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Nearest Neighbour Analysis Settlement Geography

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Learning outcomes To study the nearest neighbour analysis and how it determines patterns of settlements To study the nearest neighbour analysis and how it determines patterns of settlements

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Nearest Neighbour Analysis Settlements often appear on maps as dots Settlements often appear on maps as dots The patterns of these dots are difficult to describe The patterns of these dots are difficult to describe Sometimes patterns are obvious: Sometimes patterns are obvious: Nucleated Nucleated Dispersed Dispersed However the pattern is likely to lie between these two extremes However the pattern is likely to lie between these two extremes Nearest neighbour helps to determine the pattern Nearest neighbour helps to determine the pattern

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The technique Was devised by a botanist to determine plant distributions Was devised by a botanist to determine plant distributions Allows one region to be compared to another Allows one region to be compared to another It is only a technique and offers no explanation of patterns It is only a technique and offers no explanation of patterns

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Formula The formula is The formula is Rn= 2đ n/A Rn= 2đ n/A Rn= The description of the distribution Rn= The description of the distribution đ = The mean distance between the nearest neighbours đ = The mean distance between the nearest neighbours n= the number of settlements in the study area n= the number of settlements in the study area A= the area under study (km) A= the area under study (km)

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Rn Rn is the description of the settlement distribution Rn is the description of the settlement distribution This can be as follows: This can be as follows: Clustering- where dots are very close together. In extreme cases the value of Rn=0 Clustering- where dots are very close together. In extreme cases the value of Rn=0 Random- distributions occur where there is no pattern at all. Rn= 1 Random- distributions occur where there is no pattern at all. Rn= 1 Regular- these are perfectly uniform. If ever found in reality they would have a value of 2.15 Regular- these are perfectly uniform. If ever found in reality they would have a value of 2.15

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Nearest Neighbour values See page 402 in Waugh See page 402 in Waugh

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