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宋利娟，景海涛，徐嘉慧，陈探，张大鹏，宋春桥.XXXX.联合哨兵卫星系列雷达与光学影像的洞庭湖水域面积变化高时空分辨率监测.遥感学报，XX（XX）： 1-16
SONG Lijuan，JING Haitao，XU Jiahui，CHEN Tan，ZHANG Dapeng，SONG Chunqiao. XXXX. High spatial and temporal resolution monitoring of water area changes in Dongting Lake from the joint Sentinel satellite series of radar and optical images. National Remote Sensing Bulletin， XX（XX）：1-16
洞庭湖是我国第二大淡水湖，干湿季节水体波动幅度大、频率高。卫星对洞庭湖水体变化的高频观测，对及时、准确地监测其水文动态变化具有重要意义。本研究的主要目的是利用Sentinel-1和Sentinel-2影像（10 m），在兼具高时频与空间分辨率条件下重建和分析2017-2020年间洞庭湖水域面积的精细时序信息。本文发展了一种基于湖区部分清晰影像来重建全湖水域面积的方法，该方法利用湖区某个区块面积与Sentinel-1全幅影像提取的湖泊面积构建的统计拟合关系建立经验模型，从而得到更密集的洞庭湖水域面积时间序列。拟合结果显示，每个区块的面积与总面积呈显著正相关，平均R,2,值为0.94。2017-2020年，获取119景Sentinel-1影像和38景Sentinel-2影像用于提取洞庭湖区块水体淹没范围，以重建整个湖区面积。结合所有Sentinel-1和Sentinel-2影像后，各月可获取的观测影像平均为6景，某些月内监测次数可达10次，时间间隔为3-6天。此外，本文重建的水域面积时间序列可以精确地刻画显著的季节波动和年际变化，水域面积在7月达到峰值，11月至2月达到谷值。一个月内最大面积与最小面积的平均比率为1.36。地表水域最剧烈的波动发生在11月份，比率为1.52。整合Sentinel-1/2影像观测，2017-2020年洞庭湖的平均水域面积约为1147.13 km,2,。与基于Sentinel-1/2影像构建的洞庭湖水域面积时间序列相比，结合Landsat-8影像的水体面积时间序列可在某些月份可以将水体观测的时间分辨率提高，但是对于水域面积的月均值和年均值影响较小。本研究联合高时空分辨率的哨兵系列雷达与光学影像发展高时频水域面积序列的精细提取方法，可为提升洞庭湖及长江中下游高动态湖泊水域遥感监测和水资源精细管理提供科技支撑。
Objective,2,As the second largest freshwater lake in China, Dongting Lake 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 of great significance for timely and accurate monitoring of its hydrological dynamic changes.The main aim of this study is 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 (10m) under the condition of high time-frequency and spatial resolution. This paper 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, so as to obtain a dense time series of Dongting Lake water area.The fitting results show that the area of each block is significantly positively correlated with the lake total area, and the average R,2, 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 to reconstruct the whole lake area. After combining all Sentinel-1 and Sentinel-2 images, 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 carry out fine monitoring of the water area change of Dongting Lake. In addition, the time series of water area reconstructed in this paper 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. Integrating Sentinel-1/2 image observation time series, the average water area of Dongting Lake from 2017 to 2020 is about 1147.13 km,2,.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, but it has little effect on the monthly and annual mean of water area. This study combines high temporal and spatial resolution sentinel series radar and optical images to develop a fine extraction method of high time-frequency water area series, which 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.,Method:Results:Conclusion,2
遥感监测洞庭湖Sentinel水域面积时间序列长江流域
Remote Sensing MonitoringDongting LakeSentinelWatershed AreaTime SeriesYangtze River Basin
Barsi, Julia A., Bahjat Alhammoud, Jeffrey Czapla-Myers, Ferran Gascon, Md Obaidul Haque, Morakot Kaewmanee, Larry Leigh, Brian L. Markham. 2018. Sentinel-2A MSI and Landsat-8 OLI radiometric cross comparison over desert sites. European Journal of Remote Sensing, 51(1): 822-837. [DOI: 10.1080/22797254.2018.1507613http://dx.doi.org/10.1080/22797254.2018.1507613]
Cai X., L. Feng, X. Hou, X. Chen. 2016. Remote Sensing of the Water Storage Dynamics of Large Lakes and Reservoirs in the Yangtze River Basin from 2000 to 2014. Sci Rep, 6: 36405. [DOI: 10.1038/srep36405http://dx.doi.org/10.1038/srep36405]
Donchyts, Gennadii, Jaap Schellekens, Hessel Winsemius, Elmar Eisemann, Nick van de Giesen. 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). [DOI: 10.3390/rs8050386http://dx.doi.org/10.3390/rs8050386]
