Understanding Nearest Neighbour Index in Geographical Analysis
The Nearest Neighbour Index (NNI) is a valuable tool in analyzing the spatial distribution pattern of geographical features by examining the distance between points. Discover how NNI values between 0 and 2.15 indicate clustered, random, or even distributions and learn how to calculate NNI to assess distribution patterns effectively.
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Presentation Transcript
A. Nearest neighbour index The nearest neighbour index (??) describes the distribution pattern of points The points represent particular geographical features ? ?, ??= ? ? where ? = mean distance to the nearest neighbour, ? = number of points in the study site, ? = area of the study site
A. Nearest neighbour index The value of Rnlies between 0 and 2.15 It tells us whether the geographical features have a clustered, random or even distribution Values and meanings of the nearest neighbor index
A. Nearest neighbour index Calculation steps: Distribution of trees at a place
A. Nearest neighbour index Find out the nearest neighbour for each tree, and measure the distance to the nearest neighbour. Nearest neighbour Distance to the nearest neighbour (m) (d) Tree A C 40 B C 30 C D 20 D C 20 E H 30 F G 20 G F 20 H E 30
A. Nearest neighbour index Calculate the mean distance to the nearest neighbor ( ?). ?? + ?? + ?? + ?? + ?? + ?? + ?? + ?? ? ? ? = = ??.??? Calculate the area of the study site (A). ? = ???? ???? = ??,????? Calculate the nearest neighbour index (R Rn n). 8 8 R Rn n= = 2 2 26.25 = ?.?? The trees in the figure tend to be randomly distributed. 26.25 10,000 10,000
A. Nearest neighbour index The nearest neighbor index quantifies the spatial distribution pattern for the ease of analysis It can be applied to the following studies: The distribution pattern of various phenomena or activities in a particular study site The difference in distribution pattern of a particular phenomenon or activity in two study sites of similar size The temporal variation of distribution pattern of a particular phenomenon or activity in a particular study site
A. Nearest neighbour index However, the analysis result is easily affected by the size of study site It the phenomena or activities are clustered at a few highly separated areas, the index may not be able to reflect the situation It only considers the relationship between each point and its nearest neighbour But it does not consider an overview of the distribution pattern of all points
A. Nearest neighbour index Take the figure below as an example Distance to the nearest neighbour (m) (d) Car park Nearest neighbour A B 25 B A 25 C D 25 D C 25 E F 25 Distribution of car parks in Region A F E 25
A. Nearest neighbour index ?? + ?? + ?? + ?? + ?? + ?? ? ? ? = = ??? ? = ???? ???? = ??,????? 6 6 500 R Rn n= = 2 2 26.25 = ?.?? The distribution of car parks in Region A tends to be clustered However, the car parks are indeed agglomerated in three locations Since the index only calculates the distance of each car park to its closest neighbour, it cannot reflect the relationship among all car parks 26.25 62 62, ,500
