{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T13:45:08Z","timestamp":1736948708142,"version":"3.33.0"},"reference-count":46,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,5,24]],"date-time":"2017-05-24T00:00:00Z","timestamp":1495584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41301390","U1404401"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Youth Innovation Promotion Association CAS","award":["2017089"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Poyang Lake is the largest freshwater lake in China and is well known for its ecological function and economic importance. However, due to the influence of clouds, it is difficult to dynamically monitor the changes in water surface areas using optical remote sensing. To address this problem, we propose a novel method to monitor these changes using Sentinel-1A data. First, the Sentinel-1A water index (SWI) was built using a linear model and a stepwise multiple regression analysis method with Sentinel-1A and Landsat-8 imagery acquired on the same day. Second, water surface areas of Poyang Lake from 24 May 2015 to 14 November 2016 were extracted by the threshold method utilizing time-series SWI data with an interval of 12 days. The results showed that the SWI threshold classification method could be applied to different regions during different periods with high quantity accuracy (approximately 99%). The water surface areas ranged between 1726.73 km2 and 3729.19 km2 during the study periods, indicating an extreme variability in the short term. The maximum and average values of the changed areas were 875.57 km2 (with a change rate of 35%) and 197.58 km2 (with a change rate of 8.2%), respectively, after 12 days. The changes in the mid-western region of Poyang Lake were more dramatic. These results provide baseline data for high-frequency monitoring of the ecological environment and wetland management in Poyang Lake.<\/jats:p>","DOI":"10.3390\/rs9060521","type":"journal-article","created":{"date-parts":[[2017,5,24]],"date-time":"2017-05-24T16:13:11Z","timestamp":1495642391000},"page":"521","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Monitoring of the Largest Freshwater Lake in China Using a New Water Index Derived from High Spatiotemporal Resolution Sentinel-1A Data"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4567-2313","authenticated-orcid":false,"given":"Haifeng","family":"Tian","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China"},{"name":"College of Resource and Environment, University of Chinese Academy of Sciences, Yuquan Road 19, Shijingshan, Beijing 100049, China"}]},{"given":"Wang","family":"Li","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China"}]},{"given":"Mingquan","family":"Wu","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China"}]},{"given":"Ni","family":"Huang","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China"}]},{"given":"Guodong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Environment and Planning, Henan University, Jinmingdadao Road, Kaifeng 475004, China"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China"},{"name":"College of Resource and Environment, University of Chinese Academy of Sciences, Yuquan Road 19, Shijingshan, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5959-9351","authenticated-orcid":false,"given":"Zheng","family":"Niu","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.O. Box 9718, Datun Road, Chaoyang, Beijing 100101, China"},{"name":"College of Resource and Environment, University of Chinese Academy of Sciences, Yuquan Road 19, Shijingshan, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1029\/2010GL045514","article-title":"A half-century of changes in China\u2019s lakes: Global warming or human influence?","volume":"37","author":"Ma","year":"2010","journal-title":"Geophys. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2281","DOI":"10.1073\/pnas.1411748112","article-title":"Rapid loss of lakes on the mongolian plateau","volume":"112","author":"Tao","year":"2015","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1007\/s12524-015-0519-4","article-title":"Analysis and inversion of the nutritional status of China\u2019s Poyang Lake using MODIS data","volume":"44","author":"Hui","year":"2016","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1007\/s12665-016-5941-6","article-title":"Spatiotemporal pattern of bird habitats in the Poyang Lake based on landsat images","volume":"75","author":"Yang","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.scitotenv.2016.03.108","article-title":"Changing land use and its impact on the habitat suitability for wintering anseriformes in China\u2019s Poyang Lake region","volume":"557","author":"Tang","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.rse.2012.01.014","article-title":"Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 2010","volume":"121","author":"Feng","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.jhydrol.2015.01.048","article-title":"Capturing variations in inundation with satellite remote sensing in a morphologically complex, large lake","volume":"523","author":"Wu","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.quaint.2009.07.020","article-title":"Lake water changes in response to climate change in northern China: Simulations and uncertainty analysis","volume":"212","author":"Yu","year":"2010","journal-title":"Quat. Int."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1007\/s10584-008-9530-x","article-title":"Global climate change and potential effects on pacific salmonids in freshwater ecosystems of southeast alaska","volume":"95","author":"Bryant","year":"2009","journal-title":"Clim. Chang."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3220","DOI":"10.1016\/j.rse.2011.07.006","article-title":"Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China","volume":"115","author":"Dronova","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1016\/j.scitotenv.2016.04.200","article-title":"Wetland loss due to land use change in the lower parana river delta, argentina","volume":"568","author":"Sica","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.rse.2016.01.011","article-title":"Four decades of wetland changes of the largest freshwater lake in China: Possible linkage to the three gorges dam?","volume":"176","author":"Feng","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.rse.2004.11.009","article-title":"Mapping lake cdom by satellite remote sensing","volume":"94","author":"Kutser","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"3","article-title":"Remote sensing monitors lakes","volume":"34","author":"Kallio","year":"2012","journal-title":"Trac Trends Anal. Chem."},{"key":"ref_15","first-page":"201","article-title":"Optical remote sensing of lakes: An overview on lake maggiore","volume":"73","author":"Giardino","year":"2014","journal-title":"J. Limnol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1016\/j.jvolgeores.2008.03.005","article-title":"Satellite observations reveal little inter-annual variability in the radiant flux from the mount erebus lava lake","volume":"177","author":"Wright","year":"2008","journal-title":"J. Volcanol. Geotherm. Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1007\/s10113-015-0853-7","article-title":"Glacier changes and related glacial lake expansion in the bhutan himalaya, 1990\u20132010","volume":"16","author":"Veettil","year":"2016","journal-title":"Reg. Environ. Chang."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3623","DOI":"10.1007\/s12665-014-3651-5","article-title":"Environmental monitoring and change assessment of toshka lakes in southern egypt using remote sensing","volume":"73","author":"Hereher","year":"2015","journal-title":"Environ. Earth Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2610","DOI":"10.1016\/j.rse.2010.05.032","article-title":"An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions","volume":"114","author":"Zhu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.inffus.2015.12.005","article-title":"An improved high spatial and temporal data fusion approach for combining Landsat and MODIS data to generate daily synthetic Landsat imagery","volume":"31","author":"Wu","year":"2016","journal-title":"Inf. Fusion"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1109\/TGRS.2006.872081","article-title":"On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance","volume":"44","author":"Gao","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"063507","DOI":"10.1117\/1.JRS.6.063507","article-title":"Use of MODIS and Landsat time series data to generate high-resolution temporal synthetic Landsat data using a spatial and temporal reflectance fusion model","volume":"6","author":"Wu","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_23","first-page":"154","article-title":"Dryland crops recognition under complex planting structure based on radarsat-2 images","volume":"31","author":"Tian","year":"2015","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Long, S., Fatoyinbo, T.E., and Policelli, F. (2014). Flood extent mapping for namibia using change detection and thresholding with SAR. Environ. Res. Lett., 9.","DOI":"10.1088\/1748-9326\/9\/3\/035002"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"Gmes Sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Cazals, C., Rapinel, S., Frison, P.L., Bonis, A., Mercier, G., Mallet, C., Corgne, S., and Rudant, J.P. (2016). Mapping and characterization of hydrological dynamics in a coastal marsh using high temporal resolution Sentinel-1a images. Remote Sens., 8.","DOI":"10.3390\/rs8070570"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1007\/s12524-011-0162-7","article-title":"An adaptive water extraction method from remote sensing image based on NDWI","volume":"40","author":"Qiao","year":"2012","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1029\/2008GL035772","article-title":"Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using oklahoma mesonet soil moisture data","volume":"35","author":"Gu","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI-a normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","first-page":"1339","article-title":"Hydrolgical effects of Poyang Lake catchment in response to climate changes Resour","volume":"22","author":"Li","year":"2013","journal-title":"Environ. Yangtze Basin"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"101","DOI":"10.2747\/1548-1603.46.1.101","article-title":"Inundation extent and flood frequency mapping using Landsat imagery and digital elevation models","volume":"46","author":"Qi","year":"2009","journal-title":"Gisci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1109\/JSTARS.2014.2342742","article-title":"Optimizing remote sensing-based level-area modeling of large lake wetlands: Case study of Poyang Lake","volume":"8","author":"Cai","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4870","DOI":"10.3390\/rs6064870","article-title":"Rapid damage assessment by means of multi-temporal SAR-a comprehensive review and outlook to Sentinel-1","volume":"6","author":"Plank","year":"2014","journal-title":"Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1109\/TGRS.2012.2197861","article-title":"Feasibility of along-track displacement measurement from Sentinel-1 interferometric wide-swath mode","volume":"51","author":"Jung","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","first-page":"181","article-title":"Rice information extraction using multi-polarization airborne synthetic aperture radar data","volume":"37","author":"Li","year":"2011","journal-title":"J. Zhejiang Univ. Agric. Life Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1016\/j.isprsjprs.2007.06.001","article-title":"Despeckle and geographical feature extraction in SAR images by wavelet transform","volume":"62","author":"Gupta","year":"2007","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1080\/0143116031000115085","article-title":"Smoothing vegetation spectra with wavelets","volume":"25","author":"Schmidt","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","unstructured":"Michel, U., Schulz, K., Ehlers, M., Nikolakopoulos, K.G., and Civco, D. (2015). Flood mapping from Sentinel-1 and Landsat-8 data. A case study from river Evros, Greece. Earth Resources and Environmental Remote Sensing\/GIS Applications VI, SPIE\u2014International Society for Optics and Photonics."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.5194\/gmd-7-1247-2014","article-title":"Root mean square error (RMSE) or mean absolute error (MAE)?-arguments against avoiding RMSE in the literature","volume":"7","author":"Chai","year":"2014","journal-title":"Geosci. Model Dev."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.ocemod.2013.08.003","article-title":"Problems in RMSE-based wave model validations","volume":"72","author":"Mentaschi","year":"2013","journal-title":"Ocean Model."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neucom.2015.12.114","article-title":"Mean absolute percentage error for regression models","volume":"192","author":"Golden","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1109\/TGRS.2005.861548","article-title":"An unsupervised artificial immune classifier for multi\/hyperspectral remote sensing imagery","volume":"44","author":"Zhong","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"5461","DOI":"10.1080\/01431161.2010.502155","article-title":"Unsupervised remote sensing image classification using an artificial immune network","volume":"32","author":"Zhong","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Yu, H.Y., Gao, L.R., Li, J., Li, S.S., Zhang, B., and Benediktsson, J.A. (2016). Spectral-spatial hyperspectral image classification using subspace-based support vector machines and adaptive markov random fields. Remote Sens., 8.","DOI":"10.3390\/rs8040355"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1080\/15481603.2015.1114199","article-title":"A support vector machine classifier based on a new kernel function model for hyperspectral data","volume":"53","author":"Lin","year":"2016","journal-title":"Gisci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/521\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,14]],"date-time":"2025-01-14T16:24:29Z","timestamp":1736871869000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/521"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,24]]},"references-count":46,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2017,6]]}},"alternative-id":["rs9060521"],"URL":"https:\/\/doi.org\/10.3390\/rs9060521","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2017,5,24]]}}}