Geographic information system
Geographic Information Systems , Geographic Information Systems ( GIS ) or Spatial information systems ( RIS ) are information systems for collecting, processing, organization, analysis and presentation of spatial data . Geographic information systems comprise the hardware, software, data and applications required for this.
Geographic information systems are used in many areas, including geography, environmental research, archeology , marketing , cartography , urban planning , criminology ( crime maps ), logistics , resource management, and healthcare . With the help of a GIS, disaster control officers can, for example, compile information for evacuation plans . Environmental protection agencies can determine which wetlands are in particularly threatened areas. Marketing departments can find out in which areas new customers can be won.
Cro-Magnon hunters drew pictures of their prey on the walls of the Lascaux cave around 15,500 years ago . Along with the animal pictures, path and line drawings were found that can be interpreted as migration routes of these animals. Although simple compared to modern techniques, these early representations depict two elements of the structure of modern geographic information systems (an image linked to attribute information).
In 1854 the doctor John Snow drew up a map of the cholera cases in London. He represented each case as a point at the appropriate position. This application was possibly the first of its kind. Snow's studies of the distribution of cholera cases led to the source of the disease, a contaminated water pump in the center of the cholera map. While the basic elements of topology and topic were already known in cartography , John Snow's map is characterized by the fact that he used these cartographic methods for the first time not only for visualization, but also for cluster analysis of spatial phenomena.
Photolithography was developed at the beginning of the 20th century . This technique splits the content of the map into several layers. With the rapid development of computer hardware in the 1960s, the first universal map creation applications emerged.
Development of modern GIS
In 1962, the first modern GIS was developed in Ottawa by the Department of Forestry and Rural Development. Dr. Roger Tomlinson developed a GIS called Canada Geographic Information System (CGIS). It had functions for storing, analyzing and processing data from the Canada Land Inventory . The aim of the development was to determine the capacities of the country (soil, agriculture, forests, wild animals, water birds, land use) on a scale of 1: 50,000. This data has been categorized into grades to enable analysis. CGIS was the first real GIS and a further development of the pure mapping applications, as it includes numerous additional functions such as overlay, measurements and digitization / scanning. It supported a national coordinate system, processed lines as arcs with a real topology, and saved the attributes from the spatial information separately in separate files. Through this development Tomlinson became known as the "Father of GIS". CGIS was in use until the 1990s and was Canada's largest digital land resource database. It was developed as a mainframe system to support national and regional resource planning and management. One of his strengths was the nationwide analysis of complex data. CGIS was never available in commercial form.
In 1964, Howard T. Fisher founded the Laboratory for Computer Graphics and Spatial Analysis at the Harvard Graduate School of Design . Numerous important theoretical concepts for the processing of spatial data were developed there. As early as the 1970s, the team had published numerous future-oriented program code sections and software systems such as "SYMAP", "GRID" and "ODYSSEY". These were sources of inspiration for later commercial developments.
In the 1980s, M&S Computing (later Intergraph ), ESRI , MapInfo and CARIS emerged as important commercial producers of geographic information software. Your GIS comprised numerous functions. They build on the traditional approach of separating spatial data from attribute data, but store the attribute data in databases .
At the end of the 20th century, GIS technology developed towards the Internet. For this it was necessary to standardize data formats and data transfer.
Today there are more and more open source GIS that run on numerous operating systems and can be adapted for special requirements. A well-known one is QGIS .
In the commercial sector, commercial GIS dominate. The best-known manufacturers include Autodesk (Topobase and Map3D), Bentley Systems (MicroStation), ESRI (ArcGIS), Intergraph (GeoMedia), Manifold System , Pitney Bowes (MapInfo and pbEncom), Supergeo (SuperGIS), Disy Informationssysteme GmbH (Cadenza) and Smallworld . These manufacturers usually offer a complete range of products with systems in different expansion stages. Authorities and the military mostly use specially created, adapted (e.g. ESRI (ArcGIS), Pitney Bowes (MapInfo), CAIGOS (CAIGOS-GIS), GEOgraFIS, POLYGIS ), or open source software products.
The best known open source GIS are GRASS GIS and QGIS , both projects of the Open Source Geospatial Foundation , as well as OpenJUMP and DIVA-GIS . There are numerous other systems or GIS tools such as SAGA GIS , FWTools , GeoTools or OpenLayers . The products from Autodesk, ESRI, CAIGOS and Pitney Bowes dominate the German-speaking market. Open source GIS play a subordinate role.
Distributed, service-based architectures enable simplified, cost-effective spatial data distribution. Most desktop GIS support access to web-based standardized map and spatial data services. Current developments in the field of web GIS show the increased importance of GIS on the Internet.
