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D. Sources of spatial data

Specific to a GIS program is the variety of data types that they can store and process. These can be vector data, raster data (including remote sensing data), and attributes recorded in data bases. This feature is often called data integration. The value of a GIS data base depends on following criteria:

• spatial coverage of existing digital maps,
• numbers of thematic layers,
• data age,
• data spatial resolution and accuracy.

In many countries, an important source of digital thematic layers for GIS analysis is cartographic agencies. These include national agencies such as the British Ordnance Survey and the United States Geological Survey (USGS) Mapping Division. An important issue remains that of standardisation of the data collected. This is one of the subjects being considered in institutions like the U.S. National Center for Geographic Information and Analysis (NCGIA), Rosgeoinform in Russia, the British Natural Environment Research Council (NERC), and the Conseil National de l'Information Geographique (CNIG) in France. There are also agencies which provide information on existing sources of digital maps, a good example being the National Geospatial Data Clearinghouse in United States.

For research purposes in the earth sciences, the construction of a GIS data base starts with the defining model of the natural environment which then is converted into a digital form. This defining model is most often expressed as an analogue thematic map. In the next step, digitising devices are used to perform quantification and compilation of data in a vector or raster format. In the first case, this is accomplished by digitisation of analogue maps using a digitiser or by the vectorisation of a raster image displayed on a screen. In both methods, there is a need to register the map to define the relationship between the digitiser and screen co-ordinates or cartographic co-ordinates. Most often a linear transformation equation is used, having the form:

x = au + bv + e
y = cu + dv + f

Registration of the map is done using control points. These points are used to solve the above equations and determine the coefficients. Using these equations, it is possible to calculate cartographic co-ordinates from the registered analogue map on a digitiser or displayed on a screen.

A scanner is a device for obtaining raster data. Digital images are registered using a set of CCD (charge coupled device) elements. This can be done using a table or drum scanner, as well as by scanner installed on an aircraft or satellite. The scanner works on the same principle as a digital camera. The resolution of scanners used to quantify printed analogue documents is very high, reaching 0.025 to 0.050 mm. The parameter used to describe scanner resolution is the number of dots per inch (dpi), which ranges up to a value of 1200, and, by interpolation, to 9600 dpi. A scanner records all elements of the analogue picture, and, in this regard, it is similar to remote sensing scanning devices.

Satellite images and aerial photographs, as a type of raster data, contain a lot of information that has to be first extracted by image processing and interpretation. The spatial resolution of aerial photographs depends on their scale, and is in the range of 2 to 200 m. Data from these sources can be used in GIS programs within thematic layers such as land use, vegetation cover type, and patterns of settlement. Digital camera technologies open new possibilities for aerial photography, and are likely to improve the spectral resolution and range of this type of image. To use an aerial photograph in GIS, it is often necessary to rectify the image, or to convert the image registered in the central projection (principle of optical objective) to an image in an orthogonal projection. Such a transformation allows the user to develop an "orthophoto" map from aerial photography. Satellite remote sensing images are most often obtained by recording a wide spectrum of radiation reflected from the ground. The spatial resolution of such a multispectral satellite images ranges from a few kilometres (meteorological satellites) to a few meters.

Raster data can be also created by other programs. For example, spatial interpolation programs or computer models with distributed parameters can generate raster data. Interpolation programs use randomly distributed observation points to calculate new values located within a regular grid. Interpolated values can be visualised by assigning them pixel values and then displaying the values in the form of a raster image. Because raster data come from various sources, and may have different resolutions, a resampling procedure is used to make them compatible within the GIS program. This is commonly done by changing the position of the pixels and the pixel size. The commonly used formats for raster images (for instance, TIF, BMP, PCX files) do not contain information on the scale and cartographic co-ordinates of image. This creates a problem in transferring raster data between the GIS programs, since many GIS systems have their own standards for coding and compressing raster images registered to cartographic co-ordinates. Likewise, there are similar concerns with regard to satellite images, with each satellite source having its own characteristic data format (e.g., the Landsat MSS uses ACRES or EROS format, the Landsat TM uses the AMIRA format, and Spot uses the Image format).

Editing the geometry of raster data is called calibration (also known as "rubbersheeting". The parameters of the transformation equations are calculated by the least squares method. The following transformation methods are widely used:

• linear isotropic (Helmert transformation),
• linear anisotropic (affine transformation),
• bilinear,
• bicubic.

The calibration of raster models is used to correct distortions in aerial photographs and satellite images. It is used also for facilitating comparisons with old topographic maps (Figure 3.1).

Both vector and raster data have positive and negative properties. Which properties prevail depend on how closely the data model fits the properties of the object being modelled. When we want to depict the spatial variability of an environment, a raster model is generally better. Raster models correspond well to the continuity property of landscape units. When dealing with objects having sharp or well-defined boundaries, vector models are generally better. For purposes of using stored data in calculations, raster data are simpler because pixel values are stored in a matrix format.

Many GIS programs use both types of data, and work with so-called "hybrid graphics" Both raster and vector layers should be registered in the same co-ordinate system, however, for these hybrid systems to function. During registration, a relationship between the raster co-ordinates (i - row, j - column) and cartographic co-ordinates (x - eastings, y - northings) is calculated. Within the hybrid graphics environment, it is possible to perform conversions between data types by means of vectorisation or rasterisation. Vectorisation is more difficult, since precise vector data are being generated from less accurate raster data. In a raster data set, there is no information on topology, which has to be included in a vector data set. Automatic methods of vectorisation work on similar principles to those used in OCR (optical character recognition) programs. The raster layers have to be specially prepared before vectorisation. Specific concerns include the number of thematic layers visible, the continuity of lines, and width.

Rasterisation is much simpler, since topological information does not need to be stored. The vector layer is converted to a raster image at a declared resolution (pixel size).

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