[R] Selecting a minimum value of an attribute associated with point values neighboring a given point and assigning it as a new attribute

[Duhl, Tiffany R.]

Hello,

I have sets of spatial points with LAT, LON coords (unprojected, WGS84 datum) and several value attributes associated with each point, from numerous csv files (with an average of 6,000-9,000 points in each file) as shown in the following example:

data<- read.csv("R_find_pts_testdata.csv")

> data
    ID      Date         Time        LAT            LON           Conc    Leg.Speed    CO2  H2O BC61 Hr Min Sec
1   76 4/19/2021 21:25:38 42.40066 -70.98802 99300   0.0 mph 428.39 9.57  578 21  25  38
2   77 4/19/2021 21:25:39 42.40066 -70.98802 96730   0.0 mph 428.04 9.57  617 21  25  39
3   79 4/19/2021 21:25:41 42.40066 -70.98802 98800   0.2 mph 427.10 9.57 1027 21  25  41
4   80 4/19/2021 21:25:42 42.40066 -70.98802 96510     2 mph 427.99 9.58 1381 21  25  42
5   81 4/19/2021 21:25:43 42.40067 -70.98801 95540     3 mph 427.99 9.58 1271 21  25  43
6   82 4/19/2021 21:25:44 42.40068 -70.98799 94720     4 mph 427.20 9.57  910 21  25  44
7   83 4/19/2021 21:25:45 42.40069 -70.98797 94040     5 mph 427.18 9.57  652 21  25  45
8   84 4/19/2021 21:25:46 42.40072 -70.98795 95710     7 mph 427.07 9.57  943 21  25  46
9   85 4/19/2021 21:25:47 42.40074 -70.98792 96200     8 mph 427.44 9.56  650 21  25  47
10  86 4/19/2021 21:25:48 42.40078 -70.98789 93750    10 mph 428.76 9.57  761 21  25  48
11  87 4/19/2021 21:25:49 42.40081 -70.98785 93360    11 mph 429.25 9.56 1158 21  25  49
12  88 4/19/2021 21:25:50 42.40084 -70.98781 94340    12 mph 429.56 9.57  107 21  25  50
13  89 4/19/2021 21:25:51 42.40087 -70.98775 92780    12 mph 428.62 9.56  720 21  25  51


What I want to do is, for each point, identify all points within 50m of that point, find the minimum value of the "Conc" attribute of each nearby set of points (including the original point) and then create a new variable ("Conc_min") and assign this minimum value to a new variable added to "data".

So far, I have the following code:

library(spdep)
library(sf)

setwd("C:\\mydirectory\\")
data<- read.csv("R_find_pts_testdata.csv")

#make sure the data is a data frame
pts <- data.frame(data)

#create spatial data frame and define projection
pts_coords <- cbind(pts$LON, pts$LAT)
data_pts <- SpatialPointsDataFrame(coords= pts_coords,
data=pts, proj4string = CRS("+proj=longlat +datum=WGS84"))

#Re-project to WGS 84 / UTM zone 18N, so the analysis is in units of m
ptsUTM  <- sf::st_as_sf(data_pts, coords = c("LAT", "LON"), remove = F)%>% st_transform(32618)

#create 50 m buffer around each point then intersect with points and finally find neighbors within the buffers
pts_buf <- sf::st_buffer(ptsUTM, 50)
coords  <- sf::st_coordinates(ptsUTM)
int <- sf::st_intersects(pts_buf, ptsUTM)
x   <- spdep::dnearneigh(coords, 0, 50)

Now at this point, I'm not sure what to either the "int" (a sgbp list) or "x" (nb object) objects (or even if I need them both)

> int
Sparse geometry binary predicate list of length 974, where the predicate was `intersects'
first 10 elements:
 1: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 2: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 3: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 4: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 5: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 6: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 7: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 8: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...
 9: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, ...

> x
Neighbour list object:
Number of regions: 974
Number of nonzero links: 34802
Percentage nonzero weights: 3.668481
Average number of links: 35.73101

One thought is that maybe I don't need the dnearneigh function and can instead convert "int" into a dataframe and somehow merge or associate (perhaps with an inner join) the ID fields of the buffered and intersecting points and then compute the minimum value of "Conc" grouping by ID:

> as.data.frame(int)
    row.id col.id
1        1      1
2        1      2
3        1      3
4        1      4
5        1      5
6        1      6
7        1      7
8        1      8
9        1      9
10       1     10
11       1     11
12       1     12
13       1     13
14       1     14
15       1     15
16       1     16
17       1     17
18       1     18
19       2      1
20       2      2
21       2      3
22       2      4
23       2      5
24       2      6
25       2      7
26       2      8
27       2      9
28       2     10


So in the above example I'd like to take the minimum of "Conc" among the col.id points grouped with row.id 1 (i.e., col.ids 1-18) and assign the  minimum value of this group as a new variable in data (Data$Conc_min), and do the same for row.id 2 and all the rest of the rows.

I'm just not sure how to do this and I appreciate any help folks might have on this matter!

Many thanks,
-Tiffany

	[[alternative HTML version deleted]]