{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:21:44Z","timestamp":1772691704176,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2022,9,9]],"date-time":"2022-09-09T00:00:00Z","timestamp":1662681600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Adequate water resource management is essential for fulfilling ecosystem and human needs. Nainital Lake is a popular lake in Uttarakhand State in India, attracting lakhs of tourists annually. Locals also use the lake water for domestic purposes and irrigation. The increasing impact of climate change and over-exploration of water from lakes make their regular monitoring key to implementing effective conservation measures and preventing substantial degradation. In this study, dynamic change in the water spread area of Nainital Lake from 2001 to 2018 has been investigated using the multiband rationing indices, namely normalized difference water index (NDWI), modified normalized difference water index (MNDWI), and water ratio index (WRI). The model has been developed in QGIS 3.4 software. A physical GPS survey of the lake was conducted to check the accuracy of these indices. Furthermore, to determine the trend in water surface area for a studied period, a non-parametric Mann\u2013Kendall test was used. San\u2019s slope estimator test determined the magnitude of the trend and total percentage change. The result of the physical survey shows that NDWI was the best method, with an accuracy of 96.94%. Hence, the lake water spread area trend is determined based on calculated NDWI values. The lake water spread area significantly decreased from March to June and July to October at a 5% significance level. The maximum decrease in water spread area has been determined from March to June (7.7%), which was followed by the period July to October (4.67%) and then November to February (2.79%). The study results show that the lake\u2019s water spread area decreased sharply for the analyzed period. The study might be helpful for the government, policymakers, and water experts to make plans for reclaiming and restoring Nainital Lake. This study is very helpful in states such as Uttarakhand, where physical mapping is not possible every time due to its tough topography and climate conditions.<\/jats:p>","DOI":"10.3390\/s22186827","type":"journal-article","created":{"date-parts":[[2022,9,13]],"date-time":"2022-09-13T04:05:41Z","timestamp":1663041941000},"page":"6827","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Detection of Water Spread Area Changes in Eutrophic Lake Using Landsat Data"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6035-595X","authenticated-orcid":false,"given":"Vaibhav","family":"Deoli","sequence":"first","affiliation":[{"name":"Department of Environmental Science and Technology, Indian Institute of Technology, Indian School of Mines, Dhanbad 826004, India"},{"name":"Department of Soil and Water Conservation Engineering, GB Pant University of Agriculture and Technology, Pantnagar 263145, India"}]},{"given":"Deepak","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Soil and Water Conservation Engineering, GB Pant University of Agriculture and Technology, Pantnagar 263145, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7464-8377","authenticated-orcid":false,"given":"Alban","family":"Kuriqi","sequence":"additional","affiliation":[{"name":"CERIS, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal"},{"name":"Civil Engineering Department, University for Business and Technology, 10000 Pristina, Kosovo"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/S0034-4257(97)00112-0","article-title":"A Comparison of Four Algorithms for Change Detection in an Urban Environment","volume":"63","author":"Ridd","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2273","DOI":"10.4319\/lo.2009.54.6_part_2.2273","article-title":"Lakes and reservoirs as sentinels, integrators, and regulators of climate change","volume":"54","author":"Williamson","year":"2009","journal-title":"Limnol. Oceanogr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2015.10.014","article-title":"Development of a global ~90m water body map using multi-temporal Landsat images","volume":"171","author":"Yamazaki","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_4","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 ob-servations between 2000 and 2010","volume":"121","author":"Feng","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5067","DOI":"10.3390\/rs6065067","article-title":"An Automated Method for Extracting Rivers and Lakes from Landsat Imagery","volume":"6","author":"Jiang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1080\/2150704X.2014.1002945","article-title":"Results of the Global WaterPack: A novel product to assess inland water body dynamics on a daily basis","volume":"6","author":"Klein","year":"2015","journal-title":"Remote Sens. Lett."