The term Land Cover describes the physical configuration of the earth surface and distinguishes between natural and anthropogenic materials. Land Use is the actual usage of the land. It describes the incorporation of portions of the solid earth surface by human activities. It refers to the built environment as well as to open space. The available space can be subject to different usage demands simultaneously.
The land-use typology of the IOER Monitor is based on the principle that all land-use classes are exclusive, which means that each part of the earth surface is assigned to exactly one land-use category. Thus, the aggregation of the main land-use classes Settlement, Open Space, and Transportation equals to the total study area. Each of these three top-level categories is subdivided into further differenciated land-use classes.
Land-use classification scheme adopted by the IOER Monitor: Exhaustive and non-redundant description of the earth’s surface by land-use categories derived from the ATKIS Basis-DLM (based on the AAA Model) ) - Download (PDF 241 KB).
Land category will follow the following table of land use prioritization in the case of overlapping in creation of land use geometry. Higher levels are laying over eventually the lower level of surfaces.
37 Railroad traffic
36 Road traffic
35 Aviation area
34 Harbor basin
33 Standing water
32 Sea, shallow bay
31 Running water
30 Traffic accompanying area (road traffic)
29 Traffic accompanying area (railroad traffic)
28 Traffic accompanying area (air traffic)
27 Residential area
26 Combined use area
25 Other urban open space
24 Industrial, commercial area
22 Weekend housing
21 Small Garden
20 Golf course
19 Other recreation areas
17 Specific functional area
16 Mining area or dump site
12 Unproductive area
10 Mixed forest
9 Deciduous forest
8 Coniferous forest
7 Grazing land
6 Arable land
4 Fruit growing
2 Traditional orchard
1 Other agriculture
0 Undetermined area
In order to quantify the total and proportionate areas of transport pathways and watercourses, which are available as linear objects in the ATKIS Basis DLM, these must first be transformed into polygons. This is achieved by buffering both sides of the corresponding lines by the application of suitable attributes on object width. In the case where no width attribute is indicated or values are implausible, standard buffer values are applied.
In ATKIS, roads are generally modelled to reflect their real-world axes. Roads with physically separate carriageways (e.g. Autobahns) are defined as composite objects, consisting of a roadway axis and accompanying lanes. Otherwise, road axes and carriageways are geometrically identical. In order to create roadway areas, carriageways are buffered according to the value of the attribute BRF (carriageway width). This is the width of the sealed carriageway surface or the width of the accessible section of a pedestrian zone up to a precision of 50 cm. As BRF values are only intended to model carriageways, the estimation of the required area for pavements in urban roadways (excluding Autobahns and private roads) is realised by buffering the carriageway on both sides to a width of 2.50 m.
The standard values for carriageway width in the case of no or an incorrect BRF attribute value is specified as follows, depending on the attributes FSZ (number of lanes) and WDM (private or public roads). Roads with an invalid status as public roads are treated as private roads. If the number of carriageways appears implausible, two lanes are assumed.
|Lanes||Autobahn||Other roads (*)|
|1||5,50 m||4,50 m|
|2||10,00 m||5,50 m|
|3||14,00 m||10,00 m|
|>3||17,50 m||12,50 m|
(*) An additional 2.50 m is calculated on both sides of urban roads for pavements (except for private roads).
Rural hard-surface roads
Rural hard-surface roads (Hauptwirtschaftswege) are always modelled as linear objects along their real-world axis. They are the most densely interconnected roadways system in the entire transport network, and thus make up a considerable proportion of the total transport area. Such rural roads are buffered using the width attribute BRV (carriageway width). This gives the lane width in intervals of 3 m, whereby the smallest class has width 0-6 m. The target width of buffering corresponds to the mean value of an interval, which in the lowest width class is 4.50 m.
In the case of an invalid attribute value, BRV is set at 6 m.
Rail infrastructure is modelled in ATKIS Basis-DLM as both spatial and linear objects. In the case of linear modelling, railway lines are buffered in order to determine the corresponding transport area. The chosen buffer width depends on the attribute GLS (number of tracks) as well as BKT (railway category). Track sections in tunnels as well as decommissioned lines are not buffered.
The railway axes are buffered according to the target widths given in the following tab
|Number od Tracks||General||Tramway||Museum railway, park railway|
|1||7,50||4,50 m||2,00 m|
|2||10,50||7,50 m||4,00 m|
In air transport facilities (airports), runways as well as taxiways for airplanes are partly modelled as linear objects. In these cases the lines are buffered in order to determine the land requirements for the land-use category air transport. The target width of buffered areas corresponds to the value of the attribute BRO (object width; values in m).
