database/db_creation.R
In ptaconet/malamodpkg: R scripts - modeling the risk of residual malaria transmission at a micro-scale
require(RSQLite)
require(dplyr)
require(sf)
require(rgdal)
require(gdalUtils)
require(raster)
require(gdalUtils)
require(readxl)
require(lubridate)
require(stringr)
require(purrr)
require(tidyverse)
require(googlesheets4)
setwd("/home/ptaconet/react/datasets/")
path_to_amal_database<-"miscellaneous_data/React_dbase_V7.db"
path_to_gpkg_database<-"react_db.gpkg" # Empty gpkg template is available here : http://www.geopackage.org/data/empty.gpkg
path_to_gpkg_light_database<-"react_db_light.gpkg"
path_to_metadata_table<-"https://docs.google.com/spreadsheets/d/1O7JUhoAzXtoFWjiLOz7HgDLe--zxkZKR96_BhzU7DME/edit?usp=sharing"
download.file("http://www.geopackage.org/data/empty.gpkg",path_to_gpkg_database)
file.copy(path_to_gpkg_database,path_to_gpkg_light_database,overwrite =T)
## Connect to DBs
amal_db <- dbConnect(RSQLite::SQLite(),path_to_amal_database)
react_gpkg <- dbConnect(RSQLite::SQLite(),path_to_gpkg_database)
react_gpkg_light <- dbConnect(RSQLite::SQLite(),path_to_gpkg_light_database)
## Open and load tables metadata and metadata_mapping
metadata_tables<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "metadata_tables",col_types="c")
metadata_contacts<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "contacts",col_types="c")
metadata_mapping<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "metadata_mapping",col_types="c")
metadata_data_dictionary_table<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "data_dictionary_columns",col_types="c")
dbWriteTable(react_gpkg,"metadata_tables",metadata_tables,overwrite=TRUE)
dbWriteTable(react_gpkg,"metadata_contacts",metadata_contacts,overwrite=TRUE)
dbWriteTable(react_gpkg,"metadata_mapping",metadata_mapping,overwrite=TRUE)
dbWriteTable(react_gpkg,"metadata_data_dictionary_table",metadata_data_dictionary_table,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_tables",metadata_tables %>% filter(identifier %in% c(
"recensement_individus_l0",
"recensement_menages_l0",
"recensement_villages_l1",
"entomo_comportementhumain_l0",
"entomo_csh_ctrlequalite_l0",
"entomo_csh_metadata_l0",
"entomo_csh_metadata_l1",
"entomo_idmoustiques_l0",
"entomo_hobo_l0",
"entomo_hygro_l0",
"entomo_baro_l0",
"epidemio_active_bf_l0",
"epidemio_active_ci_l0",
"epidemio_active_l1",
"epidemio_passive_l0",
"epidemio_goutteepaisse_l1",
"interv_ivm_bf_recenses_l0",
"interv_ivm_bf_traites_l0",
"interv_irs_bf_ctrlequalite_chimique_l0",
"interv_irs_ci_ctrlequalite_chimique_l0",
"interv_larvicide_ci_ctrlequalite_l0",
"interv_irs_ctrlequalite_cone_l0",
"interv_iec_bf_ctrlequalite_l0",
"interv_iec_ci_ctrlequalite_l0",
"contexte_paysafriqueouest",
"contexte_villesafriqueouest",
"contexte_frontieresreact",
"metadata_tables",
"metadata_contacts",
"metadata_mapping",
"metadata_data_dictionary_table")),overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_contacts",metadata_contacts,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_mapping",metadata_mapping,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_data_dictionary_table",metadata_data_dictionary_table,overwrite=TRUE)
## Create and load tables :
# initiate data dictionary
data_dictionnary <- data.frame(name=character(),table=character(),label=character(),type=character(),description=character(),additional_information=character())
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_tables),table="metadata_tables"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_contacts),table="metadata_contacts"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_mapping),table="metadata_mapping"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_data_dictionary_table),table="metadata_data_dictionary_table"))
# recensement_individus_l0
source("/home/ptaconet/malamodpkg/database/recensement_individus_l0.R") # source("https://raw.githubusercontent.com/ptaconet/malamodpkg/master/database/recensement_individus_l0.R")
individus <- cbind(fid = 1:nrow(individus), individus)
dbWriteTable(react_gpkg,"recensement_individus_l0",individus,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"recensement_individus_l0",individus,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(individus),table="recensement_individus_l0"))
# recensement_menages_l0
#source("/home/ptaconet/malamodpkg/database/raw_menages.R")
source("/home/ptaconet/malamodpkg/database/recensement_menages_l0.R")
menages_sf<-st_as_sf(menages,coords = c("coordgpsLongitude", "coordgpsLatitude"), crs = 4326 )
menages_sf<-cbind(menages_sf,st_coordinates(menages_sf))
st_write(menages_sf, path_to_gpkg_database, "recensement_menages_l0", delete_layer = TRUE)
st_write(menages_sf, path_to_gpkg_light_database, "recensement_menages_l0", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(menages_sf),table="recensement_menages_l0"))
# recensement_villages_l1
source("/home/ptaconet/malamodpkg/database/recensement_villages_l1.R")
villages_sf<-st_as_sf(villages,coords = c("X", "Y"), crs = 4326 )
villages_sf<-cbind(villages_sf,st_coordinates(villages_sf))
st_write(villages_sf, path_to_gpkg_database, "recensement_villages_l1", delete_layer = TRUE)
st_write(villages_sf, path_to_gpkg_light_database, "recensement_villages_l1", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(villages_sf),table="recensement_villages_l1"))
# entomo_comportementhumain_l0
source("/home/ptaconet/malamodpkg/database/entomo_comportementhumain_l0.R")
df_humanbehavior_sf<-st_as_sf(df_humanbehavior,coords = c("longitude", "latitude"), crs = 4326 )
df_humanbehavior_sf <- cbind(fid = 1:nrow(df_humanbehavior_sf), df_humanbehavior_sf)
st_write(df_humanbehavior_sf, path_to_gpkg_database, "entomo_comportementhumain_l0", delete_layer = TRUE)
st_write(df_humanbehavior_sf, path_to_gpkg_light_database, "entomo_comportementhumain_l0", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_humanbehavior_sf),table="entomo_comportementhumain_l0"))
# entomo_csh_ctrlequalite_l0
source("/home/ptaconet/malamodpkg/database/entomo_csh_ctrlequalite_l0.R") # créé le data.frame nommé "all_data" contenant les données brutes de supervision capture