},{"key":"ref_7","first-page":"428","article-title":"Water body mapping method with HJ-1A\/B satellite imagery","volume":"13","author":"Lu","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"13763","DOI":"10.3390\/s150613763","article-title":"Classification of Potential Water Bodies Using Landsat 8 OLI and a Combination of Two Boosted Random Forest Classifiers","volume":"15","author":"Ko","year":"2015","journal-title":"Sensors"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4574","DOI":"10.1080\/01431161.2016.1217441","article-title":"Inland waterbody mapping: Towards improving discrimination and extraction of inland surface water fea-tures","volume":"37","author":"Malahlela","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1080\/22797254.2017.1297540","article-title":"Object-based water body extraction model using Sentinel-2 satellite imagery","volume":"50","author":"Kaplan","year":"2017","journal-title":"Eur. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.isprsjprs.2013.01.010","article-title":"Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011","volume":"79","author":"Tulbure","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.ecoinf.2009.09.013","article-title":"Improvements in mapping water bodies using ASTER data","volume":"5","author":"Sivanpillai","year":"2010","journal-title":"Ecol. Inform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"277","DOI":"10.2747\/1548-1603.42.4.277","article-title":"Remote Detection of Prairie Pothole Ponds in the Devils Lake Basin, North Dakota","volume":"42","author":"Sethre","year":"2005","journal-title":"GIScience Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1002\/jbio.201100066","article-title":"Hyperspectral im-aging microscopy for identification and quantitative analysis of fluorescently-labeled cells in highly autofluorescent tissue","volume":"5","author":"Leavesley","year":"2012","journal-title":"J. Biophotonics."},{"key":"ref_16","first-page":"685","article-title":"Utilization of satellite data for inventorying prairie ponds and lakes, Photogramm","volume":"42","author":"Work","year":"1976","journal-title":"Eng. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3611","DOI":"10.1080\/01431161.2016.1201228","article-title":"An index and approach for water extraction using Landsat\u2013OLI data","volume":"37","author":"Li","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhang, A., Zhang, S., Sun, G., Li, F., Fu, H., Zhao, Y., Huang, H., Cheng, J., and Wang, Z. (2019). Mapping of Coastal Cities Using Optimized Spectral\u2013Spatial Features Based Multi-Scale Superpixel Classification. Remote Sens., 11.","DOI":"10.3390\/rs11090998"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","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_21","doi-asserted-by":"crossref","first-page":"4173","DOI":"10.3390\/rs6054173","article-title":"Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery","volume":"6","author":"Rokni","year":"2014","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"9097","DOI":"10.1109\/JSTARS.2014.2387196","article-title":"A simple enhanced water index (EWI) for present surface water estimation using Landsat data","volume":"8","author":"Wang","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"775","DOI":"10.20546\/ijcmas.2019.805.092","article-title":"Remote Sensing and GIS Approach for Spatiotemporal Mapping of Ramganga Reservoir","volume":"8","author":"Deoli","year":"2019","journal-title":"Int. J. Curr. Microbiol. Appl. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3153","DOI":"10.1080\/01431160500309934","article-title":"A water index for rapid mapping of shoreline changes of five East African Rift Valley lakes: An em-pirical analysis using Landsat TM and ETM+ data","volume":"27","author":"Ouma","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2619","DOI":"10.1016\/j.proenv.2011.09.407","article-title":"Water Body Extraction Methods Study Based on RS and GIS","volume":"10","author":"Haibo","year":"2011","journal-title":"Procedia Environ. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Tang, Z., Ou, W., Dai, Y., and Xin, Y. (2012). Extraction of Water Body Based on LandSat TM5 Imagery\u2014A Case Study in the Yangtze River. International Conference on Computer and Computing Technologies in Agriculture, Springer.","DOI":"10.1007\/978-3-642-36137-1_48"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1080\/10095020.2015.1017911","article-title":"Comparison of surface water extraction performances of different classic water indices using OLI and TM imageries in different situations","volume":"18","author":"Zhai","year":"2015","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_28","first-page":"275","article-title":"Performances Evaluation of Water Body Extraction Techniques Using Landsat ETM+ Data: Case- Study of Lake Nubia, Sudan","volume":"19","author":"Elsahabi","year":"2016","journal-title":"Egypt. J. Eng. Sci. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5430","DOI":"10.1080\/01431161.2017.1341667","article-title":"A weighted normalized difference water index for water extraction using Landsat imagery","volume":"38","author":"Guo","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"026016","DOI":"10.1117\/1.JRS.11.026016","article-title":"Evaluation of automated urban surface water extraction from Sentinel-2A imagery using different water indices","volume":"11","author":"Yang","year":"2017","journal-title":"J. Appl. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.isprsjprs.2018.08.014","article-title":"An automated mathematical morphology driven algorithm for water body extraction from remotely sensed images","volume":"146","author":"Rishikeshan","year":"2018","journal-title":"ISPRS J. Photogramm."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"195","DOI":"10.18280\/ts.370205","article-title":"A Novel Image Fusion Method for Water Body Extraction Based on Optimal Band Combi-nation","volume":"37","author":"Xiao","year":"2020","journal-title":"Trait. Signal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"126644","DOI":"10.1016\/j.jhydrol.2021.126644","article-title":"Mapping inter- and intra-annual dynamics in water surface area of the Tonle Sap Lake with Landsat time-series and water level data","volume":"601","author":"Gu","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12665-020-09220-y","article-title":"Assessment of human-induced environmental disaster in the Aral Sea using Landsat satellite images","volume":"79","author":"Deliry","year":"2020","journal-title":"Environ. Earth Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"063609","DOI":"10.1117\/1.JRS.6.063609","article-title":"Estimating surface water area changes using time-series Landsat data in the Qingjiang River Basin, China","volume":"6","author":"Du","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.jtusci.2016.04.005","article-title":"Water body extraction and change detection using time series: A case study of Lake Burdur, Turkey","volume":"11","author":"Sarp","year":"2017","journal-title":"J. Taibah Univ. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.catena.2019.02.020","article-title":"Dynamic detection of water surface area of Ebinur Lake using multi-source satellite data (Landsat and Senti-nel-1A) and its responses to changing environment","volume":"177","author":"Wang","year":"2019","journal-title":"Catena"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Herndon, K., Muench, R., Cherrington, E., and Griffin, R. (2020). An Assessment of Surface Water Detection Methods for Water Resource Management in the Nigerien Sahel. Sensors, 20.","DOI":"10.3390\/s20020431"},{"key":"ref_39","unstructured":"Acharya, T.D., Yang, I.T., Subedi, A., and Lee, D.H. (2016). Change Detection of Lakes in Pokhara, Nepal Using Landsat Data. Multidiscip. Digit. Publ. Inst. Proc., 1."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"238","DOI":"10.2166\/wcc.2019.078","article-title":"A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)","volume":"12","author":"Babaei","year":"2019","journal-title":"J. Water Clim. Chang."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"100346","DOI":"10.1016\/j.ancene.2022.100346","article-title":"Changes in extent of open-surface water bodies in China\u2019s Yellow River Basin (2000\u20132020) using Google Earth Engine cloud platform","volume":"39","author":"Cao","year":"2022","journal-title":"Anthropocene"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"108993","DOI":"10.1016\/j.ecolind.2022.108993","article-title":"Tracing surface water change from 1990 to 2020 in China\u2019s Shandong Province using Landsat series images","volume":"140","author":"Xing","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1080\/22797254.2022.2062054","article-title":"A new method for surface water extraction using multi-temporal Landsat 8 images based on maximum entropy model","volume":"55","author":"Li","year":"2022","journal-title":"Eur. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1007\/s10040-008-0295-0","article-title":"Lake bank filtration at Nainital, India: Water-quality evaluation","volume":"16","author":"Dash","year":"2008","journal-title":"Appl. Hydrogeol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.jrmge.2017.09.011","article-title":"Hill slope instability of Nainital City, Kumaun Lesser Himalaya, Uttarakhand, India","volume":"10","author":"Sah","year":"2018","journal-title":"J. Rock Mech. Geotech. Eng."