Prodes clouds final corrections

R/download.R

@@ -7,17 +7,12 @@ sidra_download <- function(sidra_code = NULL, year, geo_level = "municipality",
   code_micro <- NULL
 
   # Obs: Sometimes there are non-catched municipalieis - user should check on IBGE SIDRA
-  # f = geo %>% filter(!(code_muni %in% unique(dat_uf$`Município (Código)`)))
+  # f = geo %>% filter(!(code_muni %in% unique(dat_uf$`MunicC-pio (CC3digo)`)))
 
   # ----------------------------------------------------
 
   ## Download from Sidra IBGE
-
-  ## Include Progress Bar
-  ## Omit Warnings
-  ## We should include support for microregion/mesoregion
-
-  # ------------------------------------------------------
+----------------
 
   ##############################
   ## Setting Basic Parameters ##
@@ -28,6 +23,11 @@ sidra_download <- function(sidra_code = NULL, year, geo_level = "municipality",
   param$sidra_code <- sidra_code
   param$year <- year
   param$classific <- classific
+  ## Include Progress Bar
+  ## Omit Warnings
+  ## We should include support for microregion/mesoregion
+
+  # --------------------------------------
   param$category <- category
 
   if (geo_level == "country") {
@@ -418,7 +418,33 @@ external_download <- function(dataset = NULL, source = NULL, year = NULL,
       "&disableProjSubset=on&addLatLon=true&accept=netcdf"
     )
   }
-
+
+  if (source == "prodes") {
+  if (year == 2016){
+    path = "https://drive.google.com/file/d/1bMDRs5-EYLQu-GRj6NREh9ukk_72HqKz/view?usp=sharing"
+  }
+  if (year == 2017){
+    path = "https://drive.google.com/file/d/1YvV-zSmdxuItNgHexzR5feTVozCZoS2t/view?usp=sharing"
+  }
+  if (year == 2018){
+    path = "https://drive.google.com/file/d/1k0BLOsFPnkW2LQQqO62ppWb6hcSPKsGA/view?usp=sharing"
+  }
+  if (year == 2019){
+    path = "https://drive.google.com/file/d/1OWFShUSk4mcg2G5HH_2gUnfvZgtTyf6Y/view?usp=sharing"
+  }
+  if (year == 2020){
+    path = "https://drive.google.com/file/d/1OggXwTbOjLo6w8sqiPI9PAj8TG4BlwVp/view?usp=sharing"
+  }
+  if (year == 2021){
+    path = "https://drive.google.com/file/d/1GbhWEPxXh9M_MHvYdoet-9CLDeLVFyuU/view?usp=sharing"
+  }
+  if (year == 2022){
+    path = "https://drive.google.com/file/d/1Ga0iVlq-F-kiUPwjQjt6n0h8dlSGyvcS/view?usp=sharing"
+  }
+  if (year == 2023){
+    path = "https://drive.google.com/file/d/1fbyFxLsxGygeDBaa7IKZf59IolqUdlHx/view?usp=sharing"              
+  }
+}
   #######################
   ## Initiate Download ##
   #######################
@@ -441,7 +467,11 @@ external_download <- function(dataset = NULL, source = NULL, year = NULL,
     file_extension <- ".xlsx"
   }
   if (source == "prodes") {
-    file_extension <- ".txt"
+    if (dataset == "deforestation") {
+      file_extension <- ".txt"
+    }else{
+      file_extension <- ".rds"
+    }
   }
   if (source == "terraclimate") {
     file_extension <- ".nc"
@@ -480,7 +510,8 @@ external_download <- function(dataset = NULL, source = NULL, year = NULL,
 
   dir <- tempdir()
   temp <- tempfile(fileext = file_extension, tmpdir = dir)
-
+
+
   ## Picking the way to download the file
 
   download_method <- "standard" # works for most functions
@@ -502,6 +533,12 @@ external_download <- function(dataset = NULL, source = NULL, year = NULL,
       download_method <- "googledrive"
     }
   }
+
+  if (source == "prodes") {
+    if (dataset == "cloud") {
+      download_method <- "googledrive"
+    }
+  }
   if (source %in% c("deter", "terraclimate", "baci", "sigmine", "mapbiomas")) {
     download_method <- "curl"
     quiet <- FALSE
@@ -520,6 +557,7 @@ external_download <- function(dataset = NULL, source = NULL, year = NULL,
       download_method <- "googledrive"
     }
   }
+
 
   ## Downloading file by the selected method
 
@@ -689,7 +727,8 @@ datasets_link <- function(source = NULL, dataset = NULL, url = FALSE) {
     ## PRODES
 
     "prodes", "deforestation", NA, "2000-2022", "Municipality", "http://www.dpi.inpe.br/prodesdigital/tabelatxt.php?ano=2022&estado=&ordem=MUNICIPIO&type=tabela&output=txt&",
-
+    "prodes", "cloud", NA, NA, "Municipality", "https://drive.google.com/uc?export=download&id=1bMDRs5-EYLQu-GRj6NREh9ukk_72HqKz",
+
     ## DETER
 