Drusch M., U. Del Bello, S. Carlier, O. Colin, V. Fernandez, F. Gascon, B. Hoersch, et al. 2012. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services. Remote Sensing of Environment, 120: 25-36. [DOI: 10.1016/j.rse.2011.11.026http://dx.doi.org/10.1016/j.rse.2011.11.026]
Gorelick, Noel, Matt Hancher, Mike Dixon, Simon Ilyushchenko, David Thau, Rebecca Moore. 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202: 18-27. [DOI: 10.1016/j.rse.2017.06.031http://dx.doi.org/10.1016/j.rse.2017.06.031]
Hu, Yan-xia, Jin-liang Huang, Yun Du, Peng-peng Han, Jiu-ling Wang, Wei Huang. 2015. Monitoring wetland vegetation pattern response to water-level change resulting from the Three Gorges Project in the two largest freshwater lakes of China. Ecological Engineering, 74: 274-285. [DOI: 10.1016/j.ecoleng.2014.10.002http://dx.doi.org/10.1016/j.ecoleng.2014.10.002]
Li, Jian, David Roy. 2017. A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring. Remote Sensing, 9(9). [DOI: 10.3390/rs9090902http://dx.doi.org/10.3390/rs9090902]
Li, Juanjuan, Chao Wang, Lu Xu, Fan Wu, Hong Zhang, Bo Zhang. 2021. Multitemporal Water Extraction of Dongting Lake and Poyang Lake Based on an Automatic Water Extraction and Dynamic Monitoring Framework. Remote Sensing, 13(5). [DOI: 10.3390/rs13050865http://dx.doi.org/10.3390/rs13050865]
Li, Yang, Zhenguo Niu, Zeyu Xu, Xin Yan. 2020. Construction of High Spatial-Temporal Water Body Dataset in China Based on Sentinel-1 Archives and GEE. Remote Sensing, 12(15). [DOI: 10.3390/rs12152413http://dx.doi.org/10.3390/rs12152413]
Li, Yu, Sandro Martinis, Simon Plank, Ralf Ludwig. 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. [DOI: 10.1016/j.jag.2018.05.023http://dx.doi.org/10.1016/j.jag.2018.05.023]
Li, Yunliang, Qi Zhang, Jianrong Lu, Jing Yao, Zhiqiang Tan. 2018. Assessing surface water–groundwater interactions in a complex river‐floodplain wetland‐isolated lake system. River Research and Applications, 35(1): 25-36. [DOI: 10.1002/rra.3389http://dx.doi.org/10.1002/rra.3389]
Loveland, Thomas R., James R. Irons. 2016. Landsat 8: The plans, the reality, and the legacy. Remote Sensing of Environment, 185: 1-6. [DOI: 10.1016/j.rse.2016.07.033http://dx.doi.org/10.1016/j.rse.2016.07.033]
Manjusree, Panchagnula, L. Prasanna Kumar, Chandra Mohan Bhatt, Goru Srinivasa Rao, Veerubhotla Bhanumurthy. 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. [DOI: 10.1007/s13753-012-0011-5http://dx.doi.org/10.1007/s13753-012-0011-5]
Markert, Kel N., Amanda M. Markert, Timothy Mayer, Claire Nauman, Arjen Haag, Ate Poortinga, Biplov Bhandari, et al. 2020. Comparing Sentinel-1 Surface Water Mapping Algorithms and Radiometric Terrain Correction Processing in Southeast Asia Utilizing Google Earth Engine. Remote Sensing, 12(15). [DOI: 10.3390/rs12152469http://dx.doi.org/10.3390/rs12152469]
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. [DOI: 10.1080/01431169608948714http://dx.doi.org/10.1080/01431169608948714]
Pahlevan, Nima, Sundarabalan Balasubramanian, Sudipta Sarkar, Bryan Franz. 2018. Toward Long-Term Aquatic Science Products from Heritage Landsat Missions. Remote Sensing, 10(9). [DOI: 10.3390/rs10091337http://dx.doi.org/10.3390/rs10091337]
Pekel J. F., A. Cottam, N. Gorelick, A. S. Belward. 2016. High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633): 418-422. [DOI: 10.1038/nature20584http://dx.doi.org/10.1038/nature20584]
Steinhausen, Max J., Paul D. Wagner, Balaji Narasimhan, Björn Waske. 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. [DOI: 10.1016/j.jag.2018.08.011http://dx.doi.org/10.1016/j.jag.2018.08.011]
Suhet, B Hoersch. 2015. Sentinel-2 User Handbook. In.: ESA: EU.