Data models describe which data can be stored in an information system and how this data is structured. This is information about real objects (people, parcels , rivers). These objects are described by selected attributes. For example, you can assign the attributes district number , corridor, parcel number and type of use to all parcels . The properties mentioned are those that uniquely designate an object of the type parcel (state, district, corridor, parcel counter, parcel denominator in the format 00/0000/000/00000/00000) and describe its nature. One also speaks of “descriptive data”, “thematic data”, “factual data” or “attribute data”.
The "classic" information systems are limited to the pure administration and processing of factual data. In GIS, the so-called geometry data are compared to the factual data. They describe the geographical location, shape, orientation and size of objects (see also spatial objects ). A distinction is made between vector data and raster data . Vector data represent the object geometry using graphic elements (e.g. points, lines, arcs). Raster or pixel data are mostly created from digital images (map images or aerial or satellite images ).
In the case of vector data, the geometry of a parcel is given in the form of the boundary point coordinates and the geometry of the boundary lines (line, arc). The extract of a digital aerial photograph (usually in the form of an orthophoto ) represents the parcel geometry in the form of raster data.
In addition to the information of the individual objects, information systems also store relationships between these objects. It can be a matter of factual or spatial relationships, or both relationship categories can be mapped. A logical relationship can e.g. B. Establish between parcels and people: A “person” (object) is the “owner” (factual relationship) of the “parcel” (object). The logical relationships can be evaluated in an information system; Example: Query all parcels owned by a specific person.
Spatial (= topological) relationships, for example, enter into parcels with one another: a parcel (more precisely: the parcel area) “is a neighbor” (topological relationship) of another parcel. Topological relationships can also be evaluated in a GIS. Example: Querying all neighboring lots of a certain parcel.
GIS master the integrated management of factual and geometric data as well as factual and topological relationships. This means that queries or evaluations can also relate to both types of information. Example: Query of owner data (factual data-related aspect) for all parcels that are adjacent to a selected parcel (topological aspect) and have an area that is larger than 1000 m² (geometry-related aspect).
Data structure model
A data structure model specifies the way in which objects and their mutual relationships can be mapped in an information system, here specifically a GIS. For the storage of the object properties and relationships, z. B. enforced the relation model. All attributes of similar objects are managed in tables ; The same applies to the relationships between the objects.
Vector-based data structure models make it possible to describe the object geometry with the help of geometric elements (e.g. points, circular arcs, lines); These elements can be combined to form higher-value geometries (e.g. lines or areas) through ordered or unordered grouping. Vector data can be linked relatively easily with factual data.
The raster-based data structure model only knows a single data structure element, namely the raster element, also called pixels or "image point" depending on the type of raster . Two properties can be assigned to the grid elements: the geometric and the radiometric resolution. The geometric resolution indicates the length and width of a grid element in nature; the radiometric resolution describes the distinguishable gray values per raster element.
The topology describes the spatial relationship between spatial objects (neighborhood relationships). In contrast to geometry, which affects the absolute form and position in space, topological relationships between spatial objects are independent of dimensions such as distance. The most important topological relationships between two spatial objects A and B according to Egenhofer are:
- A is disjoint to B
- A lies within B.
- B lies within A.
- A covers B
- B covers A
- A touches B
- A equals B
Depending on the task at hand, geographic information systems can manage and process geodata in one to four dimensions:
- along a line (road or rail route , shaft, border , etc.),
- on a surface ( 2D , which is the most common case),
- 3D - solids or 2D time series, or
- combined in space and time (4D)
In older systems, the shape primitives were only embedded in the two-dimensional space due to a lack of 3D data.
In a transition phase, the height specification was added as an attribute to two-dimensional objects. However, since this has not yet resulted in a 3D embedding, in this case we only speak of a two-and- a- half- dimensional embedding.
The quality of data can only be assessed on the basis of the quality characteristics with regard to a specific question. The amount of data features that enable the use of the data for a specific task can be referred to as data quality. These data characteristics should be documented in the corresponding metadata . The ISO has listed features for the quality of geodata in the ISO standard ISO 19113 .
The rights to geospatial information are mainly derived from copyright . If geographic information is managed under public law, there may also be rights under surveying and geographic information law . The rights of “everyone” allow you to determine your own location, as well as to create maps of publicly accessible places, to use and distribute this data yourself. Projects like OpenStreetMap follow this development path.
