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High spatial and temporal resolution monitoring of water area changes of Dongting Lake by joint Sentinel satellite series of radar and optical images

  • role： First author第一作者
  • Affiliation：

    College of Surveying and Geotechnical Engineering, Henan Polytechnic University, Jiaozuo 454000, China

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

  • Email：lijuansong88888@163.com
  • Introduction：宋利娟，研究方向为水文遥感的理论和应用。E-mail： lijuansong88888@163.com
SONG Lijuan12,  
  • Affiliation：

    College of Surveying and Geotechnical Engineering, Henan Polytechnic University, Jiaozuo 454000, China

JING Haitao1,  
  • Affiliation：

    College of Surveying and Geotechnical Engineering, Henan Polytechnic University, Jiaozuo 454000, China

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

XU Jiahui12,  
  • Affiliation：

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

CHEN Tan2,  
  • Affiliation：

    College of Surveying and Geotechnical Engineering, Henan Polytechnic University, Jiaozuo 454000, China

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

ZHANG Dapeng12,  
  • 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 Chunqiao2*

resumen

Dongting Lake is the second largest freshwater lake in China, and the water body fluctuates greatly and frequently in dry and wet seasons. The high-frequency observation of water body changes in Dongting Lake by satellite is important for timely and accurate monitoring of its hydrological dynamic changes.This study aims to reconstruct and analyze the elaborate time series information of Dongting Lake water area from 2017 to 2020 by using Sentinel-1 and Sentinel-2 images (10 m) under the condition of high time-frequency and high spatial resolution. In addition, this study develops a method to reconstruct the whole lake water area and encrypt the time series of lake area based on the partially cloudless image of the lake area. This method uses the statistical fitting relationship between the block area and total area extracted from Sentinel-1 full image to establish an empirical model for obtaining a dense time series of Dongting Lake water area.Fitting results show that the area of each block is significantly positively correlated with the lake total area, and the average R2 value is 0.94. From 2017 to 2020, 119 Sentinel-1 images and 38 Sentinel-2 images were obtained to extract the block inundation range of Dongting Lake for reconstructing the whole lake area. After all Sentinel-1 and Sentinel-2 images were combined, the average observation images available in each month are 6. In some months, the monitoring times can reach 10 times, and the time interval is 3—6 days. It can conduct fine monitoring of the water area change of Dongting Lake. Besides, the time series of water area reconstructed in this study can accurately describe the significant seasonal fluctuations and interannual changes. The water area reaches the peak in July and the valley from November to February. The average ratio of maximum area to minimum area in a month is 1.36. The most violent fluctuation in surface waters occurred in November, with a ratio of 1.52. After Sentinel-1/2 image observation time series were integrated, the average water area of Dongting Lake from 2017 to 2020 is about 1147.13 km2.Compared with the water area time series of Dongting Lake constructed based on Sentinel-1/2 images, the water area time series combined with landsat-8 image can improve the time resolution of water observation. However, it has little effect on the monthly and annual averages of water area. This study combines sentinel series radar and optical images of high temporal and spatial resolution to develop a fine extraction method of high time-frequency water area series. In summary, this study can provide scientific and technological support for improving remote sensing monitoring and fine management of water resources in Dongting Lake and high dynamic lakes in the middle and lower reaches of the Yangtze River.

palabra clave

remote sensing monitoring;Dongting Lake;Sentinel;Watershed Area;time series;Yangtze River Basin

