Nearest Neighbour in R

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Package in use: "spatstat"

Data:

> title <- c("Name", "X", "Y", "Surface", "Date", "Temprature")> GWT <- read.csv2("E:\\Slides\\Geostatistics & Geomarketing(Nein)\\data\\Groundwater_Temperature.csv", header = TRUE, sep = ",", dec = ".", col.names = title)> GWT_sub <- subset(GWT, subset = (GWT$Surface >0))> head(GWT_sub)     Name       X       Y Surface    Date Temprature1 ABP9922 4459725 5340978  497.50 7/25/09        9.92 ABP9926 4460005 5341246  498.90 7/25/09       12.03   BP 25 4464282 5331784  534.17 7/26/09        9.94   BP 26 4464222 5330721  542.08 7/27/09       10.55   BP 32 4460921 5337893  509.09 7/25/09       11.66   BP 49 4463843 5339414  501.50 7/24/09       11.3

Creat a point pattern dataset with function ppp.

> Xgwt_subset <- ppp(GWT_sub$X, GWT_sub$Y, window = owin(c(min(GWT_sub$X), max(GWT_sub$X)), c(min(GWT_sub$Y), max(GWT_sub$Y))), marks = GWT_sub$Temperature)> plot(Xgwt_subset)> plot(Xgwt_subset, main = "GWT")

Calculating neighbors of each points. M means that, the 85th point is neighbor of the 1st point, 170th point is the nearest neighbor of 2ed point. b is another dataset for every points' neighbors.

> m <- nnwhich(GWT_sub$X, GWT_sub$Y)> m  [1]   2   1 407 411 257 143 319  14  13  80  12  11   9   8  44  53 107 104 329   6 [21] 102 268 198 194 284 233 233 170 142  19 299 278  47 159  25 291 131  39  40  39... ...> b <- GWT_sub[m, ]

Displaying.

> arrows(GWT_sub$X, GWT_sub$Y, b$X, b$Y, col = "red", length = 0.06)

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