Information on the available generalised geodata on land use based on the land use statistics
Swiss land use statistics provide precise and detailed information on the current status and development of land use and land cover in Switzerland. They are an important basis for monitoring land use and for developing indicator systems. In addition to statistical tables, the results of the land use statistics are also available as geobasis data in hectare resolution.
Generalisation for better map visualisation
In addition to information about land use and cover, cartographic representations also meet a common requirement.
Since the 1979/85 survey, the Swiss land use statistics have been based on random sample points that do not represent actual surfaces. For this reason it is difficult to reproduce results in the form of maps. Although each random sample point statistically represents a hectare of ground surface, the position of the point gives little information about the spatial location and distribution of the hectares represented. A cartographic representation, therefore, leads to an inhomogeneous, noisy and rather implausible map image, in which many categories are widely scattered and appear to be distributed at random. Small-scale and linear uses such as woodland, buildings, watercourses and roads are particularly affected by this problem. To obtain a more suitable basis for cartographic work – especially with regard to the creation of a visually appealing land use map – the FSO, in a process involving several stages, has condensed the point data of the land use statistics into 18 groups and generalised them geometrically. By rasterisation and the subsequent running of image processing algorithms, three background datasets with different information content were created that are suitable for cartographic visualisation in various scales. These data distinguish the 18 following land use classes:
As the present geodata of the simplified land use in hectare resolution are based on a generalisation process that based on neighbourhood criteria, majorities and similarities, condenses and greatly simplifies the basis data which was collected using exact, scientifically tested methods, their statistical evaluation and the derivation of results in the form of numeric tables is not recommended.