References

  1. 1.
    Barsi J A, Alhammoud B, Czapla-Myers J, Gascon F, Haque M O, Kaewmanee M, Leigh L and Markham B L. 2018. Sentinel-2A MSI and Landsat 8 OLI radiometric cross comparison over desert sites. European Journal of Remote Sensing, 51(1): 822-837
  2. 2.
    Cai X B, Feng L, Hou X J and Chen X L. 2016. Remote sensing of the water storage dynamics of large lakes and reservoirs in the Yangtze River Basin from 2000 to 2014. Scientific Reports, 6: 36405
  3. 3.
    Chen S N and Jiang M. 2021. Application research of Sentinel-1 SAR in flood range extraction and polarization analysis. Journal of Geo-information Science, 23(6): 1063-1070
  4. 4.
    Cheng G, Li D, Wang Y and Kang T T. 2015. Water area change of Dongting lake based on landsat data and its affecting factors analysis. Journal of Irrigation and Drainage, 34(S1): 246-249
  5. 5.
    Cui L, Li Y P, Huang G H and Zeng X T. 2015. Dynamic changes of Dongting Lake based on Landsat-TM remote sensing data. South-to-North Water Transfers and Water Science and Technology, 13(1): 63-66, 107
  6. 6.
    Donchyts G, Schellekens J, Winsemius H, Eisemann E and van de Giesen N. 2016. A 30 m resolution surface water mask including estimation of positional and thematic differences using landsat 8, SRTM and OpenStreetMap: a case study in the Murray-Darling Basin, Australia. Remote Sensing, 8(5): 386
  7. 7.
    Drusch M, Del Bello U, Carlier S, Colin O, Fernandez V, Gascon F, Hoersch B, Isola C, Laberinti P, Martimort P, Meygret A, Spoto F, Sy O, Marchese F and Bargellini P. 2012. Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sensing of Environment, 120: 25-36
  8. 8.
    Du T, Xiong L H, Yi F H, Xiao Y and Song Q M. 2012. Relation of the water area of Dongting Lake to the water levels of hydrological stations based on MODIS images. Resources and Environment in the Yangtze Basin, 21(6): 756-765
  9. 9.
    Gao Y, Xie Y H, Zou D S, Hou T J and Li Z Z. 2019. Changes and driving factors of water surface area for inner lakes in Lake Dongting district in the past 40 years. Journal of Lake Sciences, 31(3): 755-765
  10. 10.
    Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D and Moore R. 2017. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202: 18-27
  11. 11.
    Huang J M, Zou Y C, Cai H C, Tan H and Yu Y. 2013. Change characteristics of the air temperature during the past 60 a over Dongting Lake area. Journal of the Meteorological Sciences, 33 (04): 457-463
  12. 12.
    Li J and Roy D P. 2017. A global analysis of Sentinel-2A, Sentinel-2B and Landsat 8 data revisit intervals and implications for terrestrial monitoring. Remote Sensing, 9(9): 902
  13. 13.
    Li J, Zhang W and Xu X. 2020. Information extraction and analysis of food disaster in Dongting Lake area base on Sentinel-1. Anhui Agricultural Science Bulletin, 26(19): 151-153
  14. 14.
    Li J G, Li J R, Huang S F and Zang W B. 2010. The remote sensing monitoring analysis of Chinese Dongting Lake water area variations in last 10 years using Terra/MODIS data time series. Journal of China Institute of Water Resources and Hydropower Research, 8(3): 201-207
  15. 15.
    Li J G, Li J R, Huang S F and Zuo C G. 2009. Application of Terra/MODIS time series data in dynamic monitoring of lake water area variations: a case study in Dongting Lake region, China. Journal of Natural Resources, 24(5): 923-933
  16. 16.
    Li J J, Wang C, Xu L, Wu F, Zhang H and Zhang B. 2021. Multitemporal water extraction of Dongting Lake and Poyang Lake based on an automatic water extraction and dynamic monitoring framework. Remote Sensing, 13(5): 865
  17. 17.
    Li Y, Martinis S, Plank S and Ludwig R. 2018. An automatic change detection approach for rapid flood mapping in Sentinel-1 SAR data. International Journal of Applied Earth Observation and Geoinformation, 73: 123-135