Tamiminia, Haifa, Bahram Salehi, Masoud Mahdianpari, Lindi Quackenbush, Sarina Adeli, Brian Brisco. 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. [DOI: 10.1016/j.isprsjprs.2020.04.001http://dx.doi.org/10.1016/j.isprsjprs.2020.04.001]
Torres, Ramon, Paul Snoeij, Dirk Geudtner, David Bibby, Malcolm Davidson, Evert Attema, Pierre Potin, et al. 2012. GMES Sentinel-1 mission. Remote Sensing of Environment, 120: 9-24. [DOI: 10.1016/j.rse.2011.05.028http://dx.doi.org/10.1016/j.rse.2011.05.028]
Twele, André, Wenxi Cao, Simon Plank, Sandro Martinis. 2016. Sentinel-1-based flood mapping: a fully automated processing chain. International Journal of Remote Sensing, 37(13): 2990-3004. [DOI: 10.1080/01431161.2016.1192304http://dx.doi.org/10.1080/01431161.2016.1192304]
Vuolo, Francesco, Mateusz Żółtak, Claudia Pipitone, Luca Zappa, Hannah Wenng, Markus Immitzer, Marie Weiss, Frederic Baret, Clement Atzberger. 2016. Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples. Remote Sensing, 8(11). [DOI: 10.3390/rs8110938http://dx.doi.org/10.3390/rs8110938]
Wang C., W. Jiang, Y. Deng, Z. Ling, Y. Deng. 2021. 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: 1-1. [DOI: 10.1109/JSTARS.2021.3088127http://dx.doi.org/10.1109/JSTARS.2021.3088127]
Wang, Jida, Yongwei Sheng, Tak Shun D. Tong. 2014. Monitoring decadal lake dynamics across the Yangtze Basin downstream of Three Gorges Dam. Remote Sensing of Environment, 152: 251-269. [DOI: 10.1016/j.rse.2014.06.004http://dx.doi.org/10.1016/j.rse.2014.06.004]
Wulder, Michael A., Thomas R. Loveland, David P. Roy, Christopher J. Crawford, Jeffrey G. Masek, Curtis E. Woodcock, Richard G. Allen, et al. 2019. Current status of Landsat program, science, and applications. Remote Sensing of Environment, 225: 127-147. [DOI: 10.1016/j.rse.2019.02.015http://dx.doi.org/10.1016/j.rse.2019.02.015]
Xing L., X. Tang, H. Wang, W. Fan, G. Wang. 2018. Monitoring monthly surface water dynamics of Dongting Lake using Sentinel-1 data at 10 m. PeerJ, 6: e4992. [DOI: 10.7717/peerj.4992http://dx.doi.org/10.7717/peerj.4992]
Yang K., F. Yao, J. Wang, J. Luo, Z. Shen, C. Wang, C. Song. 2017. Recent dynamics of alpine lakes on the endorheic Changtang Plateau from multi-mission satellite data. Journal of Hydrology, 552: 633-645. [DOI: 10.1016/j.jhydrol.2017.07.024http://dx.doi.org/10.1016/j.jhydrol.2017.07.024]
Yang, Liu, Lunche Wang, Deqing Yu, Rui Yao, Chang'an Li, Qiuhua He, Shaoqiang Wang, Lizhe Wang. 2020. Four decades of wetland changes in Dongting Lake using Landsat observations during 1978–2018. Journal of Hydrology, 587. [DOI: 10.1016/j.jhydrol.2020.124954http://dx.doi.org/10.1016/j.jhydrol.2020.124954]
Yang, Liu, Lunche Wang, Ming Zhang, Zigeng Niu, Rui Yao, Deqing Yu, Chang’an Li, Qiuhua He. 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. [DOI: 10.1080/17538947.2021.1907464http://dx.doi.org/10.1080/17538947.2021.1907464]
