diff --git a/R/get_glw_data.R b/R/get_glw_data.R
new file mode 100644
index 0000000..1098827
--- /dev/null
+++ b/R/get_glw_data.R
@@ -0,0 +1,33 @@
+#' .. content for \description{} (no empty lines) ..
+#'
+#' .. content for \details{} ..
+#'
+#' @title
+#' @param 
+#' @return
+#' @author Whitney Bagge
+#' @export
+#' 
+get_glw_data <- function(glw_directory_raw) {
+  
+  options(timeout=200)
+  
+  location <- c("url_cattle", "url_sheep", "url_goats")
+  
+  for(loc in location) { 
+    
+    url_out<- switch(loc,  "url_cattle" = "https://dataverse.harvard.edu/api/access/datafile/6769710", 
+                           "url_sheep" = "https://dataverse.harvard.edu/api/access/datafile/6769629",
+                           "url_goats" = "https://dataverse.harvard.edu/api/access/datafile/6769692")
+    
+    filename <- paste("data/glw/", loc, sep="", ".tif")
+    
+    download.file(url=url_out, destfile = filename)
+  
+  }
+
+  return(glw_directory_raw)
+
+  
+  
+}
diff --git a/R/preprocess_glw_data.R b/R/preprocess_glw_data.R
new file mode 100644
index 0000000..d2d0f08
--- /dev/null
+++ b/R/preprocess_glw_data.R
@@ -0,0 +1,38 @@
+#' .. content for \description{} (no empty lines) ..
+#'
+#' .. content for \details{} ..
+#'
+#' @title
+#' @param bounding_boxes
+#' @return
+#' @author Whitney Bagge
+#' @export
+#' 
+library(raster)
+library(terra)
+preprocess_glw_data<- function(glw_directory_raw, glw_downloaded, continent_raster_template) {
+  
+  transformed_raster_cat <- transform_raster(raw_raster = rast(paste0(glw_downloaded, "/url_cattle.tif")),
+                                         template = rast(continent_raster_template))
+  transformed_raster_sh <- transform_raster(raw_raster = rast(paste0(glw_downloaded, "/url_sheep.tif")),
+                                         template = rast(continent_raster_template))
+  transformed_raster_go <- transform_raster(raw_raster = rast(paste0(glw_downloaded, "/url_goats.tif")),
+                                         template = rast(continent_raster_template))
+  
+  # Convert to dataframe
+  dat_out_cat<- as.data.frame(transformed_raster_cat, xy = TRUE) |> 
+    as_tibble() 
+  dat_out_sh<- as.data.frame(transformed_raster_sh, xy = TRUE) |> 
+    as_tibble() 
+  dat_out_go<- as.data.frame(transformed_raster_go, xy = TRUE) |> 
+    as_tibble() 
+  
+  # Save as parquet 
+  write_parquet(dat_out_cat,  "data/glw/glw_cattle", compression = "gzip", compression_level = 5)
+  write_parquet(dat_out_sh, "data/glw/glw_sheep", compression = "gzip", compression_level = 5)
+  write_parquet(dat_out_go, "data/glw/glw_goats", compression = "gzip", compression_level = 5)
+  
+  
+  return(glw_directory_raw)
+  
+}
diff --git a/R/preprocess_soil.R b/R/preprocess_soil.R
new file mode 100644
index 0000000..d36c994
--- /dev/null
+++ b/R/preprocess_soil.R
@@ -0,0 +1,138 @@
+#' .. content for \description{} (no empty lines) ..
+#'
+#' .. content for \details{} ..
+#'
+#' @title
+#' @param continent_polygon
+#' @return
+#' @author Whitney Bagge
+#' @export
+library(DBI)
+library(RSQLite)
+preprocess_soil <- function(soil_downloaded, continent_raster_template, soil_directory_raw) {
+
+    #read in the raster file
+
+  #crop the raster to the continent
+  #hwsd_bounded <- terra::crop(unzipped_soil_raster, terra::unwrap(continent_raster_template))
+  
+  #reproject the raster
+    #print(paste("UTM zone:", utm.zone <-
+    #            floor(((sf::st_bbox(hwsd_bounded)$xmin +
+    #                      sf::st_bbox(hwsd_bounded)$xmax)/2 + 180)/6)
+    #          + 1))
+  
+  #(epsg <- 32600 + utm.zone)
+  
+  #hwsd_bounded.utm <- project(hwsd_bounded, paste0("EPSG:", epsg), method = "near")
+  
+  #terra::resample(hwsd_bounded.utm, method = "near")
+  
+  transformed_raster <- transform_raster(raw_raster = rast(paste0(soil_downloaded, "/HWSD2.bil")),
+                                         template = rast(continent_raster_template))
+  
+  #connect to database and extract values
+  m <- dbDriver("SQLite")
+  con <- dbConnect(m, dbname="data/soil/soil_database.sqlite")
+  dbListTables(con)
+  
+  ####extract map unit codes in bounded area (WINDOW_ZHNJ) to join with SQL databases###
+  dbWriteTable(con, name="WINDOW_ZHNJ",
+               value=data.frame(hwsd2_smu = sort(unique(values(transformed_raster)))),
+               overwrite=TRUE)