Functions of GIS
Modern GIS use digital information, for the acquisition of which different data acquisition methods are used. Especially in the early days, the digitization of paper maps and survey plans was the most common data acquisition method. For this purpose, the analog information is transferred into a digital form with the aid of a digitization board and georeferencing methods (in GIS or CAD programs). The on-screen digitization of satellite and aerial images is becoming increasingly important. The scanned or already digital images are used directly on the screen as a template for digitization.
Another method of data collection is data collection in the field with GPS devices. With the help of DGPS , usable accuracies can also be achieved for surveying purposes.
Geodata can be saved in a wide variety of file formats and (geo) databases. Practically every commercial GIS manufacturer provides their own formats. Geographic information systems therefore usually offer functions for converting geodata into different file formats.
Since digital data can be collected and stored in a wide variety of ways, two data sources are not compatible. The spatial information system must therefore be able to convert spatial data from one structure to the other. A GIS can be used to convert satellite images (grid structure) into vector structures or vice versa, to convert vector structures into grid structures.
Vector to raster and raster to vector conversion
General irregular surfaces can only be approximated with difficulty using a grid, since several pieces of information can be omitted from one grid cell. This problem becomes particularly clear with coarser cell structures, but even a fine grid does not solve the problem in principle. A frequently used approach is that the grid cell gets the value of the starting area that has the largest share of the cell. It can also be useful to determine certain properties that should be assigned priority or greater weight to a cell.
There are two types of raster-vector conversion:
- Vector objects are to be generated from neighboring cells with the same attribute values.
- Attributes from raster data sets are to be assigned to existing spatial objects.
In practice, this type of raster-vector conversion is based almost exclusively on the so-called point method . Geo-objects are intersected with the centers of the grid cells. If the center of the cell lies within the spatial object, the value of the cell is used to calculate the value of the spatial object (for example by averaging).
Geodata are available in a wide variety of coordinate systems. In order to be able to process them together, they must be related to the same coordinate system. Coordinate transformation is therefore a central function of geographic information systems. The coordinate transformation can be done on-the-fly , i. H. take place during operation or in a separate work step.
Georeferencing, geocoding or localization is the assignment of spatial reference information to a data set. In many cases, transformations and conversions as well as interpolations are necessary to establish the spatial reference . This includes eliminating geometric distortions, fitting the data into a selected coordinate system and / or mutually adapting two data layers.
Personal data can be located using the address. For this, depending on the task at hand, extensive address databases are necessary in order, for example, to obtain street-specific values.
With growing amounts of data and the increasing spread of geographic information systems, it is becoming more and more important to manage geospatial data efficiently. To do this, it is necessary to collect metadata and update it continuously. Some GIS have built-in functionality for this, while other systems let the user manage metadata using other software products.
At the beginning of the GIS era, only a few GIS basic systems used commercially available database systems (e.g. DBASE or Oracle) to store the factual and geometric data (primarily vector data ). A variety of systems were based on proprietary database management systems. Today, the use of commercially available relational or object-relational database systems for spatial data management has established itself.
Conventional databases cannot manage geospatial data efficiently. Therefore, there are extensions for the management of spatial data for many commercial and open source databases. Examples of geospatial databases are: Oracle Spatial , PostGIS and SpatiaLite . Some manufacturers offer interfaces to different databases.
The concept of spatial or GIS analysis is not clearly defined. For analysis, raw data must be converted into useful information in order to make more effective decisions. Analyzes can reveal circumstances and relationships that would otherwise have remained invisible. In the literature, the term is used for the following areas:
- Spatial data manipulation (for example the creation of buffer zones)
- Spatial data analysis - descriptive and investigative
- Spatial statistical analysis (e.g. interpolation by kriging )
- Spatial modeling for spatial forecasting
A further distinction can be made between qualitative and quantitative spatial analysis.
For spatial analysis, it is important to know in what form data is stored and how the spatial phenomena are represented. The quality of the initial data has a decisive influence on the analysis. Both the suitability of the data and the choice of suitable analysis areas are of great importance.
Spatial analysis methods include: queries, measurements, transformations, descriptive summarization, optimization, hypothesis testing, and modeling.
The results of spatial analyzes change when the location of the examination objects is changed. To avoid misinterpretations, every spatial analysis requires a professional interpretation of the results.
Queries and selections
- factual: how many inhabitants does a particular city have?
- spatial: how many and which cities are there on the bank of a particular river?
The buffer function (engl. Buffer ) allows the formation of buffer zones to geo-objects of arbitrary dimension. Depending on the dimension, one speaks of point, line or area buffers.
When creating the buffer zones, an area is generated around the selected spatial objects. The buffer zones enclose the spatial object and surrounding areas within a certain distance (fixed value or depending on the attributes of the spatial object) from the original spatial object. The original geo-objects are not changed during this process.