supervcapture_sf<-st_as_sf(all_data,coords = c("longitude", "latitude"), crs = 4326 )
supervcapture_sf<-cbind(supervcapture_sf,st_coordinates(supervcapture_sf))
st_write(supervcapture_sf, path_to_gpkg_database, "entomo_csh_ctrlequalite_l0", delete_layer = TRUE)
st_write(supervcapture_sf, path_to_gpkg_light_database, "entomo_csh_ctrlequalite_l0", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(supervcapture_sf),table="entomo_csh_ctrlequalite_l0"))
# entomo_csh_metadata_l0
source("/home/ptaconet/malamodpkg/database/entomo_csh_metadata_l0.R")
raw_dates_hlc <- cbind(fid = 1:nrow(raw_dates_hlc), raw_dates_hlc)
dbWriteTable(react_gpkg,"entomo_csh_metadata_l0",raw_dates_hlc,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_csh_metadata_l0",raw_dates_hlc,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(raw_dates_hlc),table="entomo_csh_metadata_l0"))
# entomo_csh_metadata_l1
source("/home/ptaconet/malamodpkg/database/entomo_csh_metadata_l1.R")
hlc_dates_loc_times_sf<-st_as_sf(hlc_dates_loc_times,coords = c("longitude", "latitude"), crs = 4326 )
hlc_dates_loc_times_sf<-cbind(hlc_dates_loc_times_sf,st_coordinates(hlc_dates_loc_times_sf))
st_write(hlc_dates_loc_times_sf, path_to_gpkg_database, "entomo_csh_metadata_l1", delete_layer = TRUE) # use delete_layer=TRUE to delete first
st_write(hlc_dates_loc_times_sf, path_to_gpkg_light_database, "entomo_csh_metadata_l1", delete_layer = TRUE) # use delete_layer=TRUE to delete first
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(hlc_dates_loc_times_sf),table="entomo_csh_metadata_l1"))
# entomo_idmoustiques_l0
source("/home/ptaconet/malamodpkg/database/entomo_idmoustiques_l0.R")
entomo <- cbind(fid = 1:nrow(df_mosquitoes), df_mosquitoes)
dbWriteTable(react_gpkg,"entomo_idmoustiques_l0",entomo,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_idmoustiques_l0",entomo,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(entomo),table="entomo_idmoustiques_l0"))
# Entomo - micro-climate from sensors
source("/home/ptaconet/malamodpkg/database/entomo_env_sensors.R")
df_hobo <- cbind(fid = 1:nrow(df_hobo), df_hobo)
df_hygro <- cbind(fid = 1:nrow(df_hygro), df_hygro)
df_baro <- cbind(fid = 1:nrow(df_baro), df_baro)
dbWriteTable(react_gpkg,"entomo_hobo_l0",df_hobo,overwrite=TRUE)
dbWriteTable(react_gpkg,"entomo_hygro_l0",df_hygro,overwrite=TRUE)
dbWriteTable(react_gpkg,"entomo_baro_l0",df_baro,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_hobo_l0",df_hobo,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_hygro_l0",df_hygro,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_baro_l0",df_baro,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_hobo),table="entomo_hobo_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_hygro),table="entomo_hygro_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_baro),table="entomo_baro_l0"))
# epidemio_xxx (toutes les tables épidémio)
source("/home/ptaconet/malamodpkg/database/epidemio.R")
act <- cbind(fid = 1:nrow(act), act)
BF_act <- cbind(fid = 1:nrow(BF_act), BF_act)
CI_act <- cbind(fid = 1:nrow(CI_act), CI_act)
pas <- cbind(fid = 1:nrow(pas), pas)
GE_stats <- cbind(fid = 1:nrow(GE_stats), GE_stats)
dbWriteTable(react_gpkg,"epidemio_active_l1",act,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_active_bf_l0",BF_act,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_active_ci_l0",CI_act,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_passive_l0",pas,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_goutteepaisse_l1",GE_stats,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_active_l1",act,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_active_bf_l0",BF_act,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_active_ci_l0",CI_act,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_passive_l0",pas,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_goutteepaisse_l1",GE_stats,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(act),table="epidemio_active_l1"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(BF_act),table="epidemio_active_bf_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(CI_act),table="epidemio_active_ci_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(pas),table="epidemio_passive_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(GE_stats),table="epidemio_goutteepaisse_l1"))
# interv_ivm_l0
source("/home/ptaconet/malamodpkg/database/interv_ivm_l0.R")
interv_ivm_traites_l0 <- cbind(fid = 1:nrow(interv_ivm_traites_l0), interv_ivm_traites_l0)
interv_ivm_recenses_l0 <- cbind(fid = 1:nrow(interv_ivm_recenses_l0), interv_ivm_recenses_l0)
dbWriteTable(react_gpkg,"interv_ivm_bf_traites_l0",interv_ivm_traites_l0,overwrite=TRUE)
dbWriteTable(react_gpkg,"interv_ivm_bf_recenses_l0",interv_ivm_recenses_l0,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_ivm_bf_traites_l0",interv_ivm_traites_l0,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_ivm_bf_recenses_l0",interv_ivm_recenses_l0,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(interv_ivm_traites_l0),table="interv_ivm_bf_traites_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(interv_ivm_recenses_l0),table="interv_ivm_bf_recenses_l0"))
#interv_larvicide_ci_ctrlequalite_l0
source("/home/ptaconet/malamodpkg/database/interv_larvicide_ci_ctrlequalite_l0.R")
larvicide_ci_ctrlequalite <- cbind(fid = 1:nrow(larvicide_ci_ctrlequalite), larvicide_ci_ctrlequalite)
dbWriteTable(react_gpkg,"interv_larvicide_ci_ctrlequalite_l0",larvicide_ci_ctrlequalite,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_larvicide_ci_ctrlequalite_l0",larvicide_ci_ctrlequalite,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(larvicide_ci_ctrlequalite),table="interv_larvicide_ci_ctrlequalite_l0"))
#interv_irs_ctrlequalite_cone_l0
source("/home/ptaconet/malamodpkg/database/interv_irs_ctrlequalite_cone_l0.R")
interv_irs_ctrlequalite_cone_l0 <- cbind(fid = 1:nrow(interv_irs_ctrlequalite_cone_l0), interv_irs_ctrlequalite_cone_l0)
dbWriteTable(react_gpkg,"interv_irs_ctrlequalite_cone_l0",interv_irs_ctrlequalite_cone_l0,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_irs_ctrlequalite_cone_l0",interv_irs_ctrlequalite_cone_l0,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(interv_irs_ctrlequalite_cone_l0),table="interv_irs_ctrlequalite_cone_l0"))