+  
+  dbExecute(con, "drop table if exists ZHNJ_SMU") # to overwrite
+  
+  dbListTables(con)
+  
+  #creates a temp database that combines the map unit codes in the raster window to the desired variable
+  dbExecute(con,
+            "create TABLE ZHNJ_SMU AS select T.* from HWSD2_SMU as T
+              join WINDOW_ZHNJ as U
+              on T.HWSD2_SMU_ID=U.HWSD2_SMU
+              order by HWSD2_SMU_ID")
+  
+  #creates a dataframe "records" in R from SQL temp table created above
+  records <- dbGetQuery(con, "select * from ZHNJ_SMU")
+  
+  #create sand and clay tables in R
+  #sand.d1 <- dbGetQuery(con,
+  #                      "select U.HWSD2_SMU_ID, U.SAND from ZHNJ_SMU as T
+  #                      join HWSD2_LAYERS as U on T.HWSD2_SMU_ID=U.HWSD2_SMU_ID
+  #                      where U.LAYER='D1'
+  #                      order by U.HWSD2_SMU_ID")
+  #
+  #clay.d1 <- dbGetQuery(con,
+  #                      "select U.HWSD2_SMU_ID, U.CLAY from ZHNJ_SMU as T
+  #                      join HWSD2_LAYERS as U on T.HWSD2_SMU_ID=U.HWSD2_SMU_ID
+  #                      where U.LAYER='D1'
+  #                      order by U.HWSD2_SMU_ID")
+  
+  #remove the temp tables and database connection
+  dbRemoveTable(con, "WINDOW_ZHNJ")
+  dbRemoveTable(con, "ZHNJ_SMU")
+  dbDisconnect(con)
+  
+  #join sand and clay data frames in r to create a ratio variable
+  #full_join (sand.d1, clay.d1)
+  
+  #changes from character to factor for the raster
+  for (i in names(records)[c(2:5,7:13,16:17,19:23)])
+  {
+    eval(parse(text=paste0("records$",i," <- as.factor(records$",i,")")))
+  }
+
+  #create matrix of map unit ids and the variable of interest - TEXTURE CLASS
+  rcl.matrix.texture <- cbind(id = as.numeric(as.character(records$HWSD2_SMU_ID)),
+                      texture = as.numeric(records$TEXTURE_USDA))
+  
+  #classify the raster (transformed_raster) using the matrix of values - TEXTURE CLASS
+  hwsd.zhnj.texture <- classify(transformed_raster, rcl.matrix.texture)
+  hwsd.zhnj.texture <- as.factor(hwsd.zhnj.texture)
+  levels(hwsd.zhnj.texture) <- levels(records$TEXTURE_USDA)
+  
+  # Convert to dataframe
+  dat_out <- as.data.frame(hwsd.zhnj.texture, xy = TRUE) |> 
+    as_tibble() 
+  
+  dat_out$HWSD2 <- if_else(dat_out$HWSD2=="5", "1",
+                   if_else(dat_out$HWSD2=="7", "2",
+                   if_else(dat_out$HWSD2=="8", "3",
+                   if_else(dat_out$HWSD2=="9", "4",
+                   if_else(dat_out$HWSD2=="10", "5",
+                   if_else(dat_out$HWSD2=="11", "6",
+                   if_else(dat_out$HWSD2=="12", "7","0")))))))
+                                           
+
+  #create matrix of map unit ids and the variable of interest - DRAINAGE
+  rcl.matrix.drainage <- cbind(id = as.numeric(as.character(records$HWSD2_SMU_ID)),
+                      drainage = as.numeric(records$DRAINAGE))
+  
+  #classify the raster (transformed_raster) using the matrix of values - DRAINAGE
+  hwsd.zhnj.drainage <- classify(transformed_raster, rcl.matrix.drainage)
+  hwsd.zhnj.drainage <- as.factor(hwsd.zhnj.drainage)
+  levels(hwsd.zhnj.drainage) <- levels(records$DRAINAGE)
+  
+  # Convert to dataframe
+  dat_out2 <- as.data.frame(hwsd.zhnj.drainage, xy = TRUE) |> 
+    as_tibble() 
+  
+  dat_out2$HWSD2 <- if_else(dat_out2$HWSD2=="MW", "4",
+              if_else(dat_out2$HWSD2=="P", "6",
+              if_else(dat_out2$HWSD2=="SE", "2",
+              if_else(dat_out2$HWSD2=="VP", "7","0"))))
+  
+  dat_out2$HWSD2 <- as.numeric(as.character(dat_out2$HWSD2))
+  
+  # Save as parquet 
+  write_parquet(dat_out,  "data/soil/soil_texture", compression = "gzip", compression_level = 5)
+  write_parquet(dat_out2, "data/soil/soil_drainage", compression = "gzip", compression_level = 5)
+  
+  #writeRaster(hwsd.zhnj.drainage, "data/soil/drainage_raster.tif", overwrite=TRUE)
+  #writeRaster(hwsd.zhnj.texture, "data/soil/texture_class_raster.tif", overwrite=TRUE)
+  #writeRaster(x, sand_clay_raster, overwrite=TRUE)
+  
+  
+  return("/data/soil")
+  
+}
diff --git a/R/soil_download.R b/R/soil_download.R
index 44bcb05..38e577b 100644
--- a/R/soil_download.R
+++ b/R/soil_download.R
@@ -7,29 +7,30 @@
 #' @return
 #' @author Whitney Bagge
 #' @export
-soil_download <- function() {
+soil_download <- function(soil_directory_raw) {
   