Buffers are not just graphical representations, but objects that can be used to carry out analyzes such as intersections. It is possible to create several buffers around an object and to weight them differently (e.g. different protection zone categories).
Processing of borders
When processing borders, only the geometry of a data layer is changed. The attributes and attribute values are not affected. Only the area and the circumference of the resulting partial areas are recalculated. Possible modifications are:
- Merging geometries
- Punching out areas
- Split into several small areas
- Cutting out / deleting parts from the interior of an area
Intersection is the superposition of subject levels (layers) or object classes . With the help of Boolean operations , new objects are created from the output data levels, which combine the attributes of the output objects. A new data level is created. The output data levels are not changed.
This function combines objects with the same attribute, e.g. B. to remove " splinter polygons " that were created by intersection.
The analysis of networks is one of the central applications of geographic information systems.
Areas of application for networks are the modeling of traffic systems such as road or rail networks, but also line networks such as B. pipeline networks or telecommunications line networks. Networks are sets of nodes and edges. They belong to the graphs, whereby in practice mostly only asymmetrical and weighted graphs occur. The analysis of networks is based on graph theory . Networks have a node-edge-node topology and are thus based on the vector model.
Network edges can represent roads, railways or shipping lines for a transport network as well as conductor tracks of an electrical network or the rivers of a river network. The nodes of the network are z. B. stops or general connection points such as intersections. The network elements can be assigned properties that can be included in analyzes depending on the task at hand. The evaluation of the edges is usually based on the path length between two nodes. The journey time can also be used to evaluate the vehicle navigation.
Network analyzes are carried out to solve the following problems:
- Determination of the shortest paths between two points
- Salesman Problem
- Determination of catchment areas
Powerful GIS offer methods for spatial interpolation and modeling of areas in space. Starting from a few points (x i , y i ) with attribute values z i (for example temperature measurements or height information) distributed in space, attribute values z k are to be determined for any points (x k , y k ) . For this purpose, the known values z i are deduced from the unknown z k values using interpolation methods . It is implicitly assumed that those locations (or the associated values) that are closer to it have a greater influence on the value sought at a new location. Interpolation methods boil down to determining weighted mean values.
Classic areas of application are the calculation of a spatial precipitation or temperature distribution, a terrain or groundwater surface or the spatial distribution of substance concentrations in the soil.
The spatial interpolation methods include:
- Trend area analysis
- Spatial interpolation by averaging
- Triangulation and Thiessen polygons (Voronoi diagram or Dirichlet decomposition)
The display and presentation options play a decisive role in GIS and are therefore very extensive. Here are some important examples:
- automatic creation of legend, scale bar, north arrow and other map edge information
- Freely selectable map scale and any map sections
- Representation in a freely selectable map network design
- Freely definable colors and patterns, as well as symbolic representations
- Fade in / out and combination of different layers ( raster and vector data )
- 3D representations, digital terrain models , "drape" (3D model overlaid with raster or vector data)
- Animations (flight over terrain and the like)
- Terrain sections / profiles
- Integration of diagrams, image or audio data
For recurring tasks, it makes sense to automate them by combining the necessary processes into macros. Such tasks can be:
- Plots of maps and plans according to a certain sheet section under the same boundary conditions
- Post-attribution of imported data
- specific periodic evaluations for regular reports
- Regular data transfer to other offices or companies via defined interfaces
- Checks for data consistency
- Inclusion of externally maintained factual data
Requirements for automation are:
- A macro language with loops, conditions and input options
- consistent , redundancy-free data (exception: if the consistency is first checked by the macro ).
- software-readable, classified data attributes that can be used for selection .
Characteristics of geographic information systems
Land information systems (LIS)
Land information systems manage detailed geospatial data, especially basic data (primary, directly measured / collected data), which are structured on a large scale . Land information systems are mostly set up and managed by the surveying authorities ( land registry and surveying office ). They primarily relate to the mapping of the earth's surface by means of surveying in the form of digital maps and land registers .
Municipal information system (KIS)
Municipal information systems are GIS in municipalities . The central component of a KIS is the geographic base data of the LIS ( automated real estate map and automated real estate book in Germany, digital cadastral map and real estate database in Austria) and aerial photographs . They allow the employees of a municipality quick access to information on a parcel (owner, area size, use ...).