# contexte_paysafriqueouest downloaded here : https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels
adm_bound_sf<-read_sf("/home/ptaconet/react/datasets/miscellaneous_data/wca_adm0/wca_adm0.shp")
adm_bound_sf<-st_transform(adm_bound_sf,crs=4326)
st_write(adm_bound_sf, path_to_gpkg_database, "contexte_paysafriqueouest", update = TRUE)
st_write(adm_bound_sf, path_to_gpkg_light_database, "contexte_paysafriqueouest", update = TRUE)
# contexte_villesafriqueouest
ancillary_africa_cities<-read_sf("/home/ptaconet/react/datasets/miscellaneous_data/africa_places/places.shp")
ancillary_africa_cities<-st_intersection(ancillary_africa_cities,adm_bound_sf)
st_write(ancillary_africa_cities, path_to_gpkg_database, "contexte_villesafriqueouest", update = TRUE)
st_write(ancillary_africa_cities, path_to_gpkg_light_database, "contexte_villesafriqueouest", update = TRUE)
# contexte_frontieresreact
roi_civ_sf<-read_sf("/home/ptaconet/react/datasets/data_CIV/ROI.kml")
roi_civ_sf$codepays<-"CI"
roi_civ_sf<-roi_civ_sf[,"codepays"]
roi_civ_sf<-st_cast(roi_civ_sf,"POLYGON")
roi_bf_sf<-read_sf("/home/ptaconet/react/datasets/data_BF/ROI.kml")
roi_bf_sf$codepays<-"BF"
roi_bf_sf<-roi_bf_sf[,"codepays"]
roi_bf_sf<-st_zm(roi_bf_sf,drop = TRUE, what = "ZM")
roi<-rbind(roi_civ_sf,roi_bf_sf)
roi<-st_transform(roi,crs=32630)
st_write(roi, path_to_gpkg_database, "contexte_frontieresreact", update = TRUE)
st_write(roi, path_to_gpkg_light_database, "contexte_frontieresreact", update = TRUE)
# LU/LC training and validation parcels (raw and segmented)
ground_truth_data_civ_raw<-st_read("/home/ptaconet/react/datasets/data_CIV/Ground_truth/civ_groundtruth_vector_32630.gpkg")
ground_truth_data_civ_raw <- cbind(pk = 1:nrow(ground_truth_data_civ_raw), ground_truth_data_civ_raw)
st_write(ground_truth_data_civ_raw, path_to_gpkg_database, "lco_groundtruth_ci_l0", update = TRUE)
ground_truth_data_civ_revised<-st_read("/home/ptaconet/react/datasets/data_CIV/Ground_truth/civ_groundtruth_objects_segmentation_v_classes_update.gpkg")
ground_truth_data_civ_revised <- cbind(pk = 1:nrow(ground_truth_data_civ_revised), ground_truth_data_civ_revised)
st_write(ground_truth_data_civ_revised, path_to_gpkg_database, "lco_groundtruth_ci_l1", update = TRUE)
ground_truth_data_bf_raw<-st_read("/home/ptaconet/react/datasets/data_BF/Ground_truth/bf_groundtruth_vector_32630.gpkg")
st_write(ground_truth_data_bf_raw, path_to_gpkg_database, "lco_groundtruth_bf_l0", update = TRUE)
ground_truth_data_bf_revised<-st_read("/home/ptaconet/react/datasets/data_BF/Ground_truth/groundtruth_bf_v_classes_update.gpkg")
ground_truth_data_bf_revised <- cbind(pk = 1:nrow(ground_truth_data_bf_revised), ground_truth_data_bf_revised)
st_write(ground_truth_data_bf_revised, path_to_gpkg_database, "lco_groundtruth_ci_l1", update = TRUE)
# LU/LC training/validation parcels with zonal statistics
lulc_zonal_stats_civ<-st_read("/home/ptaconet/react/datasets/data_CIV/Ground_truth/ground_truth_stats.gpkg")
lulc_zonal_stats_civ <- cbind(pk = 1:nrow(lulc_zonal_stats_civ), lulc_zonal_stats_civ)
st_write(lulc_zonal_stats_civ, path_to_gpkg_database, "lco_groundtruth_ci_zonalstats", update = TRUE)
lulc_zonal_stats_bf<-st_read("/home/ptaconet/react/datasets/data_BF/Ground_truth/ground_truth_stats.gpkg")
lulc_zonal_stats_bf <- cbind(pk = 1:nrow(lulc_zonal_stats_bf), lulc_zonal_stats_bf)
st_write(lulc_zonal_stats_bf, path_to_gpkg_database, "lco_groundtruth_bf_zonalstats", update = TRUE)
## LU/LC maps
# BF
cat("loading BF LU/LC rasters...\n")
path_to_LU_L1_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L1.tif"
path_to_LU_L2_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L2.tif"
path_to_LU_L3_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L3.tif"
path_to_LU_L4_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L4.tif"
path_to_LU_L5_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L5.tif"
gdal_translate(path_to_LU_L1_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l1_bf"))
gdal_translate(path_to_LU_L2_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l2_bf"))
gdal_translate(path_to_LU_L3_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l3_bf"))
gdal_translate(path_to_LU_L4_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l4_bf"))
gdal_translate(path_to_LU_L5_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l5_bf"))
path_to_LU_L1_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L1.csv"
path_to_LU_L2_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L2.csv"
path_to_LU_L3_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L3.csv"
path_to_LU_L4_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L4.csv"
path_to_LU_L5_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L5.csv"
LU_L1_classes<-read.csv(path_to_LU_L1_classes)
LU_L2_classes<-read.csv(path_to_LU_L2_classes)
LU_L3_classes<-read.csv(path_to_LU_L3_classes)
LU_L4_classes<-read.csv(path_to_LU_L4_classes)
LU_L5_classes<-read.csv(path_to_LU_L5_classes)
LU_L1_classes$classif_level<-"classificationL1"
LU_L2_classes$classif_level<-"classificationL2"
LU_L3_classes$classif_level<-"classificationL3"
LU_L4_classes$classif_level<-"classificationL4"
LU_L5_classes$classif_level<-"classificationL5"
LU_classes_bf<-rbind(LU_L1_classes,LU_L2_classes,LU_L3_classes,LU_L4_classes,LU_L5_classes) %>%
arrange(classif_level,pixval) %>%
mutate(classif_level=gsub("classification","lco_bf",classif_level)) %>%
mutate(path_to_raster=case_when(classif_level=="lco_l1_bf" ~ path_to_LU_L1_bf,
classif_level=="lco_l2_bf" ~ path_to_LU_L2_bf,
classif_level=="lco_l3_bf" ~ path_to_LU_L3_bf,
classif_level=="lco_l4_bf" ~ path_to_LU_L4_bf,
classif_level=="lco_l5_bf" ~ path_to_LU_L5_bf
))
# CIV
cat("loading CIV LU/LC rasters...\n")
path_to_LU_L1_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L1.tif"
path_to_LU_L2_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L2.tif"
path_to_LU_L3_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L3.tif"
path_to_LU_L4_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L4.tif"