  18. 18.
    Li Y, Niu Z G, Xu Z Y and Yan X. 2020. Construction of high spatial-temporal water body dataset in China based on Sentinel-1 archives and GEE. Remote Sensing, 12(15): 2413
  19. 19.
    Li Y L, Zhang Q, Lu J R, Yao J and Tan Z Q. 2019. Assessing surface water-groundwater interactions in a complex river-floodplain wetland-isolated lake system. River Research and Applications, 35(1): 25-36
  20. 20.
    Loveland T R and Irons J R. 2016. Landsat 8: the plans, the reality, and the legacy. Remote Sensing of Environment, 185: 1-6
  21. 21.
    Ma R H, Yang G S, Duan H T, Jiang J H, Wang S M, Feng X Z, Li A N, Kong F X, Xue B, Wu J L and Li S J. 2011. China's lakes at present: number, area and spatial distribution. Science China Earth Sciences, 54(2): 283-289
  22. 22.
    Manjusree P, Kumar L P, Bhatt C M, Rao G S and Bhanumurthy V. 2012. Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images. International Journal of Disaster Risk Science, 3(2): 113-122
  23. 23.
    Markert K N, Markert A M, Mayer T, Nauman C, Haag A, Poortinga A, Bhandari B, Thwal N S, Kunlamai T, Chishtie F, Kwant M, Phongsapan K, Clinton N, Towashiraporn P and Saah D. 2020. Comparing Sentinel-1 surface water mapping algorithms and radiometric terrain correction processing in Southeast Asia utilizing Google Earth Engine. Remote Sensing, 12(15): 2469
  24. 24.
    McFeeters S K. 1996. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7): 1425-1432
  25. 25.
    Pahlevan N, Balasubramanian S V, Sarkar S and Franz B A. 2018. Toward long-term aquatic science products from heritage landsat missions. Remote Sensing, 10(9): 1337
  26. 26.
    Pekel J F, Cottam A, Gorelick N and Belward A S. 2016. High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633): 418-422
  27. 27.
    Song C Q, Zhan P F and Ma R H. 2020. Progress in remote sensing study on lake hydrologic regime. Journal of Lake Sciences, 32(5): 1406-1420
  28. 28.
    Steinhausen M J, Wagner P D, Narasimhan B and Waske B. 2018. Combining Sentinel-1 and Sentinel-2 data for improved land use and land cover mapping of monsoon regions. International Journal of Applied Earth Observation and Geoinformation, 73: 595-604
  29. 29.
    Setiawan B D, Rusydi A N and Pradityo K. 2017. Lake edge detection using Canny algorithm and Otsu thresholding. Paper presented at the 2017 International Symposium on Geoinformatics (ISyG), 24-25 Nov. 2017
  30. 30.
    European Space Agency. 2015. Sentinel-2 User Handbook. ESA Standard Document Date 1, 1-64.
  31. 31.
    Tamiminia H, Salehi B, Mahdianpari M, Quackenbush L, Adeli S and Brisco B. 2020. Google Earth Engine for geo-big data applications: a meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing, 164: 152-170
  32. 32.
    Tan Z Q, Xu X L, Li Y L and Zhang Q. 2017. Wetland landscape pattern evolution of large Yangtze-connected lakes in the middle reaches of Yangtze River. Resources and Environment in the Yangtze Basin, 26(10): 1619-1629
  33. 33.
    Torres R, Snoeij P, Geudtner D, Bibby D, Davidson M, Attema E, Potin P, Rommen B, Floury N, Brown M, Traver I N, Deghaye P, Duesmann B, Rosich B, Miranda N, Bruno C, L'abbate M, Croci R, Pietropaolo A, Huchler M and Rostan F. 2012. GMES Sentinel-1 mission. Remote Sensing of Environment, 120: 9-24
  34. 34.
    Twele A, Cao W X, Plank S and Martinis S. 2016. Sentinel-1-based flood mapping: a fully automated processing chain. International Journal of Remote Sensing, 37(13): 2990-3004
  35. 35.
    Vuolo F, Żółtak M, Pipitone C, Zappa L, Wenng H, Immitzer M, Weiss M, Baret F and Atzberger C. 2016. Data service platform for Sentinel-2 surface reflectance and value-added products: system use and examples. Remote Sensing, 8(11): 938
