Data sources

The purpose of modeling is to provide accurate and meaningful representations of system behavior in specific scenarios. But, the outputs of these models are only accurate and meaningful when fed by quality data. Quality data can make or break the accuracy of modeling and simulation.

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In order to set up the model for particular spatial area, we need the best available data. 

In the table below we summarize the data sources that we use when setting up the models in NIBIO.

In the table one can find both:

 - data sources  specific for Norwegian case studies (marked in blue)

 - data sources providing wordwide data.

 

Table is under development (current version 2023.12.13)

Data

Source

Comments

General spatial settings

Matrikkelen-Eiendomskart Teig (DEK)

 

Field/farm borders

Geonorge.no

 

(SOSI format)

Matrikkelen-Eiendomskart Teig contains an extract of property information that is registered in Matrikkelen, Norway's official register of real estate. The data set contains teigers (delimited areas/plots) with information about which property (cadastral unit) they belong to. The cadastral number (municipal number-farm number/use number (DEK), possibly attachment number, section number) identifies the property and belongs to the cadastral unit data type.

Maps of catchment borders

Water regions

Vannområde

 

Location of CW

Water regions

Vannområde

 

FKB-Vann

Geonorge.no

FKB-Vann escribes the geographical location, course and form of streams, rivers, canals, ditches, lakes, glaciers and the topographical part of the coast and sea.

Maps with land use and land cover

 

Geonorge.no

NIBIO

 

AR5 is a detailed land resource map adapted to a scale of 1:1000 and up. The map is part of the joint map database (FKB-AR5) which contains detailed map data for Norway and is managed by the Geovekstsambarbeid

ESRI land cover data

This land cover data is created by artificial intelligence methods and large amounts of a training dataset which has billions of labeled pixels. ESRI land cover data is available for the year of 2022. This land cover data is produced by using Sentinel-2 10 m time series satellite imagery.

 

Lakes polygons - HydroSHEDS

The “HydroSHEDS” website is the place where we acquire lake polygons in global scale. HydroLAKES database provides lake borders with at least 10 ha area. This database “encompasses 1.4 million individual lakes or reservoirs representing a total surface area of 2.67 million km², a total shoreline length of 7.2 million km, and a total storage volume of 181,900 km³”. The data should be clipped by borders of study area.

Information about measures (eStill)

Landbruksdirektoratet

 

Information about the measures that were subsidised. We get them through application for production subsidy and RMP subsidy (via eStil)

(updated yearly)

 

Contact in NIBIO: Sigrun Kværnø (Soil and Land use section)

 

Soil maps

NIBIO

 

 

 

 

 

 

Soil map with information on soil type and slope planning, and maps with continuous values for erosion risk during autumn plowing ("EHP")

 

Contact in NIBIO:

Sigrun Kværnø (Soil and Land use section);

Division of survey and statistics

European soil data base v2.0

(vector and attribute data), published in 2001

 

The most appropriate data for European countries unless there is no local level soil data. This database has soil geographical database with several essential attributes.

NOTE: This database has coarse spatial resolution in Norway but still the only alternative. Higher resolution soil data is available only for agricultural areas in Norway.

DEM

LIDAR data

Contact in NIBIO: Robert Barneveld (Soil and Land use section)

Space Shuttle Radar Topography Mission (SRTM)

ASTER Global Digital Elevation Model (GDEM)

The most used DEM data which are available for the entire world. Both of these data have 30-meter spatial resolution, and this is the highest resolution freely available on the internet unless there is no local DEM data with higher resolution.

 

 

 

Meteorological data

Temp

Precipitation

Surface net solar radiation

10m u-component of wind

10m v-component of wind

MetNO

 

European Centre for Medium-Range Weather Forecasts (ECMWF)

Both re-analysis and ensemble mean data is available in hourly time format. Users must select days of months and hours of a day along with entering latitude-longitude information. The data comes in a “.txt” file and correct lines should be selected carefully. Also, units of specific data should be considered, and necessary conversions must be made. For example, temperature data must be converted from Kelvin to Celsius.

 

 

 

 

 

 

Field/farm data

Farm management

JOVA

Contact in NIBIO: Hans Olaf (Soil and Land use section)