path_to_LU_L5_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L5.tif"
gdal_translate(path_to_LU_L1_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l1_ci"))
gdal_translate(path_to_LU_L2_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l2_ci"))
gdal_translate(path_to_LU_L3_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l3_ci"))
gdal_translate(path_to_LU_L4_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l4_ci"))
gdal_translate(path_to_LU_L5_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l5_ci"))
path_to_LU_L1_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L1.csv"
path_to_LU_L2_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L2.csv"
path_to_LU_L3_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L3.csv"
path_to_LU_L4_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L4.csv"
path_to_LU_L5_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L5.csv"
LU_L1_classes<-read.csv(path_to_LU_L1_classes)
LU_L2_classes<-read.csv(path_to_LU_L2_classes)
LU_L3_classes<-read.csv(path_to_LU_L3_classes)
LU_L4_classes<-read.csv(path_to_LU_L4_classes)
LU_L5_classes<-read.csv(path_to_LU_L5_classes)
LU_L1_classes$classif_level<-"classificationL1"
LU_L2_classes$classif_level<-"classificationL2"
LU_L3_classes$classif_level<-"classificationL3"
LU_L4_classes$classif_level<-"classificationL4"
LU_L5_classes$classif_level<-"classificationL5"
LU_classes_civ<-rbind(LU_L1_classes,LU_L2_classes,LU_L3_classes,LU_L4_classes,LU_L5_classes) %>%
arrange(classif_level,pixval) %>%
mutate(classif_level=gsub("classification","lco_ci",classif_level)) %>%
mutate(path_to_raster=case_when(classif_level=="lco_l1_ci" ~ path_to_LU_L1_civ,
classif_level=="lco_l2_ci" ~ path_to_LU_L2_civ,
classif_level=="lco_l3_ci" ~ path_to_LU_L3_civ,
classif_level=="lco_l4_ci" ~ path_to_LU_L4_civ,
classif_level=="lco_l5_ci" ~ path_to_LU_L5_civ
))
## ESA AFRICA LC
africa_lc_pixval<-read.csv("/home/ptaconet/react/datasets/ESACCI-LC/ESACCI-LC_S2_Prototype_ColorLegend.csv",sep=";") %>%
dplyr::select(NB_LAB,LCCOwnLabel) %>%
setNames(c("pixval","lc_class")) %>%
mutate(classif_level="ESACCI-LC-L4-LC10-Map-20m-P1Y-2016-v1.0") %>%
mutate(path_to_raster="/home/ptaconet/react/datasets/ESACCI-LC/ESACCI-LC-L4-LC10-Map-20m-P1Y-2016-v1.0.tif")
## ESA Globcover
globcover<-gdalUtils::gdalinfo("/home/ptaconet/react/datasets/landcover_globcover_esa/W020N20_ProbaV_LC100_epoch2015_global_v2.0.1_discrete-classification_EPSG-4326.tif")[57:58] %>%
map(~strsplit(.,","))
globcover_lc_class<-globcover[[1]][[1]][2:length(globcover[[1]][[1]])] %>% gsub(" ","",.)
globcover_pixval<-globcover[[2]][[1]][2:length(globcover[[2]][[1]])] %>% gsub(" ","",.) %>% as.integer()
globcover_lc_pixval<-data.frame(pixval=globcover_pixval,lc_class=globcover_lc_class,stringsAsFactors = F) %>%
mutate(classif_level="W020N20_ProbaV_LC100_epoch2015_global_v2.0.1") %>%
mutate(path_to_raster="/home/ptaconet/react/datasets/landcover_globcover_esa/W020N20_ProbaV_LC100_epoch2015_global_v2.0.1_discrete-classification_EPSG-4326.tif")
LU_classes<-rbind(LU_classes_bf,LU_classes_civ,africa_lc_pixval,globcover_lc_pixval) %>%
setNames(c("class_pixel","class_label","layer_label","layer_path"))
layer_id<-unique(LU_classes$layer_label) %>%
as.data.frame(stringsAsFactors=F) %>%
setNames("layer_label") %>%
mutate(layer_id=as.integer(seq(1,nrow(.),1)))
LU_classes<-left_join(LU_classes,layer_id)
dbWriteTable(react_gpkg,"lco_metadata",LU_classes,overwrite=T)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(LU_classes),table="lco_metadata"))
## Built up surfaces
#source("/home/ptaconet/malamodpkg/database/builtup.R)
path_to_builtup_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/bati_raster.tif"
path_to_builtup_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/bati_raster.tif"
gdal_translate(path_to_builtup_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_builtup_ci")) # Tip : Setting Int16 as 'ot' value enables to store source NA as NA in output (and not 0)
gdal_translate(path_to_builtup_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_builtup_bf"))
## Pedology (raster)
path_to_pedology_civ<-"/home/ptaconet/react/datasets/data_CIV/pedology/pedology.tif"
path_to_pedology_bf<-"/home/ptaconet/react/datasets/data_BF/pedology/pedology.tif"
gdal_translate(path_to_pedology_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_pedology_ci"))
gdal_translate(path_to_pedology_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_pedology_bf"))
## Environmental covariates
# Data dictionnary of environmental covariates :
environmental_covariates_dictionary <- read.csv(system.file("extdata/environmental_covariates_dictionary.csv", package = "malamodpkg"),stringsAsFactors = F,fileEncoding = "latin1")
environmental_covariates_dictionary <- cbind(fid = 1:nrow(environmental_covariates_dictionary), environmental_covariates_dictionary)
dbWriteTable(react_gpkg,"env_dictionary",environmental_covariates_dictionary,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(environmental_covariates_dictionary),table="env_dictionary"))
path_to_bf_folder<-"/home/ptaconet/react/datasets/data_BF"
path_to_civ_folder<-"/home/ptaconet/react/datasets/data_CIV"
# timeseries
paths<-c("envCov_TND_M","envCov_TMD_M","envCov_TNW_M","envCov_TMW_M","envCov_TND_V","envCov_TMD_V","envCov_TNW_V","envCov_TMW_V","envCov_RFD_G","envCov_RFD_T","envCov_EVT","envCov_VNI","envCov_VEI","envCov_SMO")
path_to_bf_ts<-paste0(path_to_bf_folder,"/",paths,".csv")
path_to_civ_ts<-paste0(path_to_civ_folder,"/",paths,".csv")
path_to_ts<-c(path_to_bf_ts,path_to_civ_ts)
data_ts<-path_to_ts %>%
map(~read_csv(.)) %>%
do.call(rbind,.)
data_ts <- cbind(fid = 1:nrow(data_ts), data_ts)
dbWriteTable(react_gpkg,"env_ts",data_ts,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(data_ts),table="env_ts"))
# nightcatch
paths<-c("envCov_RFH","envCov_WDR","envCov_WSP","envCov_LMN","envCov_LNL")
path_to_bf_nightcatch<-paste0(path_to_bf_folder,"/",paths,".csv")
path_to_civ_nightcatch<-paste0(path_to_civ_folder,"/",paths,".csv")
path_to_nightcatch<-c(path_to_bf_nightcatch,path_to_civ_nightcatch)
data_nightcatch<-path_to_nightcatch %>%
map(~read_csv(.)) %>%
do.call(rbind,.)