},{"key":"ref_46","first-page":"245","article-title":"Non-parametric tests against trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econ. J. Econ. Soc."},{"key":"ref_47","unstructured":"Kendall, M.G. (1975). Rank correlation methods. Charles Griffin., 202."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1111\/j.1467-9671.2011.01280.x","article-title":"A Contextual Mann-Kendall Approach for the Assessment of Trend Significance in Image Time Series","volume":"15","author":"Neeti","year":"2011","journal-title":"Trans. GIS"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1270","DOI":"10.1080\/19475705.2022.2070552","article-title":"Assessment of spatio-temporal trends of satellite-based aerosol optical depth using Mann\u2013Kendall test and Sen\u2019s slope estimator model","volume":"13","author":"Mohammad","year":"2022","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.atmosres.2013.10.024","article-title":"Spatial and temporal trends of mean and extreme rainfall and temperature for the 33 urban centers of the arid and semi-arid state of Rajasthan, India","volume":"138","author":"Pingale","year":"2014","journal-title":"Atmos. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s12594-019-1308-4","article-title":"Analysis and Prediction of Groundwater Level Trends Using Four Variations of Mann Kendall Tests and ARIMA Modelling","volume":"94","author":"Kumar","year":"2019","journal-title":"J. Geol. Soc. India"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.1007\/s11600-020-00475-4","article-title":"Seasonality shift and streamflow flow variability trends in central India","volume":"68","author":"Kuriqi","year":"2020","journal-title":"Acta Geophys."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12517-022-09883-w","article-title":"Detection of abrupt change in trends of rainfall and rainy day\u2019s pattern of Uttarakhand","volume":"15","author":"Rana","year":"2022","journal-title":"Arab. J. Geosci."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1007\/s00704-015-1390-5","article-title":"Analysis of trends in streamflow and its linkages with rainfall and anthropogenic factors in Gomti River basin of North India","volume":"123","author":"Abeysingha","year":"2015","journal-title":"Arch. Meteorol. Geophys. Bioclimatol. Ser. B"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1538","DOI":"10.1002\/joc.2001","article-title":"Trend analysis of annual and seasonal rainfall time series in the Mediterranean area","volume":"30","author":"Longobardi","year":"2010","journal-title":"Int. J. Climatol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.jhydrol.2014.03.005","article-title":"Comparison of Mann\u2013Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey","volume":"513","author":"Kisi","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_57","first-page":"1429","article-title":"Application of Water Indices in Surface Water Change Detection Using Landsat Imagery in Nepal","volume":"31","author":"Acharya","year":"2019","journal-title":"Sens. Mater."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"5530","DOI":"10.3390\/rs5115530","article-title":"A Comparison of Land Surface Water Mapping Using the Normalized Difference Water Index from TM, ETM+ and ALI","volume":"5","author":"Li","year":"2013","journal-title":"Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12517-021-08597-9","article-title":"Water spread mapping of multiple lakes using remote sensing and satellite data","volume":"14","author":"Deoli","year":"2021","journal-title":"Arab. J. Geosci."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1016\/j.protcy.2016.02.001","article-title":"Performances Evaluation of Surface Water Areas Extraction Techniques Using Landsat ETM+ Data: Case Study Aswan High Dam Lake (AHDL)","volume":"22","author":"Elsahabi","year":"2016","journal-title":"Procedia Technol."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Bijeesh, T.V., and Narasimhamurthy, K.N. (2019, January 1\u20132). A comparative study of spectral indices for surface water delineation using Landsat 8 Images. Proceedings of the 2019 International Conference on Data Science and Communication (IconDSC), Bangalore, India.","DOI":"10.1109\/IconDSC.2019.8816929"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/18\/6827\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:28:17Z","timestamp":1760142497000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/18\/6827"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,9]]},"references-count":61,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2022,9]]}},"alternative-id":["s22186827"],"URL":"https:\/\/doi.org\/10.3390\/s22186827","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,9]]}}}