  36. 36.
    Wang C L, Jiang W G, Deng Y, Ling Z Y and Deng Y W. 2022. Long time series water extent analysis for SDG 6.6.1 based on the GEE platform: a case study of Dongting Lake. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15: 490-503
  37. 37.
    Wang J D, Sheng Y W and Tong T S D. 2014. Monitoring decadal lake dynamics across the Yangtze Basin downstream of Three Gorges Dam. Remote Sensing of Environment, 152: 251-269
  38. 38.
    Wang Q. 2021. Progress of environmental remote sensing monitoring technology in China and some related frontier issues. National Remote Sensing Bulletin, 25(1): 25-36
  39. 39.
    Wang S L, Luo J and Chen Z Q. 2021. Study on relationship between water level and water area based on Google Earth Engine. Computer Systems and Applications, 30(6): 238-245
  40. 40.
    Wang W, Sui B, Lin N and Chen T L. 2020. Study on area changes of the Dongting lake based on remote sensing data. Advances in Meteorological Science and Technology, 10(3): 128-132
  41. 41.
    Wulder M A, Loveland T R, Roy D P, Crawford C J, Masek J G, Woodcock C E, Allen R G, Anderson M C, Belward A S, Cohen W B, Dwyer J, Erb A, Gao F, Griffiths P, Helder D, Hermosilla T, Hipple J D, Hostert P, Hughes M J, Huntington J, Johnson D M, Kennedy R, Kilic A, Li Z, Lymburner L, Mccorkel J, Pahlevan N, Scambos T A, Schaaf C, Schott J R, Sheng Y W, Storey J, Vermote E, Vogelmann J, White J C, Wynne R H and Zhu Z. 2019. Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225: 127-147
  42. 42.
    Xie W J, Yue C Y and Zhang W. 2017. Study on change of temporal and spatial characteristic of Dongting Lake from 1996 to 2016. Water Resources Informatization, (5): 32-38
  43. 43.
    Xing L W, Tang X M, Wang H B, Fan W F and Wang G H. 2018. Monitoring monthly surface water dynamics of Dongting Lake using Sentinel-1 data at 10 m. PeerJ, 6: e4992
  44. 44.
    Yan L, Long D, Bai L L, Zhang C J, Han Z Y, Li X D, Wang W, Shen S H and Ye Y T. 2020. A review on water resources stereoscopic monitoring systems based on multisource data. Journal of Remote Sensing (Chinese), 24(7): 787-803
  45. 45.
    Yang G S, Ma R H, Zhang L, Jiang J H, Yao S C, Zhang M and Zeng H A. 2010. Lake status major problem and protection in China. Journal of Lake Sciences, 22(6): 799-810
  46. 46.
    Yang K H, Yao F F, Wang J D, Luo J C, Shen Z F, Wang C and Song C Q. 2017. Recent dynamics of alpine lakes on the endorheic Changtang Plateau from multi-mission satellite data. Journal of Hydrology, 552: 633-645
  47. 47.
    Yang L, Wang L C, Yu D Q, Yao R, Li C A, He Q H, Wang S Q and Wang L Z. 2020. Four decades of wetland changes in Dongting Lake using Landsat observations during 1978-2018. Journal of Hydrology, 587: 124954
  48. 48.
    Yang L, Wang L C, Zhang M, Niu Z G, Yao R, Yu D Q, Li C A and He Q H. 2021. Variation of water body in Dongting Lake from in situ measurements and MODIS observations in recent decades. International Journal of Digital Earth, 14(8): 959-984
  49. 49.
    Yu S C, Yu D Q, Wang L C, Li C A, He Q H and Xiang F F. 2019. Remote sensing study of Dongting Lake beach changes before and after operation of Three Gorges Reservoir. Earth Science, 44(12): 4275-4283
  50. 50.
    Zhang M, Zeng Y N and Zhu Y S. 2017. Wetland mapping of Donting Lake Basin based on time-series MODIS data and object-oriented method. Journal of Remote Sensing, 21(3): 479-492
  51. 51.
    Zhu P, Huang S F, Yang Y M, Ma J W, Sun Y Y and Gao S Y. 2019. High-frequency monitoring of inland lakes water extent using time-series Sentinel-1 SAR data//2019 IEEE International Conference on Signal, Information and Data Processing. Chongqing: IEEE: 1-6

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