data_nightcatch <- cbind(fid = 1:nrow(data_nightcatch), data_nightcatch)
dbWriteTable(react_gpkg,"env_nightcatch",data_nightcatch,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(data_nightcatch),table="env_nightcatch"))
# static
paths<-c("envCov_TEL_TSL_TAS_WAC_TCI_TWI","envCov_WAD_WMD_WLS_WAL","envCov_POP","envCov_POH","envCov_BDE","envCov_BCH","envCov_HYS")
path_to_bf_static<-paste0(path_to_bf_folder,"/",paths,".csv")
path_to_civ_static<-paste0(path_to_civ_folder,"/",paths,".csv")
path_to_static<-c(path_to_bf_static,path_to_civ_static)
data_static<-path_to_static %>%
map(~read_csv(.)) %>%
do.call(rbind,.)
data_static <- cbind(fid = 1:nrow(data_static), data_static)
dbWriteTable(react_gpkg,"env_static",data_static,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(data_static),table="env_static"))
# landcover
path_to_lsm_civ<-"/home/ptaconet/react/datasets/data_CIV/envCov_LSM.csv"
path_to_lsm_bf<-"/home/ptaconet/react/datasets/data_BF/envCov_LSM.csv"
lsm<-rbind(read.csv(path_to_lsm_civ,stringsAsFactors = F),read.csv(path_to_lsm_bf,stringsAsFactors = F))
lsm <- cbind(fid = 1:nrow(lsm), lsm)
dbWriteTable(react_gpkg,"env_lsm",lsm,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(lsm),table="env_lsm"))
dbSendQuery(react_gpkg,"VACUUM") # It is very important to Vacuum. Not vacuuming may prevent the DB to be opened.
dbDisconnect(react_gpkg)
dbSendQuery(react_gpkg_light,"VACUUM") # It is very important to Vacuum. Not vacuuming may prevent the DB to be opened.
dbDisconnect(react_gpkg_light)
## Create data dictionnary
data_dictionnary$label <- data_dictionnary$type <- data_dictionnary$description <- data_dictionnary$additional_information <- NA
# fill-in some columns
data_dictionnary <- data_dictionnary %>%
mutate(label = case_when(
name=="fid" ~ "unique numeric identifier",
name=="codevillage" ~ "alpha-3 code identifier of the village",
name=="codepays" ~ "alpha-2 code identifier of the country",
)) %>%
mutate(type = case_when(
name %in% c("fid","codevillage") ~ "string"
))
write.csv(data_dictionnary,"data_dictionnary.csv",row.names = F)
ptaconet/malamodpkg documentation built on Feb. 12, 2020, 3:45 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
require(RSQLite)
require(dplyr)
require(sf)
require(rgdal)
require(gdalUtils)
require(raster)
require(gdalUtils)
require(readxl)
require(lubridate)
require(stringr)
require(purrr)
require(tidyverse)
require(googlesheets4)
setwd("/home/ptaconet/react/datasets/")
path_to_amal_database<-"miscellaneous_data/React_dbase_V7.db"
path_to_gpkg_database<-"react_db.gpkg" # Empty gpkg template is available here : http://www.geopackage.org/data/empty.gpkg
path_to_gpkg_light_database<-"react_db_light.gpkg"
path_to_metadata_table<-"https://docs.google.com/spreadsheets/d/1O7JUhoAzXtoFWjiLOz7HgDLe--zxkZKR96_BhzU7DME/edit?usp=sharing"
download.file("http://www.geopackage.org/data/empty.gpkg",path_to_gpkg_database)
file.copy(path_to_gpkg_database,path_to_gpkg_light_database,overwrite =T)
## Connect to DBs
amal_db <- dbConnect(RSQLite::SQLite(),path_to_amal_database)
react_gpkg <- dbConnect(RSQLite::SQLite(),path_to_gpkg_database)
react_gpkg_light <- dbConnect(RSQLite::SQLite(),path_to_gpkg_light_database)
## Open and load tables metadata and metadata_mapping
metadata_tables<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "metadata_tables",col_types="c")
metadata_contacts<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "contacts",col_types="c")
metadata_mapping<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "metadata_mapping",col_types="c")
metadata_data_dictionary_table<-googlesheets4::read_sheet(path_to_metadata_table,sheet = "data_dictionary_columns",col_types="c")
dbWriteTable(react_gpkg,"metadata_tables",metadata_tables,overwrite=TRUE)
dbWriteTable(react_gpkg,"metadata_contacts",metadata_contacts,overwrite=TRUE)
dbWriteTable(react_gpkg,"metadata_mapping",metadata_mapping,overwrite=TRUE)
dbWriteTable(react_gpkg,"metadata_data_dictionary_table",metadata_data_dictionary_table,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_tables",metadata_tables %>% filter(identifier %in% c(
"recensement_individus_l0",
"recensement_menages_l0",
"recensement_villages_l1",
"entomo_comportementhumain_l0",
"entomo_csh_ctrlequalite_l0",
"entomo_csh_metadata_l0",
"entomo_csh_metadata_l1",
"entomo_idmoustiques_l0",
"entomo_hobo_l0",
"entomo_hygro_l0",
"entomo_baro_l0",
"epidemio_active_bf_l0",
"epidemio_active_ci_l0",
"epidemio_active_l1",
"epidemio_passive_l0",
"epidemio_goutteepaisse_l1",
"interv_ivm_bf_recenses_l0",
"interv_ivm_bf_traites_l0",
"interv_irs_bf_ctrlequalite_chimique_l0",
"interv_irs_ci_ctrlequalite_chimique_l0",
"interv_larvicide_ci_ctrlequalite_l0",
"interv_irs_ctrlequalite_cone_l0",
"interv_iec_bf_ctrlequalite_l0",
"interv_iec_ci_ctrlequalite_l0",
"contexte_paysafriqueouest",
"contexte_villesafriqueouest",
"contexte_frontieresreact",
"metadata_tables",
"metadata_contacts",
"metadata_mapping",
"metadata_data_dictionary_table")),overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_contacts",metadata_contacts,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_mapping",metadata_mapping,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"metadata_data_dictionary_table",metadata_data_dictionary_table,overwrite=TRUE)
## Create and load tables :
# initiate data dictionary
data_dictionnary <- data.frame(name=character(),table=character(),label=character(),type=character(),description=character(),additional_information=character())
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_tables),table="metadata_tables"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_contacts),table="metadata_contacts"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_mapping),table="metadata_mapping"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(metadata_data_dictionary_table),table="metadata_data_dictionary_table"))
# recensement_individus_l0
source("/home/ptaconet/malamodpkg/database/recensement_individus_l0.R") # source("https://raw.githubusercontent.com/ptaconet/malamodpkg/master/database/recensement_individus_l0.R")
individus <- cbind(fid = 1:nrow(individus), individus)
