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I have sf data frame with refugee camps / populations across sub-Saharan Africa from 2009-2018. I created 50KM buffers around each camp for analysis, and am using that file for analysis buffer_shp

data <- data.frame(country = rep(c("Angola", "DRC", "Uganda"), each = 10),
                   location = rep(c("Luanda", "Kilueka", "Adjumani"), each = 10),
                   year = rep(2009:2018, times = 3),
                   population = sample(10000:50000, 30, replace = TRUE),
                   lon = c(13.23294531, 14.47044, 31.7905912),
                   lat = c(-8.815191647, -5.42059, 3.3769442))

data$lon[data$location == "Luanda"] <- 13.23294531
data$lat[data$location == "Luanda"] <- -8.815191647

data$lon[data$location == "Kilueka"] <- 14.47044
data$lat[data$location == "Kilueka"] <- -5.42059

data$lon[data$location == "Adjumani"] <- 31.7905912
data$lat[data$location == "Adjumani"] <- 3.3769442

data_sf <- st_as_sf(data, coords = c("lon", "lat"), crs = 4326)

buffer_shp <- data_sf %>%
  st_transform("ESRI:102022") %>%
  st_buffer(dist = 100000) 

## I make an extra buffer item, so that I don't have to keep creating the original if there are mistakes

buffer_shp2 <- buffer_shp %>%
  mutate(ID = seq_len(nrow(.)))

I also have 10 raster files showing rainfall per year. I am trying to find the mean value of the cells that intersect the polygon for each location, every year. I want to create a new column in buffer_shp2 called 'CHIRPS_mean' that tracks the resulting mean value for the intersection. I have tried so many different things and I just cannot get it to work.

Iteration 1:

# List with all my rasters (Could this be a stack?)
CHIRPS_annual_list <- list(CHIRPS_annual_2009, CHIRPS_annual_2010, 
                           CHIRPS_annual_2011, CHIRPS_annual_2012, 
                           CHIRPS_annual_2013, CHIRPS_annual_2014, 
                           CHIRPS_annual_2015, CHIRPS_annual_2016,
                           CHIRPS_annual_2017, CHIRPS_annual_2018)

years <- 2009:2018
  
for (year in 2009:2018){
  
  # Get the corresponding raster
  raster_name <- paste0("CHIRPS_annual_", year)
  raster_brick <- get(raster_name)
  raster_brick[raster_brick == -9999] <- NA

  # Filter buffer shapefile to the current year
  buffer_year <- buffer_shp2 %>%
    dplyr::filter(Year == year)
  
  # Empty dataframe to store values
  intersection_df <- data.frame(ID = numeric(), Year = numeric(), CHIRPS_mean = numeric())
  
  # Loop through each row in the buffer shapefile, finding intersection
  for (i in 1:nrow(buffer_year)) {
    buffer_row <- buffer_year[i,]
    intersection <- extract(raster_brick, buffer_row, fun = mean, na.rm = TRUE)
    new_row <- data.frame(ID = buffer_row$ID,
                          Year = year,
                          CHIRPS_mean = intersection)

    # Add the intersection value to the dataframe
    intersection_df <- rbind(intersection_df, new_row)
    buffer_shp2 <- left_join(buffer_shp2, intersection_df, by = c("ID", "Year"))
  }

This results in something along the lines of the following, it seems to create a new column for each year and location.

output = CHIRPS_mean.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y. ...
     CHIRPS_mean.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x. ...
     CHIRPS_mean.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y.y. ...
     CHIRPS_mean.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x.x. ...

If I move the rbind and left_join outside the loop, it then doesn't do it for every year. I seem to be able to figure it out if it is just one year, but I am not sure how to process through the for-loop. Any help would be appreciated.

I have spent hours on this and am incredibly stuck. Thank you in advance.

Victoria Puglia
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