Belgif Linked Data Fragments server

Matches in Data.gov.be for { <https://www.dov.vlaanderen.be/dataset/80b78280-2182-4031-ad24-2b717f110ef5> ?p ?o ?g. }

• 80b78280-2182-4031-ad24-2b717f110ef5 accessRights PUBLIC @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 accrualPeriodicity IRREG @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 conformsTo 4326 @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 created "2017-12-06" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 description "Die belgische Bestandsaufnahme des organischen Kohlenstoffs (SOC) für Oberböden (0-30 cm) 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 Regionalkarten wurden mit einer feineren Auflösung (10 m x 10 m und 40 m x 40 m Rasterzellen) erstellt. Anschließend wurden sie angeschlossen (40 m x 40 m Rasterzellen) und schließlich auf die erforderliche 1 Rasterzellen um 1 km erhöht. Dabei wurden folgende Instrumente eingesetzt: Blockstatistiken (Mittelwert), Mosaik zu einem neuen Gitter (Mittelwert), Rasterprojekt, Statistik (Mittelwert), Neustichprobe (nächste Nachbarschaft) und Projektraster. 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 SOC-Bestandskarten sind die erste umfassende Karte für Belgien unter Einbeziehung von Grünland, Ackerland und Wäldern. Dabei handelt es sich um zwei Aussagen der SOC-Bestandskarten für Belgien: (1) Auflösung von 40 m x 40 m im koordinierten Referenzsystem Lambert72 und 2) Auflösung von 1 km x 1 km im koordinierten Referenzsystem WGS84. Die Metadaten sind verfügbar und bewerten die Unempfänglichkeiten der Bestandsschätzungen in den verschiedenen Komponentenkarten." @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 description "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) 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 finer resolution (10m x 10m and 40m x 40m grid cells). Next they were joined (40m x 40m grid cells) and finally scaled up to the required 1 by 1 km grid cells. This was done using the following tools: block statistics (mean), mosaic to new raster (mean), project to raster, block statistics (mean), resample (nearest neighbour) and project raster. 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 SOC stock maps are the first comprehensive map for Belgium integrating grasslands, croplands and forests. There are two versions of the SOC stock maps for Belgium: 1) resolution of 40m x 40m in the coordinate reference system Lambert72 and 2) resolution of 1km x 1km in the coordinate reference system WGS84. The metadata are available and allow assessing the uncertainties of the stock estimates in the different component maps." @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 description "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) 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 finer resolution (10 m x 10 m and 40 m x 40 m grid cells). Next they were joined (40 m x 40 m grid cells) and finally scaled up to the required 1 by 1 km grid cells. This was done using the following tools: block statistics (mean), mosaic to new grid (mean), project to raster, block statistics (mean), resample (nearest neighbour) and project grid. 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 SOC stock maps are the first comprehensive map for Belgium integrating grassland, croplands and forests. Where are two statements of the SOC stock maps for Belgium: (1) resolution of 40 m x 40 m in the coordinated reference system Lambert72 and 2) resolution of 1 km x 1 km in the coordinated reference system WGS84. The metadata are available and assess the unperceptions of the stock estimates in the different component maps." @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 description "The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) était composé de 2 unités de stock régional SOC. 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 finer resolution (10 m x 10 m et 40 m x 40 m de cellules grides). Next they were joined (40 m x 40 m grid cells) et finally scaled up to the required 1 by 1 km grid cells. This is done using the following tools: statistiques block (mean), mosaic to new raster (mean), projet to raster, statistics block statistics (mean), resample (nearest neighbour) et grille de projet. 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 SOC stock maps are the first comprehensive map for Belgium integrating grasslands, croplands and forests. There are two versions of the SOC stock maps for Belgium: 1) résolution de 40 m x 40 m dans le système de référence coordonné Lambert72 et 2) résolution de 1 km x 1 km dans le système de référence coordonné WGS84. The metadata are available and allow assessing the inties of the stock estimates in the different composante maps." @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 identifier "80b78280-2182-4031-ad24-2b717f110ef5" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 issued "2018-01-15" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 language NLD @default.
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• 80b78280-2182-4031-ad24-2b717f110ef5 publisher 2143719695 @default.
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• 80b78280-2182-4031-ad24-2b717f110ef5 subject regional @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 subject so @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 temporal genid50145 @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 title "Karten der organischen Kohlenstoffbestände im Boden für Belgien: Mittelwert (1 km Gitter)" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 title "Soil Organic Carbon Stock Maps for Belgium: Mean (1 km de grid)" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 title "Soil Organic Carbon Stock Maps for Belgium: Mean (1 km grid)" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 title "Soil Organic Carbon Stock Maps for Belgium: mean (1 km grid)" @default.
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• 80b78280-2182-4031-ad24-2b717f110ef5 versionInfo "2017" @default.
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• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "DOV" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "Databank Ondergrond Vlaanderen" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "Departement Omgeving" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "Ondergrond" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "Vlaanderen" @default.
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• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "grasland" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "koolstof" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "landbouw" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "ondergrond" @default.
• 80b78280-2182-4031-ad24-2b717f110ef5 keyword "totaal aan organische koolstof" @default.
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• 80b78280-2182-4031-ad24-2b717f110ef5 theme TECH @default.