dbWriteTable(react_gpkg,"recensement_individus_l0",individus,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"recensement_individus_l0",individus,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(individus),table="recensement_individus_l0"))
# recensement_menages_l0
#source("/home/ptaconet/malamodpkg/database/raw_menages.R")
source("/home/ptaconet/malamodpkg/database/recensement_menages_l0.R")
menages_sf<-st_as_sf(menages,coords = c("coordgpsLongitude", "coordgpsLatitude"), crs = 4326 )
menages_sf<-cbind(menages_sf,st_coordinates(menages_sf))
st_write(menages_sf, path_to_gpkg_database, "recensement_menages_l0", delete_layer = TRUE)
st_write(menages_sf, path_to_gpkg_light_database, "recensement_menages_l0", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(menages_sf),table="recensement_menages_l0"))
# recensement_villages_l1
source("/home/ptaconet/malamodpkg/database/recensement_villages_l1.R")
villages_sf<-st_as_sf(villages,coords = c("X", "Y"), crs = 4326 )
villages_sf<-cbind(villages_sf,st_coordinates(villages_sf))
st_write(villages_sf, path_to_gpkg_database, "recensement_villages_l1", delete_layer = TRUE)
st_write(villages_sf, path_to_gpkg_light_database, "recensement_villages_l1", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(villages_sf),table="recensement_villages_l1"))
# entomo_comportementhumain_l0
source("/home/ptaconet/malamodpkg/database/entomo_comportementhumain_l0.R")
df_humanbehavior_sf<-st_as_sf(df_humanbehavior,coords = c("longitude", "latitude"), crs = 4326 )
df_humanbehavior_sf <- cbind(fid = 1:nrow(df_humanbehavior_sf), df_humanbehavior_sf)
st_write(df_humanbehavior_sf, path_to_gpkg_database, "entomo_comportementhumain_l0", delete_layer = TRUE)
st_write(df_humanbehavior_sf, path_to_gpkg_light_database, "entomo_comportementhumain_l0", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_humanbehavior_sf),table="entomo_comportementhumain_l0"))
# entomo_csh_ctrlequalite_l0
source("/home/ptaconet/malamodpkg/database/entomo_csh_ctrlequalite_l0.R") # créé le data.frame nommé "all_data" contenant les données brutes de supervision capture
supervcapture_sf<-st_as_sf(all_data,coords = c("longitude", "latitude"), crs = 4326 )
supervcapture_sf<-cbind(supervcapture_sf,st_coordinates(supervcapture_sf))
st_write(supervcapture_sf, path_to_gpkg_database, "entomo_csh_ctrlequalite_l0", delete_layer = TRUE)
st_write(supervcapture_sf, path_to_gpkg_light_database, "entomo_csh_ctrlequalite_l0", delete_layer = TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(supervcapture_sf),table="entomo_csh_ctrlequalite_l0"))
# entomo_csh_metadata_l0
source("/home/ptaconet/malamodpkg/database/entomo_csh_metadata_l0.R")
raw_dates_hlc <- cbind(fid = 1:nrow(raw_dates_hlc), raw_dates_hlc)
dbWriteTable(react_gpkg,"entomo_csh_metadata_l0",raw_dates_hlc,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_csh_metadata_l0",raw_dates_hlc,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(raw_dates_hlc),table="entomo_csh_metadata_l0"))
# entomo_csh_metadata_l1
source("/home/ptaconet/malamodpkg/database/entomo_csh_metadata_l1.R")
hlc_dates_loc_times_sf<-st_as_sf(hlc_dates_loc_times,coords = c("longitude", "latitude"), crs = 4326 )
hlc_dates_loc_times_sf<-cbind(hlc_dates_loc_times_sf,st_coordinates(hlc_dates_loc_times_sf))
st_write(hlc_dates_loc_times_sf, path_to_gpkg_database, "entomo_csh_metadata_l1", delete_layer = TRUE) # use delete_layer=TRUE to delete first
st_write(hlc_dates_loc_times_sf, path_to_gpkg_light_database, "entomo_csh_metadata_l1", delete_layer = TRUE) # use delete_layer=TRUE to delete first
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(hlc_dates_loc_times_sf),table="entomo_csh_metadata_l1"))
# entomo_idmoustiques_l0
source("/home/ptaconet/malamodpkg/database/entomo_idmoustiques_l0.R")
entomo <- cbind(fid = 1:nrow(df_mosquitoes), df_mosquitoes)
dbWriteTable(react_gpkg,"entomo_idmoustiques_l0",entomo,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_idmoustiques_l0",entomo,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(entomo),table="entomo_idmoustiques_l0"))
# Entomo - micro-climate from sensors
source("/home/ptaconet/malamodpkg/database/entomo_env_sensors.R")
df_hobo <- cbind(fid = 1:nrow(df_hobo), df_hobo)
df_hygro <- cbind(fid = 1:nrow(df_hygro), df_hygro)
df_baro <- cbind(fid = 1:nrow(df_baro), df_baro)
dbWriteTable(react_gpkg,"entomo_hobo_l0",df_hobo,overwrite=TRUE)
dbWriteTable(react_gpkg,"entomo_hygro_l0",df_hygro,overwrite=TRUE)
dbWriteTable(react_gpkg,"entomo_baro_l0",df_baro,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_hobo_l0",df_hobo,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_hygro_l0",df_hygro,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"entomo_baro_l0",df_baro,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_hobo),table="entomo_hobo_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_hygro),table="entomo_hygro_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(df_baro),table="entomo_baro_l0"))
# epidemio_xxx (toutes les tables épidémio)
source("/home/ptaconet/malamodpkg/database/epidemio.R")
act <- cbind(fid = 1:nrow(act), act)
BF_act <- cbind(fid = 1:nrow(BF_act), BF_act)
CI_act <- cbind(fid = 1:nrow(CI_act), CI_act)
pas <- cbind(fid = 1:nrow(pas), pas)
GE_stats <- cbind(fid = 1:nrow(GE_stats), GE_stats)
dbWriteTable(react_gpkg,"epidemio_active_l1",act,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_active_bf_l0",BF_act,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_active_ci_l0",CI_act,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_passive_l0",pas,overwrite=TRUE)
dbWriteTable(react_gpkg,"epidemio_goutteepaisse_l1",GE_stats,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_active_l1",act,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_active_bf_l0",BF_act,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_active_ci_l0",CI_act,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_passive_l0",pas,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"epidemio_goutteepaisse_l1",GE_stats,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(act),table="epidemio_active_l1"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(BF_act),table="epidemio_active_bf_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(CI_act),table="epidemio_active_ci_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(pas),table="epidemio_passive_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(GE_stats),table="epidemio_goutteepaisse_l1"))