In addition to this basis, HIS contain various additional layers. A municipal environmental information system (KUIS) is, for example, an instrument for tasks of the municipality in the field of the environment , which keeps data on all environmental areas spatially, temporally and objectively available, processes and keeps it up to date. The first additional layers that were recorded mostly contained the pipeline cadastre for water, sewer, gas and electricity. Today there are various additional layers such as green space cadastre , tree cadastre , cemetery cadastre , playground cadastre , etc. a.
Environmental information system (UIS)
Environmental information systems serve to provide environmental information. They usually consist of several environmental databases on various topics and offer powerful access and analysis methods for deriving environmental information. Environmental information systems are used to record, store, process and present data related to space, time and content to describe the state of the environment with regard to pollution and hazards and form the basis for environmental protection measures . They usually consist of many different specialist information systems (FIS).
Your tasks range from the recording of radioactivity, the control of the environmental media air, water and soil to biotope mapping and the preservation of biodiversity. They are used for emergency preparedness, administrative enforcement and public information in the environmental sector.
Because of the diversity of potential users of a UIS, there are very different, sometimes diverging requirements on the characteristics of a UIS. UIS are used as information systems in administration and in companies in the private sector (so-called corporate environmental information systems). Early users were, for example, environmental authorities such as the Federal Environment Agency (UBA) or state environment ministries and their subordinate state offices.
Soil Information System (BIS)
A soil information system in the narrower sense (A, CH) contains data on the local distribution of soil types and their properties such as soil structure, humus content, pH value and soil weight. In addition to the type of soil , the soil maps can also show soil pollution or the risk of erosion .
A soil information system in the broader sense (e.g. the BIS-NRW or the Lower Saxony soil information system NIBIS ) also includes data on the geological structure of the uppermost crust as well as on hydrogeology , resilience, engineering geology and geochemistry. The data contained Bore Descriptions, analysis data and maps of different scales and themes.
Network information system (NIS)
A network information system is used by supply and disposal companies to document their line inventory. In addition to the graphical representation of the cable routing and its status, data records about type and technical data are managed in this information system. Network information systems are offered by many companies and are used for engineering planning - for example for line research before construction work.
Specialized information system (FIS)
Specialized information systems represent a special class of geographic information systems. This includes special applications that are not covered by the previous versions. They are information systems that support specialist tasks and are necessary to cope with specific specialist requirements, for example for construction , geography , geology , hydrology , avalanche and environmental protection , traffic planning , tourism , leisure and route planning . The main buyers for specialist applications are municipalities.
GIS in archeology
Geographic information systems are also used in archaeological research. So z. B. archaeological sites are linked with information about their environment such as water, raw material and food removal, soil quality, climatic zone. Above all, geodesists , geographers and archaeologists work together in interdisciplinary groups.
In the archaeological preservation of monuments in different countries and states (pioneers in Europe, among others, the Netherlands), GIS are mainly used for inventory recording, visualization and evaluation. For example, sites and the associated information can be quickly mapped for land use planning and compared with planned construction projects. Recently, GIS have increasingly been used to calculate location criteria for as yet unknown sites (so-called prediction models; e.g. Brandenburg archaeological forecast.)
GIS in event planning
GIS also serve as a tool for planning large events. In the GEOLYMPIA project, the GIS cluster of the University of Salzburg demonstrates the improved planning and implementation of major sporting events. The optimizations were used for planning events such as the 2006 World Cycling Championships, the 2008 European Football Championship or the 2014 Olympics. The group develops modules for scenarios for the sustainable use of resources and for increasing the security of such large events.
GIS in transport and logistics (GIS-T)
Geographic information systems for transport and logistics (GIS-T) comprise the methods and applications of GIS technologies for problems in the transport sector. An important application is the creation and maintenance of road graphs.
Standards for geographic information systems
The most important standards in the GIS area are the standards of the Open Geospatial Consortium (OGC) and the ISO series 191xx.
OGC interface and protocol specifications enable communication between different web GIS, location-based services and standard IT technologies. The standards enable the development of complex geospatial applications and their functions to be made available to a variety of applications. Examples of OGC specifications are Web Map Service (WMS), Web Feature Service (WFS), and Simple Feature Access .
ISO series 191xx
Standards of this series:
- ISO 19107 (spatial reference scheme)
- ISO 19109 (application schemes )
- ISO 19111 (coordinate reference systems)
- ISO 19115 (metadata)
- ISO 19136 (Geography Markup Language / GML)
The spatial data infrastructure in the European Community , English Infrastructure for Spatial Information in the European Community (INSPIRE) is an initiative of the European Commission for a European spatial data infrastructure, especially in environmental policy. The basis is the guidelines 2007/2 / EG and their implementation provisions. They regulate a uniform data / metadata format.
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