{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T22:15:43Z","timestamp":1768083343127,"version":"3.49.0"},"reference-count":64,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2018YFD0900806"],"award-info":[{"award-number":["2018YFD0900806"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent decades, the increasing frequency and severity of cyanobacterial blooms in recreational lakes and water supply reservoirs have become a great concern to public health and a significant threat to the environment. Cyanobacterial bloom monitoring is the basis of early warning and treatment. Previous research efforts have always focused on monitoring blooms in a few specific lakes in China using moderate resolution imaging spectroradiometer (MODIS) images, which are available for the years 2000 onward. However, the lack of overall information on long-term cyanobacterial blooms in the lakes and reservoirs in the middle\u2013lower Yangtze River (MLYR) basin is an obstacle to better understanding the dynamics of cyanobacterial blooms at a watershed scale. In this study, we extracted the yearly coverage area and frequency of cyanobacterial blooms that occurred from 1990 to 2016 in 30 large lakes and 10 reservoirs (inundation area &gt;50 km2) by using time series Landsat satellite images from Google Earth Engine (GEE). Then, we calculated the cyanobacterial bloom area percentage (CAP) and the cyanobacterial bloom frequency index (CFI) and analyzed their inter-annual variation and trends. We also investigated the main driving forces of changes in the CAP and CFI in each lake and reservoir. We found that all reservoirs and more than 60% of lakes exhibited an increasing frequency and coverage area of cyanobacterial blooms under the pressures of climate change and anthropogenic interferences. Reservoirs were more prone to be affected by fertilizer consumption from their regional surroundings than lakes. High temperatures increased blooms of cyanobacteria, while precipitation in the lake and reservoir regions somewhat alleviated blooms. This study completes the data records of cyanobacterial blooms in large lakes and reservoirs located in hotspots of the MLYR basin and provides more baseline information before 2000, which will present references for water resource management and freshwater conservation.<\/jats:p>","DOI":"10.3390\/rs11151754","type":"journal-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T08:45:39Z","timestamp":1564130739000},"page":"1754","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Increasing Outbreak of Cyanobacterial Blooms in Large Lakes and Reservoirs under Pressures from Climate Change and Anthropogenic Interferences in the Middle\u2013Lower Yangtze River Basin"],"prefix":"10.3390","volume":"11","author":[{"given":"Jia-Min","family":"Zong","sequence":"first","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of the Yangtze River Estuary, and Shanghai Institute of EcoChongming (SIEC), Fudan University, Shanghai 200433, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8013-3660","authenticated-orcid":false,"given":"Xin-Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of the Yangtze River Estuary, and Shanghai Institute of EcoChongming (SIEC), Fudan University, Shanghai 200433, China"}]},{"given":"Qiao-Yan","family":"Zhong","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of the Yangtze River Estuary, and Shanghai Institute of EcoChongming (SIEC), Fudan University, Shanghai 200433, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0956-7428","authenticated-orcid":false,"given":"Xiang-Ming","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA"}]},{"given":"Jun","family":"Ma","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of the Yangtze River Estuary, and Shanghai Institute of EcoChongming (SIEC), Fudan University, Shanghai 200433, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3530-2469","authenticated-orcid":false,"given":"Bin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of the Yangtze River Estuary, and Shanghai Institute of EcoChongming (SIEC), Fudan University, Shanghai 200433, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/S0380-1330(82)71982-3","article-title":"Large Lakes of the World","volume":"8","author":"Herdendorf","year":"1982","journal-title":"J. Great Lakes Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.rse.2016.12.006","article-title":"Fifteen-year monitoring of the turbidity dynamics in large lakes and reservoirs in the middle and lower basin of the Yangtze River, China","volume":"190","author":"Hou","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.ecoser.2014.09.004","article-title":"How important are the wetlands in the middle\u2013lower Yangtze River region: An ecosystem service valuation approach","volume":"10","author":"Li","year":"2014","journal-title":"Ecosyst. Serv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"7607","DOI":"10.1080\/01431161.2013.822602","article-title":"Mapping inland lake water quality across the Lower Peninsula of Michigan using Landsat TM imagery","volume":"34","author":"Torbick","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.ecolind.2018.03.006","article-title":"Spatial variability and temporal dynamics of HABs in Northeast China","volume":"90","author":"Fang","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1166","DOI":"10.1126\/science.317.5842.1166","article-title":"ECOLOGY: Doing Battle With the Green Monster of Taihu Lake","volume":"317","author":"Guo","year":"2007","journal-title":"Science"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.rse.2016.12.013","article-title":"Using Landsat to extend the historical record of lacustrine phytoplankton blooms: A Lake Erie case study","volume":"191","author":"Ho","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6448","DOI":"10.1073\/pnas.1216006110","article-title":"Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions","volume":"110","author":"Michalak","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1016\/j.scitotenv.2011.02.001","article-title":"Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic-induced change","volume":"409","author":"Paerl","year":"2011","journal-title":"Sci. Total Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1007\/s00248-012-0159-y","article-title":"Harmful