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Ntl v2 #83

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Ntl v2 #83

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68ae3fc
cleanup
ramarty Oct 24, 2023
17ad8c0
Merge branch 'main' of https://github.com/datapartnership/syria-econo…
ramarty Oct 24, 2023
4c688ab
ntl update
ramarty Nov 6, 2023
47303d9
Merge branch 'main' of https://github.com/datapartnership/syria-econo…
ramarty Nov 6, 2023
3b29b39
update
ramarty Nov 6, 2023
b7faaaf
fix figure names
ramarty Nov 7, 2023
328969d
new ntl maps
ramarty Nov 7, 2023
9735862
adm0
ramarty Nov 7, 2023
5d4f45d
map all country
ramarty Nov 13, 2023
bf3e092
Merge branch 'main' into ntl-v2
g4brielvs Nov 20, 2023
04a39da
additional map
ramarty Nov 20, 2023
53f259e
up
ramarty Nov 20, 2023
18a431b
fix merge
ramarty Nov 20, 2023
dd2115c
updated NTL analysis
ramarty Oct 11, 2024
4834518
monthly adjust
ramarty Oct 11, 2024
294d13f
update
ramarty Nov 8, 2024
ddb82ec
ntl
ramarty Nov 15, 2024
6343c6e
ntl
ramarty Dec 20, 2024
7b3a20f
ntl
ramarty Dec 20, 2024
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24 changes: 18 additions & 6 deletions notebooks/ntl-analysis/01_clean_data/02_download_black_marble.R
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Original file line number Diff line number Diff line change
Expand Up @@ -9,26 +9,33 @@ bearer <- read_csv("~/Desktop/bearer_bm.csv") %>% pull(token)
##### Region of Interest

## Polygon around Syria and Turkey
syr_sp <- getData('GADM', country='SYR', level=0)
tur_sp <- getData('GADM', country='TUR', level=0)
syr_sp <- gadm(country = "SYR", level=1, path = tempdir()) |> st_as_sf()
tur_sp <- gadm(country = "TUR", level=1, path = tempdir()) |> st_as_sf()

# Combine Syria and Turkey into one polygon
roi_sp <- rbind(syr_sp, tur_sp)
roi_sp$id <- 1
roi_sp <- raster::aggregate(roi_sp, by = "id")
roi_sf <- roi_sp %>% st_as_sf()
roi_sf <- roi_sp %>% st_as_sf() #%>% st_combine()

# Download annual data --------------------------------------------------------
dir.create(file.path(data_dir,
"NTL BlackMarble",
"FinalData",
"annual_rasters"))
bm_raster(roi_sf = roi_sf,
product_id = "VNP46A4",
date = 2012:2022,
date = 2012:2023,
bearer = bearer,
output_location_type = "file",
file_dir = file.path(data_dir,
"NTL BlackMarble",
"FinalData",
"annual_rasters"))

dir.create(file.path(data_dir,
"NTL BlackMarble",
"FinalData",
"monthly_rasters"))
bm_raster(roi_sf = roi_sf,
product_id = "VNP46A3",
date = seq.Date(from = ymd("2012-01-01"), to = Sys.Date(), by = "month") %>% rev(),
Expand All @@ -39,15 +46,20 @@ bm_raster(roi_sf = roi_sf,
"FinalData",
"monthly_rasters"))

dir.create(file.path(data_dir,
"NTL BlackMarble",
"FinalData",
"daily_rasters"))
bm_raster(roi_sf = roi_sf,
product_id = "VNP46A2",
date = seq.Date(from = ymd("2022-01-01"), to = Sys.Date(), by = "day") %>% rev(),
bearer = bearer,
variable = "Gap_Filled_DNB_BRDF-Corrected_NTL",
quality = NULL,
output_location_type = "file",
file_dir = file.path(data_dir,
"NTL BlackMarble",
"FinalData",
"daily_rasters"))



79 changes: 5 additions & 74 deletions notebooks/ntl-analysis/01_clean_data/03_border_xing_aggregate.R
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Original file line number Diff line number Diff line change
Expand Up @@ -32,10 +32,9 @@ ntl_monthly_df <- map_df(monthly_files, function(file_i){

