    {"datasetrec":{"DasID":8887,"Acronym":null,"StandardTitle":"Integrated Dataset of Hydrological, Meteorological Parameters, Remote Sensing Chlorophyll-a, and Coastal Visitor Metrics (public transportation by bus and ferry and car parking) in Klaipėda, Lithuania (2020–2023)","OrigTitle":null,"OrigTitleLangID":null,"OrigTitleLangCode":null,"OrigTitleLang":null,"OrigTitleLangNL":null,"VersionName":null,"ContactEmail":"klaipeda.university@ku.lt","VersionDate":null,"VersionDay":null,"VersionMonth":null,"VersionYear":null,"SizeReference":null,"EngAbstract":"<p>This dataset contains integrated daily environmental and visitation data for two beaches (Melnragė and Smiltynė) in Klaipėda, Lithuania, covering the period 2020–2023. It includes satellite-derived chlorophyll-a concentrations, weather data (temperature, wind speed, and binary indicators for rain, snow, fog, thunder, and hail), and calendar variables (year, month, day, weekday, public holidays, and bridge days). Beach visitation information includes visitation counts from car, bus, and ferry, car parking hours and payments. The dataset supports analysis of the impact of weather conditions and water quality on coastal tourism in a Baltic Sea context.</p>","EngDescr":"<p>&nbsp;This dataset provides a comprehensive, daily-resolution record of environmental, mobility, and tourism-related variables from the coastal city of Klaipėda, Lithuania, covering the period from January 1, 2020 to December 31, 2023. It was created to support interdisciplinary research on the interactions between coastal environmental conditions, and beach visitors dynamics in the Baltic Sea region. The dataset was compiled by researchers at Klaipėda University and Trento University (Italy) in collaboration with local municipal and transport authorities, remote sensing data providers, and weather data sources. The main purpose of the dataset is to enable the analysis of coastal ecosystem services, urban mobility patterns, and the potential effects of meteorological and marine conditions on recreational behavior. 1. Dataset Contents The dataset includes the following main categories of variables: A. Remote Sensing Data (Chlorophyll-a):CHL_Melnrage and CHL_Smiltyne: Daily satellite-derived chlorophyll-a concentration (Chl-a, mg/m³) estimates for two key beaches — Melnragė and Smiltynė — obtained from remote sensing products E.U. Copernicus Marine Service Information; https://doi.org/10.48670/moi-00296 B. Model derived values of surface sea water temperature and salinity (in Smiltyne and Melnrage beaches) B. Meteorological Data: These variables were manually extracted from the Freemeteo website using the daily archive view for Klaipėda. At the time of data collection (2020–2023), the Freemeteo platform provided historical weather data tables in a tabular format, broken down by location and date. Since Freemeteo is not an official national meteorological agency, the data may differ slightly from sources like the Lithuanian Hydrometeorological Service (LHMT).tempmin, tempmax: Daily minimum and maximum air temperatures (°C). wind: Average daily wind speed (m/s).Binary indicators for presence of:raindummysnowdummythunderdummyfogdummyhaildummyFreemeteo Weather Service. Weather Data for Klaipėda. Available online: https://www.freemeteo.lt/ (Accessed between 2020–2023). C. Temporal Variables: date, year, month, day, weekday: Standard calendar breakdown.holiday: Indicates whether the day was a national holiday.bridge: Indicates a \"bridge day\" (a non-working day between a holiday and weekend, often used for extended recreation). D. Mobility and Transport Data: vis_car: Estimated number of cars at the Melnrangė parking slot (Parking lot, Kopų g. 2, Klaipėda, 92277 Klaipėdos m. municipality.) as indicator of beach visitors arriving by car.totpayment_car and totaltime: Total parking meter payments and cumulative parking time, derived from parking infrastructure.parkingmetercode and paidtime: Parking meter usage data including meter identifiers and time purchased.E. Public Transport:vis_bus, lnvis_bus: Total daily number of bus passengers traveling to Melnrage I beach area; log-transformed version included for modeling.Busstop_167, Busstop_3850: Daily passenger counts at two specific bus stops near beach areas.F. Ferry Transport:vis_ferry, lnvis_ferry: Daily number of passengers using the Klaipėda–Smiltynė ferry route; log-transformed version also provided.vis_passangersnew, vis_passangersold: Split passenger counts by ferry type or terminal (based on data source distinction). 