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        <r:String xml:lang="sv">Automatisk detektion av diken och vattendrag från digitala höjdmodeller med hjälp av djupinlärning</r:String>
        <r:String xml:lang="en">Automatic Detection of Ditches and Natural Streams from Digital Elevation Models Using Deep Learning</r:String>
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          <r:String xml:lang="sv">Sveriges lantbruksuniversitet</r:String>
          <r:String xml:lang="en">Swedish University of Agricultural Sciences</r:String>
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          <r:String xml:lang="sv">Sveriges lantbruksuniversitet</r:String>
          <r:String xml:lang="en">Swedish University of Agricultural Sciences</r:String>
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        <r:SimpleDate>2024-03-15</r:SimpleDate>
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      <r:Content xml:lang="sv">Den här datamängden innehåller digitala höjdmodeller och polyline-shapefiler med placeringen av kanaler från de 12 studieområdena som används i denna studie. Den innehåller också koden för att generera datamängderna som används för att träna djupinlärningsmodellerna som används för att kartera kanaler, diken och vattendrag, samt beräkna topografiska index. Koden för att träna modellerna ingår också, tillsammans med modellerna med bäst prestanda i 0,5 meters upplösning. Kanalerna kartlades på olika sätt: diken digitaliserades manuellt baserat på visuell analys av vissa topografiska index och ortofoton som erhållits från en digital höjdmodell. Vattendrag kartlades genom att först upptäcka alla naturliga kanalhuvuden, sedan spåra nedströmskanalerna och slutligen redigera dem manuellt baserat på ortofoton.</r:Content>
      <r:Content xml:lang="en">This data contains the digital elevation models and polyline shapefiles with the location of channels from the 12 study areas used in this study. It also has the code to generate the datasets used to train the deep learning models to detect channels, ditches, and streams, and calculate the topographic indices. The code to train the models is also included, along with the models with the highest performance in 0.5 m resolution. The channels were mapped differently based on their type: ditches were manually digitized based on the visual analysis of some topographic indices and orthophotos obtained from the DEM. Streams were mapped by initially detecting all natural channel heads, then tracing the downstream channels, and finally manually editing them based on orthophotos.</r:Content>
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        <r:Subject xml:lang="en" controlledVocabularyID="imagery-base-maps-earth-cover" controlledVocabularyName="INSPIRE topic categories">Imagery / Base Maps / Earth Cover</r:Subject>
        <r:Subject xml:lang="sv" controlledVocabularyID="imagery-base-maps-earth-cover" controlledVocabularyName="INSPIRE topic categories">Arealtäckande bilder och bakgrundskartor</r:Subject>
        <r:Subject xml:lang="en" controlledVocabularyID="geoscientific-information" controlledVocabularyName="INSPIRE topic categories">Geoscientific Information</r:Subject>
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          <r:Content xml:lang="en">The data covers 12 study areas spread across Sweden, containing information related to channel type for small water channels. More information with the precise locations can be found at the README.html file.</r:Content>
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