   options(timeout=200)
   
-  loc <- c("soil_database", "soil_raster")
-  for(loc in location) { 
+  location <- c("soil_database", "soil_raster")
+  
+  for(loc in location){ 
     
-    url_out<- switch(loc,  "soil_raster" = "https://s3.eu-west-1.amazonaws.com/data.gaezdev.aws.fao.org/HWSD/HWSD2_RASTER.zip", 
-                           "soil_database" = "https://www.isric.org/sites/default/files/HWSD2.sqlite")
+   url_out<- switch(loc,  "soil_raster" = "https://s3.eu-west-1.amazonaws.com/data.gaezdev.aws.fao.org/HWSD/HWSD2_RASTER.zip", 
+                          "soil_database" = "https://www.isric.org/sites/default/files/HWSD2.sqlite")
 
-    file_ext<- switch(loc,"soil_raster" = ".zip", "soil_database" = ".sqlite")
-    
-    file_name <- paste("data/soil/", loc, file_ext, sep="")
-    
-    download.file(url=url_out, destfile = file_name)
-    
-    if (loc == "soil_raster" ){
-     unzip(file_name, exdir = "data/soil/")
-    }
+   file_ext<- switch(loc,"soil_raster" = ".zip", "soil_database" = ".sqlite")
+   
+   filename <- paste("data/soil/", loc, file_ext, sep="")
+   
+   download.file(url=url_out, destfile = filename)
+   
+   if (loc == "soil_raster" ){
+    unzip(filename, exdir = "data/soil/")
+   }
 
