Rural Land Use Netherlands — LGN2018

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Dataset information

Country of origin
Updated
2019.08.01 00:00
Created
2019.08.01
Available languages
Dutch
Keywords
Quality scoring
90

Dataset description

The LGN2018 file is a land-covering grid with a resolution of 5 meters in which 48 forms of land use are distinguished. The stock distinguishes the main agricultural crops, a number of nature classes and urban classes. The LGN2018 file has undergone some important changes compared to LGN7. The geometry and theme on main classes is now fully based on Top10NL (version 2018). Agricultural parcels, greenhouses, orchards, fruit nurseries, orchards, sand, heath, forests, water and infrastructure have been taken over from Top10NL. The urban area is defined by land use resistant (BBG2015). The agricultural area is filled with (aggregated) crops from BRP2018 supplemented by crop classifications based on satellite images. For the further interpretation of nature, especially the forests, the heath and the sand, the satellite images of 2018, AHN2/3, aerial photographs, Basic Map Nature 2017 (BKN2017) and LGN7 have been used. Land use files LGN1 and LGN2 were still experimental files with limited accuracy and obvious shortcomings. In LGN3 these shortcomings have been largely resolved and with LGN3plus the usability of the file for applications in the field of nature and ecology is greatly improved. With the LGN4 file, a new step has been taken to expand the application possibilities of the LGN file. Important improvements made in the LGN4 stock are the linking of agricultural crops to TOP10 vectors and the possibility of detecting land-use change that occurred in the period 1995-2000. The versions 1-3 of the LGN file were delivered as a single raster file. The LGN7 file, like the LGN4, LGN5 and LGN6 file, does not consist of a single grid file, but constitutes a collection of files. With the LGN2018 file, the production process is streamlined so that a new version of land use in the Netherlands will be published every year. In addition to the sharp increase in spatial detail (25 m -> 5 m resolution), the thematic detail of nature is also greatly improved.
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