Zhu P., S. Huang, Y. Yang, J. Ma, Y. Sun, S. Gao. 2019. High-frequency Monitoring of Inland Lakes Water Extent Using Time-Series Sentinel-1 SAR Data. IEEE International Conference on Signal, Information and Data Processing (ICSIDP), 1-6. [DOI:10.1109/ICSIDP47821.2019.9173066http://dx.doi.org/10.1109/ICSIDP47821.2019.9173066]
Chen S N, Jiang M. 2021. Application Research of Sentinel-1 SAR in Flood Range Extraction and Polarization Analysis. Journal of Geo-information Science, 23(06): 1063-1070
陈赛楠, 蒋弥. 2021. Sentinel-1 SAR在洪水范围提取与极化分析中的应用研究 地球信息科学学报, 23(06): 1063-1070 [DOI: 10.12082/dqxxkx.2021.200717http://dx.doi.org/10.12082/dqxxkx.2021.200717]
Cheng G, Li D, Wang Y, 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
成功, 李丹, 王勇, 康婷婷. 2015. 基于Landsat数据的洞庭湖水域面积变化及其原因分析. 灌溉排水学报, 34(S1): 246-249 [DOI: CNKI:SUN:GGPS.0.2015-S1-059http://dx.doi.org/CNKI:SUN:GGPS.0.2015-S1-059]
Cui L, Li Y P, Huang G H, Zeng X T. 2015. Dynamic changes of Dongting Lake based on Landsat-TM remote sensing data. South-to-North Water Transfers and Water Science & Technology, 13(01): 63-66+107
崔亮, 李永平, 黄国和, 曾雪婷. 2015. 基于Landsat-TM影像的洞庭湖水面动态变化 南水北调与水利科技, 13(01): 63-66+107 [DOI: 10.13476/j.cnki.nsbdqk.2015.01.015http://dx.doi.org/10.13476/j.cnki.nsbdqk.2015.01.015]
Du T, Xiong L H, Yi F H, Xiao Y, 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(06): 756-765
杜涛, 熊立华, 易放辉, 肖义, 宋求明. 2012. 基于MODIS数据的洞庭湖水体面积与多站点水位相关关系研究. 长江流域资源与环境, 21(06): 756-765 [DOI: CNKI:SUN:CJLY.0.2012-06-017http://dx.doi.org/CNKI:SUN:CJLY.0.2012-06-017]
Gao Y, Xie Y H, Zou D S, Hou T J, 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(03): 755-765
高耶, 谢永宏, 邹冬生, 侯婷娟, 李正最. 2019. 近40年洞庭湖区内湖水面面积变化及其驱动因素. 湖泊科学, 31(03): 755-765 [DOI: 10. 18307 /2019. 0314http://dx.doi.org/10.18307/2019.0314]
Li J G, Li J R, Huang S F, 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(03): 201-207
李景刚, 李纪人, 黄诗峰, 臧文斌. 2010. 近10年来洞庭湖区水面面积变化遥感监测分析. 中国水利水电科学研究院学报, 8(03): 201-207 [DOI: 10.3969/j.issn.1672-3031.2011.03.008http://dx.doi.org/10.3969/j.issn.1672-3031.2011.03.008]
Li J G, Li J R, Huang S F, 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(05): 923-933
李景刚, 李纪人, 黄诗峰, 左春刚. 2009. Terra/MODIS时间序列数据在湖泊水域面积动态监测中的应用研究——以洞庭湖地区为例 自然资源学报, 24(05): 923-933 [DOI: CNKI:SUN:ZRZX.0.2009-05-021http://dx.doi.org/CNKI:SUN:ZRZX.0.2009-05-021]
Li J, Zhang W, 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
李军, 张维, 许欣. 2020. 基于Sentinel-1的洞庭湖区洪涝灾害信息提取与分析. 安徽农学通报, 26(19): 151-153 [DOI: 10.16377/j.cnki.issn1007-7731.2020.19.063http://dx.doi.org/10.16377/j.cnki.issn1007-7731.2020.19.063]
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. 2011. China's lakes at present: Number, area and spatial distribution. Scientia Sinica(Terrae), 41(03): 394-401
马荣华, 杨桂山, 段洪涛, 姜加虎, 王苏民, 冯学智, 李爱农, 孔繁翔, 薛滨, 吴敬禄. 2011. 中国湖泊的数量、面积与空间分布. 中国科学:地球科学, 41(003): 394-401 [DOI: 10.1360/zd-2011-41-3-394http://dx.doi.org/10.1360/zd-2011-41-3-394]
Song C Q, Zhan P F, Ma R H. 2020. Progress in remote sensing study on lake hydrologic regime. Journal of Lake Sciences, 32(05): 1406-1420
宋春桥, 詹鹏飞, 马荣华. 2020. 湖泊水情遥感研究进展. 湖泊科学, 32(05): 1406-1420 [DOI: 10.18307/2020.0514http://dx.doi.org/10.18307/2020.0514]
