LGN7

The LGN7 database is the newest database in the series and succeeds LGN6. This database reproduces the usage of land in the Netherlands in 2012 and differentiates between thirty-nine known land use types.

What is LGN7?

LGN7 is a grid file with a spatial resolution of 25*25 metres. This database distinguishes the most important agricultural crops, forests, water, nature and urban classes. It makes use of the following databases: Kadaster’s topographic base date (Top10NL, version 2012), the Land Parcel Information System 2012 (LPIS2012), the Netherlands digital land use map 2008 (BBG2008), the Basic Nature Map 2012 (BKN2012) and LGN6. In addition to this, use is made of satellite images from the National Satellite Data Portal (NSD) and aerial photos from 2012 during the classification process. The LGN7 database was published at the end of 2013.

Several Updates

The newly-launched LGN7 includes a number of updated features. For the first time ever the database reproduces an image of land use that is based on land use data from only one reference year. Earlier versions divided the Netherlands into two parts due to the limited availability of satellite images. LGN6, for example, based the west of the Netherlands on images from 2008 and the east on images from 2007. The LGN database uses Top10NL for the first time and it is Top10NL that provides geometry and themes for LGN7’s main classes. This results in several LGN class definitions becoming more strictly defined. Furthermore, the agricultural crop classification is improved due to the use of BRP2012 in combination with multi-temporal satellite images (high temporal frequency). As well as this, the swamps are now fully based on the presence of bogs, swamps or reeds within Top10NL fields. Lastly, the infrastructure class (LGN class 25) has been adapted to include the runways, railway bodies and car parks that are found in Top10NL.

The construction of LGN7

The LGN7 product consists of different files:

  • LGN raster database, national, +/- 39 classes (LGN7)
  • Aggregated versions of the LGN6 and LGN7 raster database (LGN6mon and LGN7mon)
  • LGN7 changes database: a national database with actual changes in land use between 2008 (LNG6) and 2012 (LGN7) based on 8 main classes.
  • Meta-information based on the ISO/CEN98 Standard in XML format

LGN7’s method

The database is constructed in the same manner as the LGN6 database. The LGN7 database is, just as its predecessors, a raster database with grid cells measuring 25*25 metres, which distinguishes thirty-nine forms of land use. The most recent version of the TOP10NL database is used as a geometric basis. This means that the classes are aggregated to the base LGN classes. The Netherlands digital land use map 2008 (BBG2008) is used for urban areas. Satellite images  and BRP2012 form the basis for ascribing crops to agricultural land. Swamps are ascribed on the basis of the symbols representing reeds, bogs and swamps. LGN6 is used to assign dune heaths, salt marshes, moors and the difference between sand along the coast and sand drifts and river sands.

Aerial photos and satellite images are used to classify the actual changes for the eight monitoring classes that occurred between 2008 and 2012. Following this, LGN6 is used in order to further refine the base classes. The difference between deciduous and evergreen forests (LGN classes 11 and 12), between open sand and coastal areas, dunes with low and dunes with tall vegetation (LGN classes 31, 32 and 33), and between heath, slightly-grazed and over-grazed heather (LGN classes 36, 37 and 38) are all taken from LGN6. Changes between these classes over a period of 4 years are usually minimal. New forests, dunes and heather are allotted to LGN class 11, 31 and 36 respectively. The Natural Landscape Standard Map adds further data about natural grass lands to LGN7.

The Process

The figures below represent the process and the different databases that are used in the production of the LGN7 database. The first step in the production of the LGN7ras database is an object-oriented classification. The second step in the production of the LGN7ras database is the enrichment of LGN7 pixels with additional information. Derivation of the finished products.

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