Buyers' origin - Legal persons corresponds to the dataset describing the origin of the buyers (legal persons) of real estate located in Belgium according to the municipality of their headquarters for legal persons settled in Belgium and according to the country or territory of their headquarters for foreign legal persons (headquarter at the date of the deed). This dataset is made up of seven classes. The first class shows, at national level, for each type of property, the total number of parcels, the number of parcels acquired by buyers from each Belgian municipality and the number of parcels acquired by buyers from each country or territory. The number of parcels takes into account the shares actually acquired. The second class shows this information at the level of the three regions. The following classes do the same at the level of provinces, arrondissements, municipalities, land register divisions and statistical sectors. The dataset is freely downloadable, in the form of zipped CSV files.

Inheritances corresponds to the dataset describing declarations of estate and the value of the assets included therein. This dataset is composed of five classes. The first class includes, at the national level, by age group, gender, and type of property, the number of deceased persons, the total value of the property, the median value of the property, the 25th and 75th percentiles of the value of the property, and the standard deviation of the value of the property. The second class includes this information at the level of the three regions. The following classes do the same at the level of provinces, districts, and municipalities. The geographical distribution is based on the deceased's tax domicile. Since January 1, 2015, the FPS Finance is no longer responsible for the estates of deceased persons with a tax domicile in Flanders. Only data for tax domiciles located in the Walloon Region and the Brussels-Capital Region are included in the dataset. The dataset can be downloaded free of charge in zipped CSV format.

The dataset shows in the form of polygons the sand and gravel extraction sites in the Belgian marine areas as defined by the successive marine spatial plans. A 2014 version illustrates the 2014-2020 plan while the 2020 version illustrates the 2020-2026 plan.

Population density and area of administrative entities (region, province, district and municipality) for Wallonia.

Owner occupants corresponds to the dataset relating to persons domiciled in a property over which they, or a member of their family, exercise a right in rem such as recorded by the FPS Finance for registration purposes. This dataset is composed of seven classes. The first class mentions, at national level, for each age-gender combination, by type of right in rem, the number of natural persons having such a right on their home. The lack of right in rem corresponds here to a fictitious right in rem in order to identify individuals who do not have rights on their home. The second class includes this information at the level of the three regions. The following classes do the same at the level of provinces, districts, municipalities, land register divisions and statistical sectors. The dataset can be freely downloaded as a zipped CSV.

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.

Distribution of real estate assets - real estate companies corresponds to the dataset relating to the distribution of real estate assets owned by legal entities such as recorded by the FPS Finance for tax purposes. This dataset is composed of eight classes. The first class mentions, at national level, for each cadastral income bracket, the number of legal entities with real estate activity (that is to say, registered under the code L of NACE nomenclature) and with real estate capital valued in the relevant bracket as well as the total and median cadastral income of the parcels held by these entities. The assessment of the cadastral income takes into account the shares actually held. The second class includes this information at the level of the three regions. The following classes do the same at the level of provinces, districts, municipalities, land register divisions and statistical sectors. The last class includes this information at the level of the countries for the legal entities which are not settled in Belgium but wich are nevertheless reigstred at the Carrefour Banque of the Entreprises.The dataset can be freely downloaded as a zipped CSV.

Mapping plan parcel - statistical sector corresponds to the dataset associating a plan parcel such as defined in article 2 of the Royal Decree of July 30th 2018 with the statistical sector including it. This dataset is composed of a single class mentioning the identifier of the plan parcels as well as the identifier of the statistical sectors. The dataset can be freely downloaded as a zipped CSV.

RMI operates a network of 17 automatic weather stations in Belgium. These weather stations report meteorological paramaters such as air pressure, temperature, relative humidity, precipitation (quantity,duration), wind (speed, gust, direction), sunshine duration, shortwave solar radiation and infrared radiation every 10 minutes. Daily AWS data are computed from the 10-min observations.

Annual and seasonal precipitation indices given in number of days: 1/ Wet days: Number of days with precipitation > 0.1 mm/day for winter, autumn, spring, summer; 2/ Dry days: Number of days with precipitation < 0.1 mm/day for winter, autumn, spring, summer; 3/ Average length of dry spells: Mean duration of minimum three consecutive days with precipitation < 0.1 mm/day; 4/ Maximum length of dry spells: Longest period of minimum three consecutive days with precipitation < 0.1 mm/day, occurring once in 20 years. The precipitation indices are available for the future target year 2085, which corresponds to the middle of the 30-year period 2071-2100, and for mean and high impact scenarios corresponding respectively to the 50th, and 5th or 95th percentiles of the change factors.