init ntl

notebooks/nighttime-lights/01_download_ntl.R

@@ -11,7 +11,7 @@ roi_sf <- read_sf(file.path(boundaries_dir, "ner_adm_ignn_20230720_ab_shp",
 ## Download data
 annual_r <- bm_raster(roi_sf = roi_sf,
                       product_id = "VNP46A4",
-                      date = 2012,
+                      date = 2012:2023,
                       bearer = bearer,
                       output_location_type = "file",
                       file_dir = file.path(ntl_dir, 
@@ -29,7 +29,7 @@ month_r <- bm_raster(roi_sf = roi_sf,
 
 day_r <- bm_raster(roi_sf = roi_sf,
                    product_id = "VNP46A2",
-                   date = seq.Date(from = ymd("2024-01-01"), to = ymd("2024-01-12"), by = "day"),
+                   date = seq.Date(from = ymd("2023-01-01"), to = Sys.Date(), by = "day"),
                    bearer = bearer,
                    output_location_type = "file",
                    file_dir = file.path(ntl_dir, 

notebooks/nighttime-lights/02_extract_data.R

@@ -0,0 +1,109 @@
+# Extract data
+
+AGG_FUNS <- c("mean", "sum")
+
+# Load ROIs --------------------------------------------------------------------
+adm0_sf <- read_sf(file.path(boundaries_dir, "ner_adm_ignn_20230720_ab_shp", 
+                             "NER_admbnda_adm0_IGNN_20230720.shp"))
+adm1_sf <- read_sf(file.path(boundaries_dir, "ner_adm_ignn_20230720_ab_shp", 
+                             "NER_admbnda_adm1_IGNN_20230720.shp"))
+adm2_sf <- read_sf(file.path(boundaries_dir, "ner_adm_ignn_20230720_ab_shp", 
+                             "NER_admbnda_adm1_IGNN_20230720.shp"))
+adm3_sf <- read_sf(file.path(boundaries_dir, "ner_adm_ignn_20230720_ab_shp", 
+                             "NER_admbnda_adm1_IGNN_20230720.shp"))
+
+city_df      <- read.csv(file.path(city_dir, "niger_cities.csv"))
+city_sf      <- st_as_sf(city_df, coords = c("longitude", "latitude"), crs = 4326)
+city_buff_sf <- city_sf %>% st_buffer(dist = 10*1000)
+
+# Extract individual files -----------------------------------------------------
+
+#### Loop through unit
+for(unit in c("adm0", "adm1", "adm2", "adm3", "city")){
+
+  dir.create(file.path(ntl_dir, "aggregated_individual", unit))
+
+  if(unit == "adm0") unit_sf <- adm0_sf
+  if(unit == "adm1") unit_sf <- adm1_sf
+  if(unit == "adm2") unit_sf <- adm2_sf
+  if(unit == "adm3") unit_sf <- adm3_sf
+  if(unit == "city") unit_sf <- city_buff_sf
+
+  #### Loop through time period
+  for(time_period in c("annually", "monthly", "daily")){
+
+    dir.create(file.path(ntl_dir, "aggregated_individual", unit, time_period))
+
+    files_vec <- file.path(ntl_dir, 
+                           "individual_rasters",
+                           time_period) %>%
+      list.files(full.names = T)
+
+    #### Loop through dates
+    for(file_i in files_vec){
+
+      date_i <- file_i %>%
+        str_replace_all(".*qflag_t", "") %>%
+        str_replace_all(".tif", "")
+
+      OUT_DIR <- file.path(ntl_dir, "aggregated_individual", unit, time_period,
+                           paste0(date_i, ".Rds"))
+
+      #### Extract data
+      if(!file.exists(OUT_DIR)){
+
+        r <- terra::rast(file_i)
+
+        ntl_df <- exact_extract(r, unit_sf, fun = AGG_FUNS)
+        names(ntl_df) <- paste0("ntl_", names(ntl_df))
+        ntl_df$date <- date_i
+
+        unit_df <- unit_sf %>%
+          st_drop_geometry()
+        unit_df$date <- NULL
+
+        ntl_df <- bind_cols(unit_df, ntl_df)
+
+        #### Cleanup dates
+        if(time_period == "annually"){
+
+          ntl_df$date <- ntl_df$date %>% as.numeric()
+
+        } else if(time_period == "monthly"){
+
+          ntl_df$date <- paste0(ntl_df$date, "-01") %>% 
+            str_replace_all("_", "-") %>%
+            ymd()
+
+        } else if(time_period == "daily"){
+
+          ntl_df$date <- ntl_df$date %>% 
+            str_replace_all("_", "-") %>%
+            ymd()
+
+        }
+
+        saveRDS(ntl_df, OUT_DIR)
+
+      }
+    }
+  }
+}
+
+# Append files -----------------------------------------------------------------
+for(unit in c("adm0", "adm1", "adm2", "adm3", "city")){
+  for(time_period in c("annually", "monthly", "daily")){
+
+    ntl_df <- file.path(ntl_dir, "aggregated_individual", unit, time_period) %>%
+      list.files(full.names = T) %>%
+      map_df(readRDS)
+
+    saveRDS(ntl_df, file.path(ntl_dir, "aggregated_appended", 
+                              paste0(unit, "_", time_period, ".Rds")))
+
+    write_dta(ntl_df, file.path(ntl_dir, "aggregated_appended", 
+                              paste0(unit, "_", time_period, ".dta")))
+
+  }
+}
+

notebooks/nighttime-lights/_main.R

@@ -8,13 +8,15 @@ data_dir <- file.path("/Users", "rmarty", "Library", "CloudStorage", "OneDrive-S
                       "Development Data Partnership - Niger Economic Monitor", "Data")
 
 boundaries_dir <- file.path(data_dir, "Boundaries")
-ntl_dir <- file.path(data_dir, "Nighttime Lights")
+ntl_dir  <- file.path(data_dir, "Nighttime Lights")
+city_dir <- file.path(data_dir, "Cities")
 
 # Packages ---------------------------------------------------------------------
 library(dplyr)
 library(lubridate)
 library(sf)
 library(ggplot2)
 library(leaflet)
+library(haven)
 library(terra)
-#library(blackmarbler)
+library(blackmarbler)