# Add date info
bc_df$date <- file_i %>%
str_replace_all("VNP46A3_t", "") %>%
str_replace_all(".*qflag_t", "") %>%
str_replace_all(".tif", "") %>%
str_replace_all("_", "-") %>%
paste0("-01") %>%
paste0("-01") %>%
ymd()

#### Merge NTL with GADM data
Expand All @@ -47,41 +46,6 @@ ntl_monthly_df <- map_df(monthly_files, function(file_i){
write_csv(ntl_monthly_df, file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_monthly.csv"))
saveRDS(ntl_monthly_df, file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_monthly.Rds"))

# for(file_i in rev(monthly_files)){
#
# OUT_FILE <- file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_temp",
# "monthly_files",
# paste0("syr_border_xing_",
# file_i %>% str_replace_all(".tif", ".Rds")))
#
# if(!file.exists(OUT_FILE)){
#
# print(file_i)
#
# r <- rast(file.path(ntl_bm_dir, "FinalData", paste0("monthly", "_rasters"), file_i))
#
# bc_df <- bc_sf
# bc_df$geometry <- NULL
# bc_df$viirs_bm_mean <- exact_extract(r, bc_sf, 'mean')
# bc_df$viirs_bm_sum <- exact_extract(r, bc_sf, 'sum')
# bc_df$viirs_bm_median <- exact_extract(r, bc_sf, 'median')
#
# # Add date info
# bc_df$date <- file_i %>%
# str_replace_all("VNP46A3_t", "") %>%
# str_replace_all(".tif", "") %>%
# str_replace_all("_", "-") %>%
# paste0("-01") %>%
# ymd()
#
# #### Merge NTL with GADM data
# bc_df$viirs_bm_mean[bc_df$viirs_bm_sum == 0] <- 0
#
# # Export -----------------------------------------------------------------------
# saveRDS(bc_df, OUT_FILE)
# }
# }

# Daily ------------------------------------------------------------------------
daily_files <- list.files(file.path(ntl_bm_dir, "FinalData", paste0("daily", "_rasters")))

Expand All @@ -97,50 +61,17 @@ ntl_daily_df <- map_df(daily_files, function(file_i){

# Add date info
bc_df$date <- file_i %>%
str_replace_all("VNP46A2_t", "") %>%
str_replace_all(".*qflag_t", "") %>%
str_replace_all(".tif", "") %>%
str_replace_all("_", "-") %>%
ymd()

#### Merge NTL with GADM data
bc_df$viirs_bm_mean[bc_df$viirs_bm_sum == 0] <- 0
bc_df$viirs_bm_mean[bc_df$viirs_bm_sum == 0] <- 0

return(bc_df)
})

write_csv(ntl_daily_df, file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_daily.csv"))
saveRDS(ntl_daily_df, file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_daily.Rds"))
write_dta(ntl_daily_df, file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_daily.dta"))

# for(file_i in rev(daily_files)){
#
# OUT_FILE <- file.path(ntl_bm_dir, "FinalData", "aggregated", "border_xing_temp",
# "daily_files",
# paste0("syr_border_xing_",
# file_i %>% str_replace_all(".tif", ".Rds")))
#
# if(!file.exists(OUT_FILE)){
#
# print(file_i)
#
# r <- rast(file.path(ntl_bm_dir, "FinalData", paste0("daily", "_rasters"), file_i))
#
# bc_df <- bc_sf
# bc_df$geometry <- NULL
# bc_df$viirs_bm_mean <- exact_extract(r, bc_sf, 'mean')
# bc_df$viirs_bm_sum <- exact_extract(r, bc_sf, 'sum')
#
# # Add date info
# bc_df$date <- file_i %>%
# str_replace_all("VNP46A2_t", "") %>%
# str_replace_all(".tif", "") %>%
# str_replace_all("_", "-") %>%
# ymd()
#
# #### Merge NTL with GADM data
# bc_df$viirs_bm_mean[bc_df$viirs_bm_sum == 0] <- 0
#
# # Export -----------------------------------------------------------------------
# saveRDS(bc_df, OUT_FILE)
# }
# }
#
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