Type
 

dataset

252 record(s)
 
Type of resources
Available actions
Topics
INSPIRE themes
federalThemes
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Scale
Resolution
From 1 - 10 / 252
  • Mean key indicators on future climate for Belgium for precipitation, temperature, relative humidity, wind speed, global solar radiation and potential evapotranspiration (spatial distributions are available through the WMS view service). The key indicators are derived from a multi-model ensemble of climate change signals or factors for a mean and high impact scenario (corresponding to respectively the 50th, and 5th or 95th percentile of the change factors), and for multiple future target years (2030, 2050, 2085, 2100).

  • The ceilometer CL51 employs a pulsed diode laser LIDAR technology, where short, powerful laser pulses are sent out in a vertical or near-vertical direction. The reflection of light (backscatter) caused by clouds, precipitation or other obscuration is analysed and used to determine the cloud base height, the cloud layer height and the amount of clouds (in octas) in different layers.

  • The number of private households according to official statistics, per administrative unit (region, province, district and municipality) for Wallonia.

  • The Solar Ultraviolet - Visible Irradiance Monitoring network (SUVIM) is formed of observation stations operated by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA). At each station, UV solar radiation is measured by several instruments. The network produces UV indices, solar irradiances and ancillary measurements such as meteorological conditions at the stations in quasi-real time. The SUVIM Station Network dataset includes information on the stations. It does not include the measured data, which form the SUVIM Observations dataset.

  • Real estate sales - Profile of the buyers corresponds to the dataset describing the profile of the buyers (natural persons) of real estate. This dataset is composed of seven classes. The first class shows, at the national level, for each cadastral nature and by price range the number of real estate property that was sold as well as the number of buyers broken down by age and gender categories. The second class includes this information at the level of the three regions. The following classes do the same at the level of provinces, arrondissements, municipalities, cadastral divisions and statistical sectors. The dataset can be freely downloaded as a zipped CSV.

  • The product is made of 6 "high resolution layers" covering all the Belgian territory as part of a European-wide coverage. The 6 layers concern 6 distinct themes: Imperviousness, Tree cover density, Forest type, Permanent grasslands, Wetlands and Permanent waterbodies. The 6 layers were produced by an automatic classification based on satellite images and collateral data and achieved by private companies (EEA service providers), and they were verified and enhanced by Belgium. At the Belgian level, verification and enhancements were made by AGIV for the northern part and SPW for the southern part. The NGI coordinated the project.

  • The product is made of 5 "high resolution layers" covering all the Belgian territory as part of a European-wide coverage for the reference year 2015. The 5 layers concern 4 distinct themes: Imperviousness, Forest, Grasslands, Wetness and Water. The 5 layers were produced by an automatic classification based on satellite images and collateral data and achieved by private companies (EEA service providers), and they were verified by Belgium. At the Belgian level, verification and enhancements were made by IV for the northern part and SPW for the outhern part. The NGI coordinated the project. Data was produced with funding by the European Union. Copyright Copernicus Programme DISCLAIMER: National Geographic Institute has undertaken to distribute the data on behalf of EEA under Specific Contract No 3436/R0-Copernicus/EEA.57005 implementing Framework service contract No EEA/IDM/R0/16/009/Belgium. National Geographic Institute accepts no responsibility or liability whatsoever with regard to the content and use of these data.” The European Environment Agency accepts no responsibility or liability whatsoever with regard to the information on this site and the information does not necessarily reflect the official opinion of the EEA or other European Communities bodies and institutions.

  • Characteristics of cadastral parcels - Concentration of cadastral income corresponds to the dataset measuring the concentration of cadastral income for parcels of a housing-like nature. This dataset is composed of seven classes. The first class shows, at the national level, for each category of parcels dedicated to housing, the number of parcels and the total cadastral income of the parcels by cadastral income bracket. The second class includes this information at the level of the three regions. The following classes do the same at the level of provinces, arrondissements, municipalities, cadastral divisions and statistical sectors. The dataset can be freely downloaded as a zipped CSV.

  • Vector dataset of aeronautical obstacles with a height of 60 meters or more above the ground. The update of this dataset takes place on a multi-year cycle; for each obstacle and for each location, the situation is indicated as applicable at the time of its last update. Based on the horizontal range of an obstacle, it is classified into one of three classes: polygonal obstacle if the smallest rectangular area enclosing the obstacle has a length and width of more than 100 meters; line obstacle if the smallest rectangular area enclosing the obstacle has a length of more than 100 meters, but a width of less than 100 meters; point obstruction in other cases.

  • DSM 1m is a homogeneous and regular point grid indicating the height of the Earth’s surface level in order to model its landscape. DSM 1m is achieved by interpolating in Lambert 2008 source data in Lambert 72 and at a 1m-resolution from the Flemish and Brussels Regions, and by adding Lambert 2008 data at 1m-resolution from the Walloon Region.