   }
   
-  return(file.path(download_directory, filename))
+  return(soil_directory_raw)
   
 
 }
diff --git a/_targets.R b/_targets.R
index f5dd248..b6aae0b 100644
--- a/_targets.R
+++ b/_targets.R
@@ -38,12 +38,47 @@ static_targets <- tar_plan(
   tar_target(continent_bounding_box, sf::st_bbox(continent_polygon)),
   tar_target(continent_raster_template,
              wrap(terra::rast(ext(continent_polygon), 
-                              resolution = 0.5))), #TODO change to 0.1 (might cause error in transform, leaving at 0.5 for now)
+                              resolution = 0.1))), #TODO change to 0.1 (might cause error in transform, leaving at 0.5 for now)
   # nasa power resolution = 0.5; enmwf = ; ndvi = 
   # tar_target(continent_raster_template_plot, create_raster_template_plot(rast(continent_raster_template), continent_polygon))
-  
-)
 
+  # SOIL -----------------------------------------------------------
+  tar_target(soil_directory_raw, 
+             create_data_directory(directory_path = "data/soil")),
+  tar_target(soil_downloaded, soil_download(soil_directory_raw),
+             format = "file", 
+             repository = "local"),
+  tar_target(soil_preprocessed, 
+             preprocess_soil(soil_downloaded, continent_raster_template)),
+  
+  # SLOPE and ASPECT -------------------------------------------------
+  tar_target(slope_aspect_directory_raw, 
+             create_data_directory(directory_path = "data/slope_aspect")),
+  tar_target(slope_aspect_downloaded, get_slope_aspect(slope_aspect_directory_raw, continent_polygon),
+    format = "file", 
+    repository = "local"),
+ 
+   # Gridded Livestock of the world -----------------------------------------------------------
+  tar_target(glw_directory_raw, 
+             create_data_directory(directory_path = "data/glw")),
+  tar_target(glw_downloaded, get_glw_data(glw_directory_raw),
+             format = "file", 
+             repository = "local"),
+  tar_target(glw_preprocessed, 
+             preprocess_glw_data(glw_directory_raw, glw_downloaded, continent_raster_template)),
+
+
+# ELEVATION -----------------------------------------------------------
+tar_target(elevation_directory_raw, 
+           create_data_directory(directory_path = "data/elevation")),
+tar_target(elevation_downloaded, get_elevation(elevation_directory_raw),
+  format = "file", 
+  repository = "local"),
+tar_target(elevation_preprocessed, 
+           process_elevation(elevation_directory_raw, elevation_downloaded, continent_raster_template)),
+
+
+)
 # Dynamic Data Download -----------------------------------------------------------
 dynamic_targets <- tar_plan(
   
@@ -52,6 +87,7 @@ dynamic_targets <- tar_plan(
   tar_target(wahis_rvf_outbreaks_preprocessed, 
              preprocess_wahis_rvf_outbreaks(wahis_rvf_outbreaks_raw)),
   
+  
   # SENTINEL NDVI -----------------------------------------------------------
   # 2018-present
   
@@ -239,27 +275,7 @@ dynamic_targets <- tar_plan(
   format = "file"
   ),
   
-  ## GLW
-
-  tar_target(glw_cattle, get_glw()),
-  tar_target(glw_sheep, get_glw()),
-  tar_target(glw_goats, get_glw()),
-  tar_target(glw_cattle_preprocessed, preprocess_glw(glw_cattle, bounding_boxes)),
-  #need to cache
-  
-  ## ELEVATION
-  
-  tar_target(elevation_layer_raw, get_elevation()),
-  tar_target(elevation_layer_processed, 
-             process_elevation(elevation_layer_processed, bounding_boxes)),
-  #need to cache
-  
-  ## GRAZING CAPACITY
   
-  tar_target(grazingcap_raw, get_grazingcap()),
-  tar_target(grazingcap_processed, 
-             process_grazingcap(grazingcap_layer_processed, bounding_boxes)),
-  #need to cache
 
 )