Belgif Linked Data Fragments server

Matches in Data.gov.be for { <https://www.dov.vlaanderen.be/dataset/127c3b51-d606-47f8-8c35-df7301b35ca2> ?p ?o ?g. }

• 127c3b51-d606-47f8-8c35-df7301b35ca2 accessRights PUBLIC @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 accrualPeriodicity IRREG @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 conformsTo 31370 @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 created "2017-12-06" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 description "Die belgische Bestandsaufnahme des organischen Kohlenstoffs (SOC) für Oberböden (0-30 cm) mit einer Auflösung von 40 m x 40 m bestand aus zwei regionalen SOC-Bestandskarten. Für die Regionalkarten wurde ein anderer Ansatz für landwirtschaftliche Flächen als für Wälder verwendet. Die Karten basieren auf digitalen Bodenkartierungskonzepten mit empirischen Modellen, die für PREDICT den SOC-Bestand kalibriert sind, und anhand von Kovariaten, die auf regionaler Ebene in ausreichender Auflösung verfügbar sind. Alle Karten sind stark von der belgischen Bodenkarte (Textur- und Entwässerungsparameter) abhängig. Die regionalen Karten wurden mit einer Feinauflösung (10 m x 10 m Rasterzellen für Flandern und 40 m x 40 m für Wallonien) gemeldet. Anschließend wurden sie angeschlossen (40 m x 40 m Rasterzellen). Die Regionalkarten für Flandern wurden auf das wallonische Netz von 40 m x 40 m ausgeweitet. Geben Sie die unterschiedliche Herkunft der einzelnen Karten und die Unsicherheitsunterschiede zwischen den Karten an. So wurde beispielsweise eine Karte des 90 %-Konfidenzintervalls der SOC-Bestände für landwirtschaftliche Böden in Wallonien auf der Grundlage eines Monte-Carlo-Ansatzes unter Berücksichtigung der Mess- und Modellunregelmäßigkeiten erstellt. Bei flämischen Waldböden waren räumliche und analytische Unregelmäßigkeiten mithilfe von Bootstrapping-Techniken zu berücksichtigen. Bei flämischen landwirtschaftlichen Böden handelt es sich bei der gemeldeten Unsicherheit um die Modellunsicherheit bei Punktschätzungen für jeden Datenpunkt, in dem die geschätzten Modellparameter unter Verwendung ihrer Modellschätzung und des Standardfehlers als Verteilungsparameter 1000-mal als unabhängige normale verteilte Varianten simuliert werden. Für die Umwandlungsfunktionen, bei denen die stochastischen Variablen „Massendichte“ verwendet werden, werden keine zusätzlichen Unsicherheiten berücksichtigt. Die Metadaten sind verfügbar und bewerten die Unempfänglichkeiten der Bestandsschätzungen in den verschiedenen Komponentenkarten. Die SOC-Bestandskarte (Auflösung von 40 m x 40 m) ist die erste umfassende Karte für Belgien unter Einbeziehung von Grünland, Ackerland und Wäldern. Auf der Grundlage dieser Karte wurde eine weitere SOC-Bestandskarte mit einer Auflösung von 1 km x 1 km im koordinierten Referenzsystem WGS84 erstellt." @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 description "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) at the resolution of 40m x 40m was composed of 2 regional SOC stock maps. For the regional maps a different approach was used for agricultural land as compared to forest. The maps are based on digital soil mapping approaches using empirical models calibrated to predict the SOC stock and using covariates that are available at a sufficient resolution at the regional scale. All maps are strongly dependent on the Belgian Soil Map (texture and drainage parameters). The regional maps were compiled at a fine resolution (10m x 10m grid cells for Flanders and 40m x 40m grid cells for Wallonia). Next they were joined (40m x 40m grid cells). The regional maps for Flanders were scaled up tot the 40m x 40m grid of Wallonia. Given the different origin of the individual maps, the uncertainty varies between maps. For instance, a map of the 90% confidence interval of the SOC stocks was produced for agricultural soils in Wallonia based on a Monte Carlo Approach taking into account both the measurement and the model uncertainties. For Flemish forest soils, spatial and analytical uncertainties were taken into account using bootstrapping techniques. For Flemish agricultural soils, the uncertainty reported is the model uncertainty on point estimates for each data point, in which the estimated model parameters are simulated 1000 times as being independent normal distributed variables using their model estimation and standard error as distribution parameters. No additional uncertainty is taken into account for the conversion functions that use the stochastic variables "bulk density". The metadata are available and allow assessing the uncertainties of the stock estimates in the different component maps. The SOC stock map (resolution of 40m x 40m) is the first comprehensive map for Belgium integrating grasslands, croplands and forests. Based on this map another SOC stock map at a resolution of 1km x 1km in the coordinate reference system WGS84 was created." @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 description "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) at the resolution of 40 m x 40 m is composed of 2 regional SOC stock maps. For the regional maps a different approach is used for agricultural land as compared to forest. The maps are based on digital soil mapping approaches using empirical models Calibrated to PREDICT the SOC stock and using codeltes that are available at a sufficient resolution at the regional scale. All maps are strongly dependent on the Belgian Soil Map (paramètres textiles et drainage). The regional maps tere compiled at a fine resolution (10 m x 10 m grid cells for Flanders and 40 m x 40 m grid cells for Wallonia). Next they were joined (40 m x 40 m grid cells). The regional maps for Flanders tere scaled up jusque 40 m x 40 m grid of Wallonia. Given the different origin of the individual maps, the unerinty varies between maps. For instance, a map of the 90 % confidence interval of the SOC stocks is produced for agricultural soils in Wallonia based on a Monte Carlo