    Watts A C, Ambrosia V G and Hinkley E A. 2012. Unmanned aircraft systems in remote sensing and scientific research: classification and considerations of use. Remote Sensing, 4(6): 1671-1692
  103. 103.
    Weber H, Riffler M, Nõges T and Wunderle S. 2016. Lake ice phenology from AVHRR data for European lakes: an automated two-step extraction method. Remote Sensing of Environment, 174: 329-340
  104. 104.
    Weeks W F, Gow A J and Schertler R J. 1981. Ground-Truth Observations of Ice-Covered North Slope Lakes Imaged by Radar. Cold Regions Research and Engineering Laboratory, CRREL Report 81-19
  105. 105.
    Wei Q F. 2010. Methods of lake ice monitoring by remote sensing at Nam Co. Beijing: University of Chinese Academy of Sciences
  106. 106.
    Wei Q F and Ye Q H. 2010. Review of lake ice monitoring by remote sensing. Progress in Geography, 29(7): 803-810
  107. 107.
    Weyhenmeyer G A, Meili M and Livingstone D M. 2005. Systematic differences in the trend towards earlier ice-out on Swedish lakes along a latitudinal temperature gradient. SIL Proceedings, 1922-2010, 29(1): 257-260
  108. 108.
    Wu Q H, Li C Y, Sun B, Shi X H, Zhao S N and Han Z M. 2019. Change of ice phenology in the Hulun Lake from 1986 to 2017. Progress in Geography, 38(12): 1933—1943
  109. 109.
    Wu Y H, Duguay C R and Xu L L. 2021. Assessment of machine learning classifiers for global lake ice cover mapping from MODIS TOA reflectance data. Remote Sensing of Environment, 253: 112206
  110. 110.
    Wu Y H, Guo L N, Fan L X, Wen M X, Chi H J and Zhang B. 2022. Lake ice phenology of the Nam Co at Tibetan Plateau: remote sensing and modelling. National Remote Sensing Bulletin, 26(1): 193-200
  111. 111.
    Yang X, Pavelsky T M, Bendezu L P and Zhang S. 2022. Simple method to extract lake ice condition from Landsat images. IEEE Transactions on Geoscience and Remote Sensing, 60: 4202010
  112. 112.
    Yao X J, Li L, Zhao J, Sun M P, Li J, Gong P and Li A N. 2015. Spatial-temporal variations of lake ice in the Hoh Xil region from 2000 to 2011. Acta Geographica Sinica, 70(7): 1114-1124
  113. 113.
    Yin Q J and Yang Y L. 2005. Remote sensing monitoring of Lake Qinghai based on EOS/MODIS data. Journal of Lake Sciences, 17(4): 356-360
  114. 114.
    Zeng T, Shi L J, Marko M, Cheng B, Zou J H and Zhang Z P. 2016. Sea ice thickness analyses for the Bohai Sea using MODIS thermal infrared imagery. Acta Oceanologica Sinica, 35(7): 96-104
  115. 115.
    Zhao Y S. 2003. Principles and Methods of Remote Sensing Applications. Beijing: Science Press
  116. 116.
    Zhou M Q, Wang Y L, Liang H, Zeng T Y, Huang W J, Wang J S and Huang X D. 2019. Comparative analysis of the snow coverage products of Soumi-NPP and MODIS in the Qinghai-Tibet Plateau. Journal of Glaciology and Geocryology, 41(1): 36-44
  117. 117.
    Zhu Z and Woodcock C E. 2012. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment, 118: 83-94
  118. 118.
    Zhuang L C, Wang N A, Zhang X H, Zhao L Q and Su X B. 2021. Analysis on the difference of the spatial model of lake ice freezing and melting in the Badain Jaran Desert. Journal of Desert Research, 41(3): 214-223

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website