In the case of an invalid attribute value, BRO is set to 15 m.
Watercourses whose width is less than 12 m are modelled as linear water axes. The width of such objects is specified by the attribute BRG (watercourse width) in three intervals, namely 0-3 m, 3-6 m and 6-12 m. Buffering is determined as the mean of the indicated interval. Underground watercourses, culverts as well as waterway sections that dry up during the year (attribute HYD – hydrological feature) are not buffered.
In the case of an invalid attribute value, the smallest width is set to BRG=3 m.
The Monitor of Settlement and Open Space Development (IOER Monitor) is based on the combined processing of geo base data, geo expert data and statistical data. Indicators are derived from these diverse sources, presented in cartographic and tabular form together with meta-information.
The most important sources of base data are the basic landscape model (ATKIS Basis-DLM), the digital land cover model LBM-DE as well as building footprints and coordinates from the real estate cadastre. This data is supplemented by topographical maps at scale 1: 25,000 (DTK25) from the Authoritative Topographic-Cartographic Information System (ATKIS) maintained by the Working Committee of the Surveying Authorities of the States of the German Federal Republic (AdV).
Geo expert data on protected areas from the German Federal Agency for Nature Conservation (BfN) is also utilized. In addition, use is made of statistical data at municipal and district level from the Federal Statistical Office bas well as indicators and maps on spatial and urban development (INKAR) from the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR).
Topicality: The basis of land-use monitoring is the regular nationwide updating of the geo-topographical base data by the surveying offices of the Länder. Hence, this data is employed by the IOER Monitor rather than the cadastral data ALK/ALKIS of official land-use surveys, as such data on land usage is not regularly updated nationwide. All data for the territory of Germany is updated at least every five years and increasingly every three years. Important object types such as road and rail networks are updated every ¼ to 1 year.
Spatial precision: Data for ATKIS Basis-DLM is captured from high-resolution orthophotos along with some additional information. The contents correspond to the object inventory required to create topographic maps at scale 1:10,000. This spatial resolution is sufficient to monitor land usage.
Thematic precision: According to the AdV (Working Committee of the Surveying Authorities of the States), agreement between the ATKIS geo-objects (actual use) and reality is at least 90%. Of course, the correct determination of land usage (classification and attributes) is vital here. Existing data errors will be successively rectified by the regular data gathering of the surveying agencies of the Länder.
Spatial comparability: The ATKIS Basis-DLM is gathered under application of an AdV model (GeoInfoDok) jointly agreed by all the Länder. Nonetheless, small disparities exist between the various Länder due to difference in data-gathering guidelines. If this serves to undermine the comparability of data, then no indicator is published (e.g. the ratio of mixed-use land in built-up areas).
Temporal comparability: Comparison through time is enabled by considering the base topicality of each dataset used to calculate indicators. However, the setting of the base data topicality is treated differently by the Länder. Temporal comparison may be temporarily impaired by the data migration of ATKIS Basis-DLM to the new AAA model. Such cases are highlighted at the level of Länder in the table tool when comparing different time periods.
Positional accuracy: For special objects such as linearly modelled streets, stretches of rail/tramway, waterways as well as topological hubs of roadways or rail/tramway, a positional accuracy of ±3 m is given. All other objects of the Basis-DLM have a positional accuracy of ±15 m.
Indicators: Indicator values are subject to both spatial and temporal verification. This helps to control for extreme outliers, which may be marked as such in the table tool. In principle, the indicator values become more reliable at higher levels of spatial aggregation. Clearly, larger target areas tend to compensate for local errors.
Indicators are presented in cartographic, tabular and chart form with statistical evaluations. A Map Viewer with WebGIS functionality is available for the quick and easy display of values on the basis of administrative units, whether the entire territory of Germany or at state, district and municipal level, as well as city quarters and spatial planning regions (so-called Raumordnungsregionen). The results can be presented in tabular form for all spatial units of a selected indicator (also in comparison with higher spatial units or other indicators) or for all indicators available for a selected spatial unit.
For visualization at higher spatial resolutions (raster maps of cell size 100 m, 200 m, 500 m, 1,000 m, 5,000 m, 10,000 m) grid maps are provided. They can be imported to an external GIS via Geoservices (WFS, WMS, WCS). Maps (different indicators, time slices and grid sizes) can be compared easily.
Ratios and indicators are calculated for spatial units at diverse levels over the territory of the Federal Republic of Germany (not including marine areas). The indicator values are generally based on administrative units (municipalities, districts, states) as well as spatial planning regions (so-called Raumordnungsregionen). If a municipality has onshore or coastal expanses of water then these areas are included in calculations. The cartographic illustration always indicates coastal lines but not borders around lakes or reservoirs.
