[R] How to average values from grid cells with coordinates

[Jim Lemon]

Hi lily,
You could also create "blackcells" as a dataframe (which is itself a
type of list). I used a list as I thought it would be a more general
solution if there were different numbers of values for different grid
cells. The use of 1 for the comparison was due to the grid increments
being 1. If you had larger or smaller grid increments, you would use
the grid increment size for the comparison. That guarantees that only
the four nearest "black" cells will be identified as within the "red"
cell.

Jim

On Sat, May 19, 2018 at 4:07 AM, lily li <chocold12 using gmail.com> wrote:
> Hi Jim,
>
> Thanks. Yes, the two assumptions are correct, and they reflect the datasets.
> I have an uncertainty about the code below. Why do you use
> abs(blackcells[[i]]$lat - redcell$lat) <1 rather than a different number
> than 1? Second, why to construct blackcells as a list, rather than a
> dataframe. Because in a dataframe, each row can represent one grid cell,
> while the three columns can represent the lati, lon, and pop. Thanks again
> for your help.
>
> for(i in 1:121) {
> if(abs(blackcells[[i]]$lat-redcell$lat) < 1 &&
> abs(blackcells[[i]]$lon-redcell$lon) < 1) {
> close4[closen]<-i
> closen<-closen+1
> }
> }
>
> On Wed, May 16, 2018 at 2:45 AM, Jim Lemon <drjimlemon using gmail.com> wrote:
>>
>> Hi lily,
>> There are one or two assumptions to be made here. First is that the
>> latitude and longitude values of the "black" cells are equally spaced
>> as in your illustration. Second, that all latitude and longitude
>> values for the "red" cells fall at the corners of four "black" cells.
>>
>> You can get the four "black" cells by finding the lat/lon values that
>> are closest to the "red" lat/lon values. Here's a basic example:
>>
>> lat<-rep(28:38,11)
>> lon<-rep(98:108,each=11)
>> pop<-sample(80:200,121)
>> blackcells<-list()
>> for(i in 1:121) blackcells[[i]]<-list(lat=lat[i],lon=lon[i],pop=pop[i])
>> redcell<-list(lat=33.5,lon=100.5,pop=NA)
>> close4<-rep(NA,4)
>> closen<-1
>> for(i in 1:121) {
>>  if(abs(blackcells[[i]]$lat-redcell$lat) < 1 &&
>>   abs(blackcells[[i]]$lon-redcell$lon) < 1) {
>>   close4[closen]<-i
>>   closen<-closen+1
>>  }
>> }
>> cat(close4,"\n")
>> redcell$pop<-(blackcells[[close4[1]]]$pop +
>>  blackcells[[close4[2]]]$pop + blackcells[[close4[3]]]$pop +
>>  blackcells[[close4[4]]]$pop)/4
>> print(blackcells[[close4[1]]])
>> print(blackcells[[close4[2]]])
>> print(blackcells[[close4[3]]])
>> print(blackcells[[close4[4]]])
>> print(redcell)
>>
>> As you can see, this has picked out the four "black" cells closest to
>> the "red" cell's coordinates and calculated the mean.
>>
>> Jim
>>
>> On Wed, May 16, 2018 at 2:23 PM, lily li <chocold12 using gmail.com> wrote:
>> > Hi R users,
>> >
>> > I have a question about data processing. I have such a dataset, while
>> > each
>> > black grid cell has a few attributes and the corresponding attribute
>> > values. The latitude and longitude of the center of each grid cell are
>> > given also.
>> >
>> > Then I want to average the attribute values from four adjacent grid
>> > cells
>> > to get the average value for the center of each red grid cell. Thus,
>> > there
>> > are the same number of attributes, but different values. The red grid
>> > cells
>> > do not overlap. I was thinking to write such a script that can ID each
>> > black grid cell, for example, 1, 2, 3, 4, ..., then the corresponding
>> > four
>> > grid cells will be used to average for the red grid cell. But I just
>> > have
>> > the latitude and longitude, attribute values for the black cells, and
>> > also
>> > latitude and longitude for the red cells, how to write such a script in
>> > R.
>> > Could anyone give me suggestion about the work flow? Thanks very much.
>> >
>> > I attached the picture of the grid cells here.
>> >
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>> >
>
>