georeference ifn3

Author: Cidree

NEWS.md

@@ -48,7 +48,7 @@
 
     -   It was returning metadata with the same name always. Now it will be different depending on the dataset that we download, and it will be checked if it exists before downloading it (according to #3).
 
-    -   Some provinces in IFN4 were incorrectly georreferenced. Now they are correctly georreferenced based on the *Documentador.*
+    -   Some provinces in IFN4 were incorrectly georreferenced. Now they are correctly georreferenced based on the *Documentador.* IFN3 provinces are now also georreferenced
 
 -   `fd_landcover_copernicus()` and `fd_canopy_height()` now crop data regardless of the CRS.
 

R/forest-inventory.R

@@ -285,7 +285,7 @@ fd_inventory_spain <- function(province,
     if (!file.exists(metadata_file$filename)) {
       download.file(
         metadata_file$url,
-        destfile = metadata_file$filename,
+        destfile = paste0(path_metadata, "/", metadata_file$filename),
         mode     = "wb",
         quiet    = quiet
       )
@@ -319,6 +319,7 @@ fd_inventory_spain <- function(province,
     filename <- list.files(dir_unzip, full.names = TRUE, pattern = "\\.accdb$")
     ## 4.2. Connect to DB
     conn <- RODBC::odbcConnectAccess2007(filename)
+    on.exit(RODBC::odbcClose(conn))
     ## 4.3. Table names
     tables_vec <- RODBC::sqlTables(conn) |>
       dplyr::filter(TABLE_TYPE != "SYSTEM TABLE") |>
@@ -337,21 +338,67 @@ fd_inventory_spain <- function(province,
       if (ifn == 4) {
         ## get datum code based on province/ccaa
         datum <- dplyr::case_when(
-          province %in% c("Navarra", "Lugo", "A Coruna", "Lugo", "Pontevedra",
+          province_fix %in% c("Navarra", "Lugo", "A Coruna", "Lugo", "Pontevedra",
                           "Ourense", "Asturias", "Cantabria", "Murcia", "Baleares",
                           "Pais Vasco", "La Rioja", "Madrid", "Cataluna") ~ 230,
-          province %in% c("Canarias") ~ 326,
+          province_fix %in% c("Canarias") ~ 326,
           .default = 258
         )
+        ## convert to spatial
+        data_lst$PCDatosMap_sf <- sf::st_as_sf(
+          x      = data_lst$PCDatosMap,
+          coords = c("CoorX", "CoorY"),
+          crs    = paste0("EPSG:", datum, data_lst$PCDatosMap$Huso)
+        )
+
+        ## IFN 3 - SF column
       } else {
-        datum <- 230
+        data_lst$PCDatosMap <- data_lst$PCDatosMap |>
+          dplyr::mutate(
+            Huso = dplyr::case_when(
+              ## Huso 29
+              province_fix %in% c("Lugo", "Ourense", "A Coruna", "Pontevedra") ~ 29,
+              province_fix %in% c("Sevilla", "Badajoz", "Caceres", "Salamanca", "Cadiz",
+                                  "Zamora", "Leon", "Asturias", "Huelva") & CoorX > 5e5 ~ 29,
+              ## Huso 28
+              province_fix %in% c("Santa Cruz De Tenerife", "Las Palmas") ~ 28,
+              ## Huso 31
+              province_fix %in% c("Islas Baleares", "Barcelona", "Girona", "Lleida", "Tarragona") ~ 31,
+              province_fix %in% c("Castellon", "Huesca", "Zaragoza",
+                                  "Teruel", "Alicante") & CoorX < 5e5 ~ 31,
+              .default = 30
+            )
+          )
+        ## convert to spatial
+        ## some provinces have 2 different CRS (they use topographic map sheets)
+        husos <- unique(data_lst$PCDatosMap$Huso)
+        if (length(husos) > 1) {
+          ## they are always 2 different CRS
+          data_huso_1 <- sf::st_as_sf(
+            x      = data_lst$PCDatosMap[data_lst$PCDatosMap$Huso == husos[1], ],
+            coords = c("CoorX", "CoorY"),
+            crs    = paste0("EPSG:230", husos[1])
+          )
+
+          data_huso_2 <- sf::st_as_sf(
+            x      = data_lst$PCDatosMap[data_lst$PCDatosMap$Huso == husos[2], ],
+            coords = c("CoorX", "CoorY"),
+            crs    = paste0("EPSG:230", husos[2])
+          ) |> sf::st_transform(paste0("EPSG:230", husos[1]))
+
+          data_lst$PCDatosMap_sf <- rbind(data_huso_1, data_huso_2)
+
+        } else {
+          ## for only 1 CRS
+          data_lst$PCDatosMap_sf <- sf::st_as_sf(
+            x      = data_lst$PCDatosMap,
+            coords = c("CoorX", "CoorY"),
+            crs    = paste0("EPSG:", datum, data_lst$PCDatosMap$Huso[1])
+          )
+        }
+
       }
-      ## convert to spatial
-      data_lst$PCDatosMap_sf <- sf::st_as_sf(
-        x      = data_lst$PCDatosMap,
-        coords = c("CoorX", "CoorY"),
-        crs    = paste0("EPSG:", datum, data_lst$PCDatosMap$Huso[1])
-      )
+
     }
     ## 4.7. Return results
     return(data_lst)