The Gemeindeverband (association of municipalities) represents a form of inter-municipal cooperation that comprises at least two municipalities. The individual federal states have a variety of names for this: Amt, Samtgemeinde, Verbandsgemeinde, Verwaltungsgemeinschaft or Verwaltungsverband. The 12-digit regional code number (Regionalschlüssel)is required to identify an association of municipalities. Such associations can be found in the following ten federal states: Baden-Württemberg, Bavaria, Brandenburg, Mecklenburg-Vorpommern, Lower Saxony, Rhineland-Palatinate, Saxony, Saxony-Anhalt, Schleswig-Holstein and Thuringia. The spatial level of the Gemeindeverband (reflecting the administrative areas VG25 of the BKG) has been constructed for the entire territory of Germany by incorporating the Einheitsgemeinden (municipalities not belonging to any superordinate association) to this level.
Selected indicators can also be shown for cities (>50,000 residents) and their administrative subdivisions (Stadtbezirke, Ortsteile or similar units). The geometrical reference is derived from local land survey agencies or Open Street Map, in each case based on the reference year 2014 (see Table Link).
Presentation is also by means of raster maps at cell resolution 100 m, 200 m, 500 m, 1 km, 5 km and 10 km. This enables an inter-communal evaluation of settlement and landscape structure. The raster maps are independent of changes to administrative boundaries and thus allow the creation of stable time frames. It should be noted that with increased resolution (smaller raster width) ratio and indicator reliability decreases due to geometrical imprecisions and disparities in data topicality.
Comparison of values in the indicator tables can only be made from a current time period backwards to a previous time period, as new administrative boundaries usually result from the merging of previous units. On the other hand, the displayed differential values are oriented towards development (i.e. from old to new).
The indicators for a time period always refer to the latest territorial status for which population statistics are available for the years relevant for monitoring (currently 31st Dec 2017). Earlier datasets are always converted to this territorial status.
In order to take account of differing data topicality during the evaluation, an annual rate of change can be indicated for each table using the button “disparity to other time periods”. This, however, can only be realized when the time difference to the current data is greater than one year. Every column of the displayed table can be resorted by clicking in the column head. This allows quick identification of maximum or minimum indicator values as well as changes in values. It is possible to show a profile of all indicators in a spatial unit for the selected time period.
Similarly, the indicator value of a spatial unit can be marked in a histogram of all displayed spatial units. This enables the comprehensive characterization of spatial units or the offered spectrum of indicators. On the other hand, the spatial unit of interest can be classified within the distribution of an indicator. Finally, the temporal change in an indicator can be visualized and exported by means of a development graph from the indicator table.
The continuous updating of IOER Monitor geo base data is a time consuming process, as all changes in topography (including land use) have to by mapped by hand from orthophotos. Basic updating of mapping sheets (the primary data unit) occurs in a three-year cycle (in some states a five-year cycle). The size of trapezoid maps sections (approx. 4, 25 or 100 km²) depends on the state, the type of map and the latitude. The topicality of topographic information will vary according to the map.
Furthermore, there is a distinction between base and peak topicality of the geo base data. The ATKIS Basis-DLM is regularly updated by official surveying agencies, thereby ensuring the base topicality of the individual maps. Changes to particularly important topographic features (primarily in the area of transport) are reflected in geo base data as part of peak updating at 3, 6 or 12 monthly intervals.
Unlike statistical data, it is generally impossible to give a general statement of topicality for ATKIS data (in the form of a specific date) on administrative units that are spread over several individual maps. Thus a spatially-weighted (base) topicality is calculated for every spatial unit in terms of a specific month, displayed beside every indicator value and illustrated in an accompanying map. The base topicality of an indicator value for a municipality can differ from that of the superordinate district or the national level.
The time frame in the interactive map selection within the IOER Monitor reflects the date at which data is made available, generally January of the following year. The actual topicality usually one or two years earlier (comparable with the figures in the Statistical Calendar).
Step by step, additional indicators are being introduced to describe the building stock (building type, building usage, floor area ratio, building volume density, etc.). These are calculated on the basis of official building footprints (HU-DE), official building coordinates (HK-DE), 3D buildings models (LoD1-DE) as well as classified building footprints of topographical maps at scale 1:25,000 (DTK25 bzw. DTK25-V). Such indicators describe developments within flood zones and protected areas.
Supplementary indicators are currently being developed to describe the potential of vacant lots.
Furthermore, it is planned to calculate building indicators for previous time periods via the automated analysis of (historic) topographic maps for the time periods 1990, 1970, 1950, 1930 and 1900.