# interv_ivm_l0
source("/home/ptaconet/malamodpkg/database/interv_ivm_l0.R")
interv_ivm_traites_l0 <- cbind(fid = 1:nrow(interv_ivm_traites_l0), interv_ivm_traites_l0)
interv_ivm_recenses_l0 <- cbind(fid = 1:nrow(interv_ivm_recenses_l0), interv_ivm_recenses_l0)
dbWriteTable(react_gpkg,"interv_ivm_bf_traites_l0",interv_ivm_traites_l0,overwrite=TRUE)
dbWriteTable(react_gpkg,"interv_ivm_bf_recenses_l0",interv_ivm_recenses_l0,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_ivm_bf_traites_l0",interv_ivm_traites_l0,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_ivm_bf_recenses_l0",interv_ivm_recenses_l0,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(interv_ivm_traites_l0),table="interv_ivm_bf_traites_l0"))
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(interv_ivm_recenses_l0),table="interv_ivm_bf_recenses_l0"))
#interv_larvicide_ci_ctrlequalite_l0
source("/home/ptaconet/malamodpkg/database/interv_larvicide_ci_ctrlequalite_l0.R")
larvicide_ci_ctrlequalite <- cbind(fid = 1:nrow(larvicide_ci_ctrlequalite), larvicide_ci_ctrlequalite)
dbWriteTable(react_gpkg,"interv_larvicide_ci_ctrlequalite_l0",larvicide_ci_ctrlequalite,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_larvicide_ci_ctrlequalite_l0",larvicide_ci_ctrlequalite,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(larvicide_ci_ctrlequalite),table="interv_larvicide_ci_ctrlequalite_l0"))
#interv_irs_ctrlequalite_cone_l0
source("/home/ptaconet/malamodpkg/database/interv_irs_ctrlequalite_cone_l0.R")
interv_irs_ctrlequalite_cone_l0 <- cbind(fid = 1:nrow(interv_irs_ctrlequalite_cone_l0), interv_irs_ctrlequalite_cone_l0)
dbWriteTable(react_gpkg,"interv_irs_ctrlequalite_cone_l0",interv_irs_ctrlequalite_cone_l0,overwrite=TRUE)
dbWriteTable(react_gpkg_light,"interv_irs_ctrlequalite_cone_l0",interv_irs_ctrlequalite_cone_l0,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(interv_irs_ctrlequalite_cone_l0),table="interv_irs_ctrlequalite_cone_l0"))
# contexte_paysafriqueouest downloaded here : https://data.humdata.org/dataset/west-and-central-africa-administrative-boundaries-levels
adm_bound_sf<-read_sf("/home/ptaconet/react/datasets/miscellaneous_data/wca_adm0/wca_adm0.shp")
adm_bound_sf<-st_transform(adm_bound_sf,crs=4326)
st_write(adm_bound_sf, path_to_gpkg_database, "contexte_paysafriqueouest", update = TRUE)
st_write(adm_bound_sf, path_to_gpkg_light_database, "contexte_paysafriqueouest", update = TRUE)
# contexte_villesafriqueouest
ancillary_africa_cities<-read_sf("/home/ptaconet/react/datasets/miscellaneous_data/africa_places/places.shp")
ancillary_africa_cities<-st_intersection(ancillary_africa_cities,adm_bound_sf)
st_write(ancillary_africa_cities, path_to_gpkg_database, "contexte_villesafriqueouest", update = TRUE)
st_write(ancillary_africa_cities, path_to_gpkg_light_database, "contexte_villesafriqueouest", update = TRUE)
# contexte_frontieresreact
roi_civ_sf<-read_sf("/home/ptaconet/react/datasets/data_CIV/ROI.kml")
roi_civ_sf$codepays<-"CI"
roi_civ_sf<-roi_civ_sf[,"codepays"]
roi_civ_sf<-st_cast(roi_civ_sf,"POLYGON")
roi_bf_sf<-read_sf("/home/ptaconet/react/datasets/data_BF/ROI.kml")
roi_bf_sf$codepays<-"BF"
roi_bf_sf<-roi_bf_sf[,"codepays"]
roi_bf_sf<-st_zm(roi_bf_sf,drop = TRUE, what = "ZM")
roi<-rbind(roi_civ_sf,roi_bf_sf)
roi<-st_transform(roi,crs=32630)
st_write(roi, path_to_gpkg_database, "contexte_frontieresreact", update = TRUE)
st_write(roi, path_to_gpkg_light_database, "contexte_frontieresreact", update = TRUE)
# LU/LC training and validation parcels (raw and segmented)
ground_truth_data_civ_raw<-st_read("/home/ptaconet/react/datasets/data_CIV/Ground_truth/civ_groundtruth_vector_32630.gpkg")
ground_truth_data_civ_raw <- cbind(pk = 1:nrow(ground_truth_data_civ_raw), ground_truth_data_civ_raw)
st_write(ground_truth_data_civ_raw, path_to_gpkg_database, "lco_groundtruth_ci_l0", update = TRUE)
ground_truth_data_civ_revised<-st_read("/home/ptaconet/react/datasets/data_CIV/Ground_truth/civ_groundtruth_objects_segmentation_v_classes_update.gpkg")
ground_truth_data_civ_revised <- cbind(pk = 1:nrow(ground_truth_data_civ_revised), ground_truth_data_civ_revised)
st_write(ground_truth_data_civ_revised, path_to_gpkg_database, "lco_groundtruth_ci_l1", update = TRUE)
ground_truth_data_bf_raw<-st_read("/home/ptaconet/react/datasets/data_BF/Ground_truth/bf_groundtruth_vector_32630.gpkg")
st_write(ground_truth_data_bf_raw, path_to_gpkg_database, "lco_groundtruth_bf_l0", update = TRUE)
ground_truth_data_bf_revised<-st_read("/home/ptaconet/react/datasets/data_BF/Ground_truth/groundtruth_bf_v_classes_update.gpkg")
ground_truth_data_bf_revised <- cbind(pk = 1:nrow(ground_truth_data_bf_revised), ground_truth_data_bf_revised)
st_write(ground_truth_data_bf_revised, path_to_gpkg_database, "lco_groundtruth_ci_l1", update = TRUE)
# LU/LC training/validation parcels with zonal statistics
lulc_zonal_stats_civ<-st_read("/home/ptaconet/react/datasets/data_CIV/Ground_truth/ground_truth_stats.gpkg")
lulc_zonal_stats_civ <- cbind(pk = 1:nrow(lulc_zonal_stats_civ), lulc_zonal_stats_civ)
st_write(lulc_zonal_stats_civ, path_to_gpkg_database, "lco_groundtruth_ci_zonalstats", update = TRUE)
lulc_zonal_stats_bf<-st_read("/home/ptaconet/react/datasets/data_BF/Ground_truth/ground_truth_stats.gpkg")
lulc_zonal_stats_bf <- cbind(pk = 1:nrow(lulc_zonal_stats_bf), lulc_zonal_stats_bf)
st_write(lulc_zonal_stats_bf, path_to_gpkg_database, "lco_groundtruth_bf_zonalstats", update = TRUE)
## LU/LC maps
# BF
cat("loading BF LU/LC rasters...\n")
path_to_LU_L1_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L1.tif"
path_to_LU_L2_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L2.tif"
path_to_LU_L3_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L3.tif"
path_to_LU_L4_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L4.tif"