Tan Z Q, Xu X L, Li Y L, Zhang Q. 2017. Wetland Landscape pattern evolution of large Yangtze-connected lakes in the middle reaches of the Yangtze River. Resources and Environment in the Yangtze Basin,(10): 1619-1629
谭志强, 许秀丽, 李云良, 张奇. 2017. 长江中游大型通江湖泊湿地景观格局演变特征. 长江流域资源与环境, 26(10): 1619-1629 [DOI: 10.11870/cjlyzyyhj201710014http://dx.doi.org/10.11870/cjlyzyyhj201710014]
Wang Q. 2021. Progress of environmental remote sensing monitoring technology in China and some related frontier issues. National Remote Sensing Bulletin, 25(01): 25-36
王桥. 2021. 中国环境遥感监测技术进展及若干前沿问题. 遥感学报, 25(01): 25-36 [DOI: 10.11834/jrs.20210572http://dx.doi.org/10.11834/jrs.20210572]
Wang S L, Luo J, Chen Z Q. 2021. Study on Relationship Between Water Level and Water Area Based on Google Earth Engine. Computer Systems & Applications, 30(06): 238-245
王诗蕾, 罗晋, 陈泽强. 2021. 基于Google Earth Engine的湖泊水位与水体面积关系研究. 计算机系统应用, 30(06): 238-245 [DOI: 10.15888/j.cnki.csa.007193http://dx.doi.org/10.15888/j.cnki.csa.007193]
Wang W, Sui B, Lin N, Chen T L. 2020. Study on Area Changes of the Dongting Lake Based on Remote Sensing Data. Advances in Meteorological Science and Technology, 10(03): 128-132
王威, 隋兵, 林南, 陈太龙. 2020. 基于Landsat遥感数据的洞庭湖面积变化研究. 气象科技进展, 10(03): 128-132 [DOI: SUN:QXKZ.0.2020-03-028http://dx.doi.org/SUN:QXKZ.0.2020-03-028]
Xie W J, Yue C Y, Zhang W. 2017. Study on change of temporal and spatial characteristic of Dongting Lake from 1996 to 2016. Water Resources Informatization,(05): 32-38
谢文君, 岳翠莹, 张文. 2017. 洞庭湖1996—2016年时空特征变化研究. 水利信息化,(05): 32-38 [DOI: 10.19364/j.1674-9405.2017.05.007http://dx.doi.org/10.19364/j.1674-9405.2017.05.007]
Yan L, Long D, Bai L L, Zhang C J, Han Z Y, Li X D, Wang W, Shen S H, Ye Y T. 2020. A review on water resources stereoscopic monitoring systems based on multisource data. Journal of Remote Sensing（Chinese）, 24(07): 787-803
岩腊, 龙笛, 白亮亮, 张才金, 韩忠颖, 李兴东, 王文, 申邵洪, 冶运涛. 2020. 基于多源信息的水资源立体监测研究综述. 遥感学报, 24(07): 787-803 [DOI: 10.11834/jrs.20210572http://dx.doi.org/10.11834/jrs.20210572]
Yang G S, Ma R H, Zhang L, Jiang J H, Yao S C, Zhang M, Zeng H A. 2010. Lake status major problem and protection in China. Journal of Lake Sciences, 22(06): 799-810
杨桂山, 马荣华, 张路, 姜加虎, 姚书春, 张民, 曾海鳌. 2010. 中国湖泊现状及面临的重大问题与保护策略. 湖泊科学, 22(06): 799-810 [DOI: 10.18307/2010.0601http://dx.doi.org/10.18307/2010.0601]
Yu S C, Yu D Q, Wang L C, Li C A, He Q H, Xiang F F. 2019. Remote Sensing Study of Dongting Lake Beach Changes before and after Operation of Three Gorges Reservoir. Journal of Earth Science, 044(012): P.4275-4283
余姝辰, 余德清, 王伦澈, 李长安, 贺秋华, 向菲菲. 2019. 三峡水库运行前后洞庭湖洲滩面积变化遥感认识. 地球科学, 44(12): 4275-4283 [DOI: CNKI:SUN:DQKX.0.2019-12-037http://dx.doi.org/CNKI:SUN:DQKX.0.2019-12-037]
Zhang M, Zeng Y N, 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(03): 479-492
张猛, 曾永年, 朱永森. 2017. 面向对象方法的时间序列MODIS数据湿地信息提取——以洞庭湖流域为例. 遥感学报, 21(03): 479-492 [DOI: 10.11834/jrs.20176129http://dx.doi.org/10.11834/jrs.20176129]
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