Cyanobacterial Blooms: Causes, Consequences, and Controls","volume":"65","author":"Paerl","year":"2013","journal-title":"Microb. Ecol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.hal.2015.07.009","article-title":"Harmful algal blooms and climate change: Learning from the past and present to forecast the future","volume":"49","author":"Wells","year":"2015","journal-title":"Harmful Algae"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"36405","DOI":"10.1038\/srep36405","article-title":"Remote Sensing of the Water Storage Dynamics of Large Lakes and Reservoirs in the Yangtze River Basin from 2000 to 2014","volume":"6","author":"Cai","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.rse.2014.06.004","article-title":"Monitoring decadal lake dynamics across the Yangtze Basin downstream of Three Gorges Dam","volume":"152","author":"Wang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.geomorph.2013.02.018","article-title":"Delineation of lakes and reservoirs in large river basins: An example of the Yangtze River Basin, China","volume":"190","author":"Yang","year":"2013","journal-title":"Geomorphology"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.isprsjprs.2016.12.011","article-title":"Quantifying annual changes in built-up area in complex urban-rural landscapes from analyses of PALSAR and Landsat images","volume":"124","author":"Qin","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1002\/jsfa.4607","article-title":"Effect of reforestation on nitrogen and phosphorus dynamics in the catchment ecosystems of subtropical China: The example of the Hanjiang River basin","volume":"92","author":"Wang","year":"2012","journal-title":"J. Sci. Food Agric."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wang, Y., Ma, J., Xiao, X., Wang, X., Dai, S., and Zhao, B. (2019). Long-Term Dynamic of Poyang Lake Surface Water: A Mapping Work Based on the Google Earth Engine Cloud Platform. Remote Sens., 11.","DOI":"10.3390\/rs11030313"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1016\/j.rse.2018.08.026","article-title":"Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index","volume":"217","author":"Wang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1016\/j.watres.2017.06.022","article-title":"MODIS observations of cyanobacterial risks in a eutrophic lake: Implications for long-term safety evaluation in drinking-water source","volume":"122","author":"Duan","year":"2017","journal-title":"Water Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1007\/s00027-014-0367-2","article-title":"Distribution and incidence of algal blooms in Lake Taihu","volume":"77","author":"Duan","year":"2015","journal-title":"Aquat. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1007\/s12665-017-6678-6","article-title":"Comprehensive evaluation of the potential risk from cyanobacteria blooms in Poyang Lake based on nutrient zoning","volume":"76","author":"Liu","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/s10750-016-3063-5","article-title":"A comparison of factors influencing the summer phytoplankton biomass in China\u2019s three largest freshwater lakes: Poyang, Dongting, and Taihu","volume":"792","author":"Liu","year":"2017","journal-title":"Hydrobiologia"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1007\/s10750-015-2536-2","article-title":"Cyanobacteria in the complex river-connected Poyang Lake: Horizontal distribution and transport","volume":"768","author":"Liu","year":"2016","journal-title":"Hydrobiologia"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1029\/2008EO220001","article-title":"Satellite-Observed Algae Blooms in China\u2019s Lake Taihu","volume":"89","author":"Wang","year":"2008","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"10523","DOI":"10.3390\/rs70810523","article-title":"Fourteen-Year Record (2000\u20132013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.ecolind.2009.11.001","article-title":"A review of methods for analysing spatial and temporal patterns in coastal water quality","volume":"11","author":"Bierman","year":"2011","journal-title":"Ecol. Indic."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"C04002","DOI":"10.1029\/2009JC005511","article-title":"Moderate Resolution Imaging Spectroradiometer (MODIS) observations of cyanobacteria blooms in Taihu Lake, China","volume":"115","author":"Hu","year":"2010","journal-title":"J. Geophys. Res."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Liang, Q., Zhang, Y., Ma, R., Loiselle, S., Li, J., and Hu, M. (2017). A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu. Remote Sens., 9.","DOI":"10.3390\/rs9020133"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1093\/plankt\/fbq039","article-title":"Seasonal-spatial variation and remote sensing of phytoplankton absorption in Lake Taihu, a large eutrophic and shallow lake in China","volume":"32","author":"Zhang","year":"2010","journal-title":"J. Plankton Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/JSTARS.2017.2757006","article-title":"Distinguishing Cyanobacterial Bloom From Floating Leaf Vegetation in Lake Taihu Based on Medium-Resolution Imaging Spectrometer (MERIS) Data","volume":"11","author":"Zhu","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2818","DOI":"10.1080\/01431161.2018.1430912","article-title":"Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager","volume":"39","author":"Keith","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","first-page":"335","article-title":"Monitoring levels of cyanobacterial blooms using the visual cyanobacteria index (VCI) and floating algae index (FAI)","volume":"38","author":"Oyama","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.rse.2014.04.031","article-title":"Distinguishing surface cyanobacterial blooms and aquatic macrophytes using Landsat\/TM and ETM+ shortwave infrared bands","volume":"157","author":"Oyama","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8552","DOI":"10.1080\/01431161.2018.1488289","article-title":"Landsat-satellite-based analysis of spatial\u2013temporal dynamics and drivers of CyanoHABs in the plateau Lake Dianchi","volume":"39","author":"Zhao","year":"2018","journal-title":"Int. J. Remote Sens"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3705","DOI":"10.1007\/s12665-013-2764-6","article-title":"Detection of algal bloom and factors influencing its formation in Taihu Lake from 2000 to 2011 by MODIS","volume":"71","author":"Huang","year":"2014","journal-title":"Environ. Earth Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2017.09.013","article-title":"Big Remotely Sensed Data: Tools, applications and experiences","volume":"202","author":"Casu","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_38","unstructured":"(2018, January 10). Landsat 5\/7\/8 Surface Reflectance Datasets. Available online: https:\/\/developers.google.com\/earth-engine\/datasets\/catalog\/LANDSAT_LC08_C01_T1_SR."