Approach taking into account both the measurement and the model undinties. Pour Flemish forest soils, géographial et analytical unstrappels tâches into account using bootstrapping techniques. Pour Flemish agricultural soils, the undinty reported is the model undinty on point estimates for each data point, in which the estimated model paramparameters are Simulated 1000 times as being independent normal variables using their model estimation and standard error as distribution paramètres. No additional undinty est des tâches into account for the conversion functions that use the Stochastic variables «bulk density». The metadata are available and allow assessing the inties of the stock estimates in the different composante maps. The SOC stock map (Résolution of 40 m x 40 m) is the first comprehensive map for Belgium integrating grasslands, croplands and forests. Based on this map another SOC stock map at a resolution of 1 km x 1 km dans le système de référence coordonné WGS84 était créated." @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 description "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) at the resolution of 40 m x 40 m was composed of 2 regional SOC stock maps. For the regional maps a different approach was used for agricultural land as compared to forest. The maps are based on digital soil mapping approaches using empirical models Calibrated to PREDICT the SOC stock and using covariates that are available at a sufficient resolution at the regional scale. All maps are strongly dependent on the Belgian Soil Map (Texture and drainage parameters). The regional maps were reported at a fine resolution (10 m x 10 m grid cells for Flanders and 40 m x 40 m grid cells for Wallonia). Next they were joined (40 m x 40 m grid cells). The regional maps for Flanders were scaled up to the 40 m x 40 m grid of Wallonia. Provide the different origin of the individual maps, the uncertainty variations between maps. For instance, a map of the 90 % confidence interval of the SOC stocks was produced for agricultural soils in Wallonia based on a Monte Carlo Approach taking into account the measurement and the model irregularities. For Flemish forest soils, spatial and analytical irregularities were tasks into account using bootstrapping techniques. For Flemish agricultural soils, the uncertainty reported is the model uncertainty on point estimates for each data point, in which the estimated model parameters are Simulated 1000 times as being independent normal distributed variations using their model estimation and standard error as distribution parameters. No additional uncertainty is tasks into account for the conversion functions that use the Stochastic variables ‘bulk density’. The metadata are available and assess the unperceptions of the stock estimates in the different component maps. The SOC stock map (resolution of 40 m x 40 m) is the first comprehensive map for Belgium integrating grassland, croplands and forests. Based on this map another SOC stock map at a resolution of 1 km x 1 km in the coordinated reference system WGS84 was created." @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 identifier "127c3b51-d606-47f8-8c35-df7301b35ca2" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 issued "2018-01-15" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 language NLD @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 provenance lineage @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 publisher 2143719695 @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 rightsHolder d285b3bd51c44c26b14412790fe151b4629-5b75d2343afb7c60 @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 rightsHolder 2199336923 @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 spatial 3337388 @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 subject regional @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 subject so @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 temporal genid34279 @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 title "Karten der organischen Kohlenstoffbestände im Boden für Belgien: Mittelwert (40 m Raster)" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 title "Soil Organic Carbon Stock Maps for Belgium: Mean (40 m grid)" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 title "Soil Organic Carbon Stock Maps for Belgium: Mean (grid 40 m)" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 title "Soil Organic Carbon Stock Maps for Belgium: mean (40 m grid)" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 type Dataset @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 versionInfo "2017" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 sample d285b3bd51c44c26b14412790fe151b4629-5b75d2343afb7c78 @default.
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• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "DOV" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "Databank Ondergrond Vlaanderen" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "Departement Omgeving" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "Ondergrond" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "Vlaanderen" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "akker" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "bos" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "grasland" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "koolstof" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "landbouw" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "ondergrond" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 keyword "totaal aan organische koolstof" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 landingPage bf8c35ad-ab45-4084-b1e1-3042c66204aa @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 spatialResolutionInMeters "40.00" @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 theme AGRI @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 theme REGI @default.
• 127c3b51-d606-47f8-8c35-df7301b35ca2 theme TECH @default.