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
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