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.rse.2015.04.021","article-title":"A scalable satellite-based crop yield mapper","volume":"164","author":"Lobell","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.rse.2015.02.009","article-title":"Generating synthetic Landsat images based on all available Landsat data: Predicting Landsat surface reflectance at any given time","volume":"162","author":"Zhu","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices over a global set of TM images for EOS-MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A 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_45","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.rse.2004.03.010","article-title":"Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data","volume":"91","author":"Xiao","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_46","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_47","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1016\/j.rse.2009.05.012","article-title":"A novel ocean color index to detect floating algae in the global oceans","volume":"113","author":"Hu","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Niroumand-Jadidi, M., and Vitti, A. (2017). Reconstruction of River Boundaries at Sub-Pixel Resolution: Estimation and Spatial Allocation of Water Fractions. IJGI, 6.","DOI":"10.3390\/ijgi6120383"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.scitotenv.2017.03.259","article-title":"Continued decrease of open surface water body area in Oklahoma during 1984\u20132015","volume":"595","author":"Zou","year":"2017","journal-title":"Sci. Total. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3810","DOI":"10.1073\/pnas.1719275115","article-title":"Divergent trends of open-surface water body area in the contiguous United States from 1984 to 2016","volume":"115","author":"Zou","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1016\/j.rse.2007.08.007","article-title":"Typology of oases in northern Oman based on Landsat and SRTM imagery and geological survey data","volume":"112","author":"Luedeling","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_52","unstructured":"(2018, March 01). Sentinel-2 MSI: MultiSpectral Instrument, Level-1C. Available online: https:\/\/developers.google.com\/earth-engine\/datasets\/catalog\/COPERNICUS_S2."},{"key":"ref_53","unstructured":"Xu, X. (2019, March 22). Watershed and River Network Dataset of China Based on DEM Extraction. Available online: http:\/\/www.resdc.cn\/DOI."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1680","DOI":"10.1890\/15-1784.1","article-title":"Warming and fertilization alter the dilution effect of host diversity on disease severity","volume":"97","author":"Liu","year":"2016","journal-title":"Ecology"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"3522","DOI":"10.1021\/es8031852","article-title":"Two-Decade Reconstruction of Algal Blooms in China\u2019s Lake Taihu","volume":"43","author":"Duan","year":"2009","journal-title":"Environ. Sci. Technol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/j.hal.2011.10.027","article-title":"The rise of harmful cyanobacteria blooms: The potential roles of eutrophication and climate change","volume":"14","author":"Davis","year":"2012","journal-title":"Harmful Algae"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.scitotenv.2014.03.031","article-title":"Satellite data regarding the eutrophication response to human activities in the plateau lake Dianchi in China from 1974 to 2009","volume":"485\u2013486","author":"Huang","year":"2014","journal-title":"Sci. Total Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1016\/j.jclepro.2019.02.031","article-title":"Is China\u2019s River Chief Policy effective? Evidence from a quasi-natural experiment in the Yangtze River Economic Belt, China","volume":"220","author":"She","year":"2019","journal-title":"J. Clean. Prod."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1111\/j.1365-2486.2007.01510.x","article-title":"Summer heatwaves promote blooms of harmful cyanobacteria","volume":"14","author":"Huisman","year":"2008","journal-title":"Glob. Chang. Biol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1016\/j.rse.2017.10.005","article-title":"Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis","volume":"204","author":"Belgiu","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.rse.2017.10.007","article-title":"Combining UAV and Sentinel-2 auxiliary data for forest growing stock volume estimation through hierarchical model-based inference","volume":"204","author":"Puliti","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.rse.2017.07.015","article-title":"Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications","volume":"199","author":"Veloso","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.rse.2015.11.030","article-title":"Investigating the capability of WorldView-3 superspectral data for direct hydrocarbon detection","volume":"173","author":"Asadzadeh","year":"2016","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/15\/1754\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:09:36Z","timestamp":1760188176000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/15\/1754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":64,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["rs11151754"],"URL":"https:\/\/doi.org\/10.3390\/rs11151754","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,25]]}}}