     "deter", "deter_amz", NA, "2016-2022", "Municipality", "http://terrabrasilis.dpi.inpe.br/file-delivery/download/deter-amz/shape",
@@ -969,4 +1008,4 @@ datasets_link <- function(source = NULL, dataset = NULL, url = FALSE) {
   }
 
   return(link)
-}
+}

R/prodes.R

@@ -2,7 +2,7 @@
 #'
 #' @description Loads data on deforestation in the Legal Amazon region.
 #'
-#' @param dataset A dataset name ("deforestation").
+#' @param dataset A dataset name ("deforestation", "cloud").
 #' @inheritParams load_baci
 #'
 #' @return A \code{tibble} with the selected data.
@@ -19,108 +19,115 @@
 #'
 #' @export
 
-load_prodes <- function(dataset, raw_data = FALSE,
+load_prodes <- function(dataset, year, raw_data = FALSE,
                         language = "eng") {
   ###########################
   ## Bind Global Variables ##
   ###########################
-
-  year <- municipio <- cod_ibge <- estado <- area_km2 <- increment <- NULL
+  
+  municipio <- cod_ibge <- estado <- area_km2 <- increment <- NULL
   municipality <- municipality_code <- state <- deforestation <- desmatamento2000 <- NULL
-
+  
   #############################
   ## Define Basic Parameters ##
   #############################
-
+  
   param <- list()
   param$source <- "prodes"
   param$dataset <- dataset
   param$raw_data <- raw_data
   param$language <- language
-
+  param$year <- year
+
   # check if dataset and time_period are supported
-
+  
   check_params(param)
-
+  
   ###################
   ## Download Data ##
   ###################
 
   ## Column Names come with numbers at the side - we need to clean those
-
+  
   dat <- external_download(
     dataset = param$dataset,
-    source = param$source
+    source = param$source,
+    year = param$year
   )
-
+  
   ## Return Raw Data
-
+  
   if (param$raw_data) {
     return(dat)
   }
-
+  
   ######################
   ## Data Engineering ##
   ######################
-
-  # keep only deforestation-related variables
-
-  dat <- dat %>%
-    janitor::clean_names() %>%
-    dplyr::select(
-      municipio, cod_ibge, estado, area_km2, desmatamento2000, dplyr::starts_with("incremento")
-    )
-
-  # change to long format with increment variable
-
-  dat <- dat %>%
-    dplyr::rename("incremento2000" = "desmatamento2000") %>%
-    tidyr::pivot_longer(
-      dplyr::starts_with("incremento"),
-      names_prefix = "incremento",
-      names_to = "year",
-      values_to = "increment"
-    )
-
-  # calculating cumulative deforestation
-
-  dat <- dat %>%
-    dplyr::arrange(municipio, year) %>%
-    dplyr::mutate(
-      deforestation = cumsum(increment),
-      .by = municipio
-    )
-
-  dat <- dat %>%
-    dplyr::mutate(
-      increment = dplyr::case_when(
-        year == 2000 ~ NA,
-        .default = increment
+
+  # keep only deforestation-related variables if the dataset is "deforestation"
+
+  if (dataset == "deforestation") {
+    required_columns <- c("municipio", "cod_ibge", "estado", "area_km2", "desmatamento2000")
+
+    # Check if the required columns are present
+    missing_columns <- setdiff(required_columns, colnames(dat))
+    if (length(missing_columns) > 0) {
+      stop(paste("The following required columns are missing in the dataset:", paste(missing_columns, collapse = ", ")))
+    }
+
+    dat <- dat %>%
+      janitor::clean_names() %>%
+      dplyr::select(
+        municipio, cod_ibge, estado, area_km2, desmatamento2000, dplyr::starts_with("incremento")
       )
-    )
-
+
+    # change to long format with increment variable
+    dat <- dat %>%
+      dplyr::rename("incremento2000" = "desmatamento2000") %>%
+      tidyr::pivot_longer(
+        dplyr::starts_with("incremento"),
+        names_prefix = "incremento",
+        names_to = "year",
+        values_to = "increment"
+      )
+
+    # calculating cumulative deforestation
+    dat <- dat %>%
+      dplyr::arrange(municipio, year) %>%
+      dplyr::mutate(
+        deforestation = cumsum(increment),
+        .by = municipio
+      ) %>%
+      dplyr::mutate(
+        increment = dplyr::case_when(
+          year == 2000 ~ NA,
+          .default = increment
+        )
+      )
+  }
+
   ################################
   ## Harmonizing Variable Names ##
   ################################
-
+  
   if (param$language == "eng") {
     dat_mod <- dat %>%
       dplyr::rename(
         "municipality" = municipio,
         "municipality_code" = cod_ibge,
         "state" = estado
       )
-  }
-  if (param$language == "pt") {
+  } else if (param$language == "pt") {
     dat_mod <- dat %>%
       dplyr::rename(
         "ano" = year,
-        "cod_municipio" = "cod_ibge",
+        "cod_municipio" = cod_ibge,
         "uf" = estado,
         "incremento" = increment,
         "desmatamento" = deforestation
       )
   }
-
+  
   return(dat_mod)
 }