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.

This dataset comprises historical orthophotos from the 1950s to 1959, derived from aerial surveys carried out by the National Geographic Institute (NGI). The ground sample distance (GSD) of the images is 50 cm. The mosaics were created using aerial photography campaigns dating from 1951, 1952 and 1954. The original photographs were digitised and orthorectified in the Lambert 2008 coordinate system. The spatial coverage for each year corresponds to the areas for which photographs were available. High-resolution data can be ordered via https://shop.ngi.be/fr/photos-aeriennes/

The data set has been established according to the INSPIRE format. It presents in the form of polygons the breakdown of Belgium in almost 20,000 statistical sectors. The statistical sector is the basic territorial unit resulting from the subdivision of the territory of municipalities by STATBEL since 1970 for the dissemination of its statistics at a finer level than the municipal level. A statistical sector cannot extend over two municipalities and any point in the municipal territory is part of one and the same statistical sector. The 1970 and 1981 versions are shown in analogue format while the 2001, 2011, 2018, 2019 etc. versions are available in digital vector format. The files can be linked to the data on population, housing and disposable income on the website of Statbel.

This dataset consists of historical aerial imagery (1947-2007) commissioned by the National Geographic Institute. It includes the spatial footprints and metadata of individual photographs as well as the corresponding flight paths of the aircraft used during image acquisition.

This dataset comprises historical orthophotos from the 2010s to 2019, derived from aerial surveys carried out by the National Geographic Institute (NGI). The ground sample distance (GSD) of the images ranges from 25 to 100 cm. The mosaics were created using aerial photography campaigns dating from 2010, 2011, 2012, 2013, 2014 and 2015. The original photographs were digitised and orthorectified in the Lambert 2008 coordinate system. The spatial coverage for each year corresponds to the areas for which photographs were available. High-resolution data can be ordered via https://shop.ngi.be/fr/photos-aeriennes/

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 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.

This is the discovery service of the pan-European spatial datasets provided by the European mapping and cadastral agencies: EuroGlobalMap, EuroRegionalMap, EuroDEM, Open Cadastral Map, Pan-European Imagery, Open Gazetteer. The datasets are openly available accessible on the platform Open Maps for Europe (OME) http://www.mapsforeurope.org/.

This dataset contains the administrative units for the organisation of elections, within their boundaries as established by Annex I of the Electoral Code.

Summer and winter mean global solar radiation given in kWh/m²/day. The global solar radiations fields 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 95th percentiles of the change factors.