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Mapping and Satellite Data [        ]
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|  Introduction
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Chorological matrix
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Histogram
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Classification
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Digital Images
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Introduction
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Model of a map with a grid.
| A map can provide an overview of a large geographical area. However, it contains only a general and limited level of detail about the mapped area and the level depends on the compiler's point of view and/or the purpose of the mapping.
A thematic map is often limited to illustrating the spatial distribution of a single feature such as temperature or population density. Choroplethic maps are special thematic maps which have many similarities with digital images.
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| A simple example of traditional chorological mapping methods can show some of the fundamental principles of satellite images: In each square the number of houses is counted as the basis of the chorological matrix.
| Chorological mapping methods are used today in digital image processing. A simple example of settlement mapping may illustrate this. Settlement density can be mapped chorologically by spreading a grid over a topographical map. The number of houses is counted in each square.
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Chorological Matrix
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| The result of the count is a Chorological matrix consisting of numbers placed in a co-ordinate system. The geographical distribution of the settlement has now, in a sense, been digitized i.e. converted into digits (= numbers), so that the computer may be used in handling the data. By compiling statistics of the distribution of houses it is now possible to get an overview.
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Histogram
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| The histogram shows the spread of data in the chorological matrix.
On the basis of the histogram, the image data can be divided into different classes.
The illustration shows two examples of classifications based on the histogram shown: One classification has four classes (agriculture, village, town and other) and another classification in two classes (rural and town)
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| As the basis of the chorological matrix a regular grid can be used to plot the number of houses in each square eg (0,1,2,...etc.) Such a grid can be based on geographical coordinates or on the UTM coordinate system. The gridsize has to be defined. In a UTM grid it might be 100m or 10km depending on the scale of the map and the distribution of the features to be mapped. The histogram overview provides the basis for defining meaningful clusters (classes): squares with 0 houses might, for example, be defined as forest and recreational areas, squares with 1 to 7 houses as agricultural areas, squares with 8 to 11 houses might be defined as villages and squares with more than 11 houses as towns.
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Classification
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| It is up to the cartographer to decide upon a suitable classification depending on the purpose of the map. Classifications are always open to debate and the same chorological matrix may form the basis of many different maps. The selected classification is placed in the histogram and each class is given hatching, grey shading or colours. The squares in the grid are hatched according to their classification (number of houses) and this produces a thematic map.
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| Classifications often require compromise - eg in the case of four classes a suburban area is assigned the status of a village. The number of classes is important. Having a classification system with many classes enables a high degree of detail so that fine distinctions between the squares can be discerned, whereas detail can be lost if the squares are grouped in too few (large) classes.
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Digital images
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| A digital image is a chorological matrix. The size of the squares in the grid is equal to the spatial resolution of the (satellite) image and depend upon the instrument providing the data. Similarly the numbers in the grid are determined by the ability of the equipment to distinguish variations. Digital images often contain values between 0 and 255, which are matched exactly by the capacity of 1 byte in the computer.
The chorological matrix is loaded into the computer and the individual squares in the grid are represented by a dot on the screen, a pixel (= picture element). The numerical value in each matrix square is referred to the corresponding pixel-position with a (x,y) coordinates. Every pixel is given a grey shading corresponding to the pixel value. Now the matrix will appear on the screen as an image or a thematic map.
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| Since many years, maps have been based on aerial photography where the single aerial photograph could function as maps immediately. However, todays scanners on aeroplanes and in satellites are used increasingly to measure the amount of electromagnetic radiation from the surface in many small area units areas (pixels in the image).
Each scanned unit area is given a number corresponding to the amount of radiation. If the geographical coordinates of each unit area are also known, a chorological matrix is produced. Such a matrix may be subject to calculations to have it map-like displayed. In such an operation new row and column positions have to be calculated and the corresponding pixel value assigned. At this point these values have to be interpolated, thus slightly changed.
Such a matrix may be manipulated endlessly, with other data sources/maps added, subtracted, multiplied and divided. These techniques are called digital image processing and they are employed in handling the large chorological matrices resulting from remote sensing via satellites.
Today this type of data is an essential source of mapping. Remote sensing and digital image processing are quick and inexpensive techniques which help secure the latest up-to-date maps and they are necessary tools in the search for real-time local and global mapping of environmental changes.
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