2. Data Collection and ProcessingChlorophyll-a data were processed using Baltic Sea Multiyear Ocean Colour Plankton, Reflectances and Transparency L3 daily observations ocean color products with atmospheric corrections, spatially averaged over 1x1km approximately covering beach locations in Melnrage 55.7369537 N 21.0825863 E and Smiltynė 55.7014885 N 21.0947247 E . Modeled sea water surface salinity and temperature values were derived at the same locations using Operational hydrodynamic model for the Curonian Lagoon and the southeastern Baltic Sea (OPER-LIT). Meteorological data were cleaned and aligned to match daily intervals, using binary indicators for precipitation and extreme weather events. Mobility data were obtained from municipal parking services (electronic meters), Klaipėda public transport agency, and ferry operators (Smiltynės perkėla). Visitor estimates by transport mode (car, bus, ferry) were cross-referenced with mobility records and observational sampling when available. 3. Purpose and Use Cases The dataset is designed to enable: Analysis of how environmental conditions affect recreational behavior. Modelling of coastal tourism flows under changing climate or policy scenarios.The dataset is designed to enable: Assessment of chlorophyll-a dynamics near urban beaches and its relationship with human activity.Support for sustainable mobility planning in coastal urban areas.&nbsp;</p>","OrigAbstract":null,"OrigDescr":null,"Comments":null,"ReleaseDate":null,"ReleaseDate0":null,"OrigDescrLang":null,"EmbargoDate":"2031-08-30","OrigDescrLangNL":null,"OrigLangCode":null,"OrigLangCodeExtended":null,"OrigLangID":null,"DescrCompFlag":null,"DescrTransFlag":null,"Citation":"Lesutiene J., Zhang N. Fezzi C. (2025) Integrated Dataset of Hydrological, Meteorological Parameters, Remote Sensing Chlorophyll-a, and Coastal Visitor Metrics (public transportation by bus and ferry and car parking) in Klaipėda, Lithuania (2020–2023). 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This discipline encompasses studies on the prediction of usage demand in future travel and the planning to ensure the necessary facilities and services to cater to that demand.","OrigThesTerm":"Transport planning","DutchTerm":"Transportplanning","URI":null,"DasKeywordDescr":null},{"ThesaurusTerm":"Urban transportation","ThesTypID":2,"ThesType":"CSA Technology Research Database Master Thesaurus","Code":null,"Description":null,"OrigThesTerm":"Urban transportation","DutchTerm":null,"URI":null,"DasKeywordDescr":null}],"parents":null,"children":null,"othrel":null,"othrelrev":null,"ownerships":[{"OrderNr":2,"Surname":"Lesutiene","Firstname":"Jurate","Initials":"J.","PerPublicFlag":1,"AdrID":null,"Email":null,"InsPublicFlag":1,"Acronym":null,"OrigNameLangCode":null,"OrigNameLangID":null,"FullOrigName":null,"InsOwnerCNT":2,"PersID":8418,"InsID":14624,"FullInstitute":"Klaipeda University; Marine research institute","RoleID":61,"Role":"Data creator","OrigName":null,"StandardName":"Marine research institute","FullAcronym":null,"ORC":null,"ROR":null},{"OrderNr":3,"Surname":"Zhang","Firstname":"Nan","Initials":null,"PerPublicFlag":1,"AdrID":170831,"Email":null,"InsPublicFlag":1,"Acronym":null,"OrigNameLangCode":null,"OrigNameLangID":null,"FullOrigName":null,"InsOwnerCNT":2,"PersID":45977,"InsID":14106,"FullInstitute":"University of Trento","RoleID":61,"Role":"Data creator","OrigName":null,"StandardName":"University of Trento","FullAcronym":null,"ORC":null,"ROR":null},{"OrderNr":4,"Surname":"Fezzi","Firstname":"Carlo","Initials":null,"PerPublicFlag":1,"AdrID":170830,"Email":null,"InsPublicFlag":1,"Acronym":null,"OrigNameLangCode":null,"OrigNameLangID":null,"FullOrigName":null,"InsOwnerCNT":2,"PersID":45976,"InsID":14106,"FullInstitute":"University of Trento","RoleID":61,"Role":"Data creator","OrigName":null,"StandardName":"University of Trento","FullAcronym":null,"ORC":null,"ROR":null}],"taxterms":null,"frameworks":null,"otherterms":[{"OtherTerm":"Coastal tourism"},{"OtherTerm":"Integrated coastal zone management"},{"OtherTerm":"Research: Remote sensing"}],"temporal":[{"DasDateID":6446,"StartYear":2020,"EndYear":2023,"StartDay":1,"EndDay":31,"StartDate":"2020-01-01","EndDate":"2023-12-31","DasDate":null,"Resolution":null,"ResolutionNL":null,"Notes":null,"StartMonth0":1,"StartMonth":"January","StartMonthNL":"Januari","EndMonth0":12,"EndMonth":"December","EndMonthNL":"December","Progress":null,"ProgressNL":null}],"geographical":[{"GeoTerm":"Lithuanian Coast","DasGeoID":15078,"DasGeoTerm":"Melnragė and Smiltynė beaches","DasID":8887,"GeotID":9641,"X":null,"Y":null,"MaxX":null,"MaxY":null,"StationName":null,"Precision":null,"CoordSystID":null,"GeoDatumID":null,"OrigCoordMinX":null,"OrigCoordMinY":null,"OrigCoordMaxX":null,"OrigCoordMaxY":null,"OrderNr":null,"Projection":null,"GeoDatum":null,"GeoObjectID":50284,"OrigGeoTerm":"Lithuanian Coast","DutchTerm":null}],"meastypes":null,"dasthemes":null,"projects":[{"ProID":5393,"Acronym":"MARBEFES","Progress":"In Progress","StandardTitle":"MARine Biodiversity and Ecosystem Functioning leading to Ecosystem Services","FP7Code":null,"GrantDOI":null,"FunderID":"101060937","FunderIDType":"EU contract id","FunderCodes":["Horizon Europe"]}],"refs":null,"urls":[],"pictures":null,"urlmaps":null,"spatreps":null,"fileformats":null,"resmessage":"","complete":1}
