I’m looking for help in disaggregating some spatial data into smaller grid cells.

structure(list(GEOID = c("17031010100", "17031010200"), NAME.x = c("Census Tract 101, Cook County, Illinois", 
"Census Tract 102, Cook County, Illinois"), median_inc = c(30708, 
35932), pop = c(4835, 8830), share25_edu = c(17.1124828532236, 
21.5430163706026), pop_poverty = c(1719, 2139), share_poverty = c(35.5532574974147, 
24.2242355605889), median_age = c(30.3, 32.6), geometry = structure(list(
    structure(list(list(structure(c(-87.677765, -87.678074, -87.675257, 
    -87.673257, -87.672251, -87.671657, -87.668657, -87.668657, 
    -87.666357, -87.6650920979757, -87.6662895604484, -87.6665966344484, 
    -87.67245, -87.677357, -87.677765, 42.02303, 42.023011, 42.020531, 
    42.019231, 42.019294, 42.019331, 42.019431, 42.019231, 42.019231, 
    42.0193213501446, 42.0223445264575, 42.0231197815191, 42.023031, 
    42.02303, 42.02303), dim = c(15L, 2L)))), class = c("XY", 
    "MULTIPOLYGON", "sfg")), structure(list(list(structure(c(-87.676457, 
    -87.679457, -87.680757, -87.683157, -87.684958, -87.684557, 
    -87.683957, -87.683357, -87.680457, -87.678457, -87.674857, 
    -87.672657, -87.670557, -87.670657, -87.670657, -87.670757, 
    -87.671557, -87.671657, -87.672251, -87.673257, -87.676457, 
    42.019131, 42.019531, 42.019531, 42.019431, 42.019431, 42.016431, 
    42.014131, 42.012331, 42.012531, 42.012631, 42.012731, 42.012731, 
    42.012731, 42.013931, 42.016031, 42.018331, 42.018031, 42.019331, 
    42.019294, 42.019231, 42.019131), dim = c(21L, 2L)))), class = c("XY", 
    "MULTIPOLYGON", "sfg"))), class = c("sfc_MULTIPOLYGON", "sfc"
), precision = 0, bbox = structure(c(xmin = -87.684958, ymin = 42.012331, 
xmax = -87.6650920979757, ymax = 42.0231197815191), class = "bbox"), crs = structure(list(
    input = "EPSG:4326", wkt = "GEOGCRS["WGS 84",n    ENSEMBLE["World Geodetic System 1984 ensemble",n        MEMBER["World Geodetic System 1984 (Transit)"],n        MEMBER["World Geodetic System 1984 (G730)"],n        MEMBER["World Geodetic System 1984 (G873)"],n        MEMBER["World Geodetic System 1984 (G1150)"],n        MEMBER["World Geodetic System 1984 (G1674)"],n        MEMBER["World Geodetic System 1984 (G1762)"],n        MEMBER["World Geodetic System 1984 (G2139)"],n        ELLIPSOID["WGS 84",6378137,298.257223563,n            LENGTHUNIT["metre",1]],n        ENSEMBLEACCURACY[2.0]],n    PRIMEM["Greenwich",0,n        ANGLEUNIT["degree",0.0174532925199433]],n    CS[ellipsoidal,2],n        AXIS["geodetic latitude (Lat)",north,n            ORDER[1],n            ANGLEUNIT["degree",0.0174532925199433]],n        AXIS["geodetic longitude (Lon)",east,n            ORDER[2],n            ANGLEUNIT["degree",0.0174532925199433]],n    USAGE[n        SCOPE["Horizontal component of 3D system."],n        AREA["World."],n        BBOX[-90,-180,90,180]],n    ID["EPSG",4326]]"), class = "crs"), n_empty = 0L)), row.names = c(NA, 
-2L), tigris = "tract", sf_column = "geometry", agr = structure(c(GEOID = NA_integer_, 
NAME.x = NA_integer_, median_inc = NA_integer_, pop = NA_integer_, 
share25_edu = NA_integer_, pop_poverty = NA_integer_, share_poverty = NA_integer_, 
median_age = NA_integer_), class = "factor", levels = c("constant", 
"aggregate", "identity")), class = c("sf", "tbl_df", "tbl", "data.frame"
))

variable_tracts has data on certain variables for all census tracts in Cook County, IL. I’m interested in those located within Chicago, which i find by

chi_tracts <- variables_tract |> 
  st_filter(chi_map)

where

chi_map_comm <- read_sf("https://raw.githubusercontent.com/thisisdaryn/data/master/geo/chicago/Comm_Areas.geojson") 
chi_map <- st_union(chi_map_comm)

This leaves roughly 800 census tracts.

**What i want to do **

I want to disaggregate all the census tracts in chi_tracts to smaller grid cells. I want to get the geometries of every grid cell.

I’m concerned about how long this process might take – 800 census tracts is a lot.

I’m pretty lost here as to how I can approach this, so any help would be appreciated! I apologize if the formatting isn’t correct – i’m not very experienced on this forum.

I tried the following code which is shamelessly taken from chatgpt, this code runs for a long time to no avail:

split_into_grid <- function(tract, cellsize) {
  grid <- st_make_grid(tract, cellsize = 0.01, what = "polygons", square = TRUE) |> 
    st_as_sf()  
 grid <- st_intersection(grid, tract)  
 grid <- grid |> 
    mutate(
      median_inc = tract$median_inc,         
      share25_edu = tract$share25_edu,       
      pop = tract$pop / nrow(grid), 
      share_poverty = tract$share_poverty,             
      median_age = tract$median_age     
    )
  
  return(grid) 
}

cell_size <- 0.01  


chi_grid <- chi_tracts |> 
  group_split() |> 
  map_dfr(~split_into_grid(.x, cell_size))