path_to_LU_L5_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L5.tif"
gdal_translate(path_to_LU_L1_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l1_bf"))
gdal_translate(path_to_LU_L2_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l2_bf"))
gdal_translate(path_to_LU_L3_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l3_bf"))
gdal_translate(path_to_LU_L4_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l4_bf"))
gdal_translate(path_to_LU_L5_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l5_bf"))
path_to_LU_L1_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L1.csv"
path_to_LU_L2_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L2.csv"
path_to_LU_L3_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L3.csv"
path_to_LU_L4_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L4.csv"
path_to_LU_L5_classes<-"/home/ptaconet/react/datasets/data_BF/Classification/classification_L5.csv"
LU_L1_classes<-read.csv(path_to_LU_L1_classes)
LU_L2_classes<-read.csv(path_to_LU_L2_classes)
LU_L3_classes<-read.csv(path_to_LU_L3_classes)
LU_L4_classes<-read.csv(path_to_LU_L4_classes)
LU_L5_classes<-read.csv(path_to_LU_L5_classes)
LU_L1_classes$classif_level<-"classificationL1"
LU_L2_classes$classif_level<-"classificationL2"
LU_L3_classes$classif_level<-"classificationL3"
LU_L4_classes$classif_level<-"classificationL4"
LU_L5_classes$classif_level<-"classificationL5"
LU_classes_bf<-rbind(LU_L1_classes,LU_L2_classes,LU_L3_classes,LU_L4_classes,LU_L5_classes) %>%
arrange(classif_level,pixval) %>%
mutate(classif_level=gsub("classification","lco_bf",classif_level)) %>%
mutate(path_to_raster=case_when(classif_level=="lco_l1_bf" ~ path_to_LU_L1_bf,
classif_level=="lco_l2_bf" ~ path_to_LU_L2_bf,
classif_level=="lco_l3_bf" ~ path_to_LU_L3_bf,
classif_level=="lco_l4_bf" ~ path_to_LU_L4_bf,
classif_level=="lco_l5_bf" ~ path_to_LU_L5_bf
))
# CIV
cat("loading CIV LU/LC rasters...\n")
path_to_LU_L1_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L1.tif"
path_to_LU_L2_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L2.tif"
path_to_LU_L3_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L3.tif"
path_to_LU_L4_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L4.tif"
path_to_LU_L5_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L5.tif"
gdal_translate(path_to_LU_L1_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l1_ci"))
gdal_translate(path_to_LU_L2_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l2_ci"))
gdal_translate(path_to_LU_L3_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l3_ci"))
gdal_translate(path_to_LU_L4_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l4_ci"))
gdal_translate(path_to_LU_L5_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_l5_ci"))
path_to_LU_L1_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L1.csv"
path_to_LU_L2_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L2.csv"
path_to_LU_L3_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L3.csv"
path_to_LU_L4_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L4.csv"
path_to_LU_L5_classes<-"/home/ptaconet/react/datasets/data_CIV/Classification/classification_L5.csv"
LU_L1_classes<-read.csv(path_to_LU_L1_classes)
LU_L2_classes<-read.csv(path_to_LU_L2_classes)
LU_L3_classes<-read.csv(path_to_LU_L3_classes)
LU_L4_classes<-read.csv(path_to_LU_L4_classes)
LU_L5_classes<-read.csv(path_to_LU_L5_classes)
LU_L1_classes$classif_level<-"classificationL1"
LU_L2_classes$classif_level<-"classificationL2"
LU_L3_classes$classif_level<-"classificationL3"
LU_L4_classes$classif_level<-"classificationL4"
LU_L5_classes$classif_level<-"classificationL5"
LU_classes_civ<-rbind(LU_L1_classes,LU_L2_classes,LU_L3_classes,LU_L4_classes,LU_L5_classes) %>%
arrange(classif_level,pixval) %>%
mutate(classif_level=gsub("classification","lco_ci",classif_level)) %>%
mutate(path_to_raster=case_when(classif_level=="lco_l1_ci" ~ path_to_LU_L1_civ,
classif_level=="lco_l2_ci" ~ path_to_LU_L2_civ,
classif_level=="lco_l3_ci" ~ path_to_LU_L3_civ,
classif_level=="lco_l4_ci" ~ path_to_LU_L4_civ,
classif_level=="lco_l5_ci" ~ path_to_LU_L5_civ
))
## ESA AFRICA LC
africa_lc_pixval<-read.csv("/home/ptaconet/react/datasets/ESACCI-LC/ESACCI-LC_S2_Prototype_ColorLegend.csv",sep=";") %>%
dplyr::select(NB_LAB,LCCOwnLabel) %>%
setNames(c("pixval","lc_class")) %>%
mutate(classif_level="ESACCI-LC-L4-LC10-Map-20m-P1Y-2016-v1.0") %>%
mutate(path_to_raster="/home/ptaconet/react/datasets/ESACCI-LC/ESACCI-LC-L4-LC10-Map-20m-P1Y-2016-v1.0.tif")
## ESA Globcover
globcover<-gdalUtils::gdalinfo("/home/ptaconet/react/datasets/landcover_globcover_esa/W020N20_ProbaV_LC100_epoch2015_global_v2.0.1_discrete-classification_EPSG-4326.tif")[57:58] %>%
map(~strsplit(.,","))
globcover_lc_class<-globcover[[1]][[1]][2:length(globcover[[1]][[1]])] %>% gsub(" ","",.)
globcover_pixval<-globcover[[2]][[1]][2:length(globcover[[2]][[1]])] %>% gsub(" ","",.) %>% as.integer()
globcover_lc_pixval<-data.frame(pixval=globcover_pixval,lc_class=globcover_lc_class,stringsAsFactors = F) %>%
mutate(classif_level="W020N20_ProbaV_LC100_epoch2015_global_v2.0.1") %>%
mutate(path_to_raster="/home/ptaconet/react/datasets/landcover_globcover_esa/W020N20_ProbaV_LC100_epoch2015_global_v2.0.1_discrete-classification_EPSG-4326.tif")
LU_classes<-rbind(LU_classes_bf,LU_classes_civ,africa_lc_pixval,globcover_lc_pixval) %>%
setNames(c("class_pixel","class_label","layer_label","layer_path"))
layer_id<-unique(LU_classes$layer_label) %>%
as.data.frame(stringsAsFactors=F) %>%
setNames("layer_label") %>%
mutate(layer_id=as.integer(seq(1,nrow(.),1)))
LU_classes<-left_join(LU_classes,layer_id)
dbWriteTable(react_gpkg,"lco_metadata",LU_classes,overwrite=T)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(LU_classes),table="lco_metadata"))
## Built up surfaces
#source("/home/ptaconet/malamodpkg/database/builtup.R)
path_to_builtup_civ<-"/home/ptaconet/react/datasets/data_CIV/Classification/bati_raster.tif"
path_to_builtup_bf<-"/home/ptaconet/react/datasets/data_BF/Classification/bati_raster.tif"
gdal_translate(path_to_builtup_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_builtup_ci")) # Tip : Setting Int16 as 'ot' value enables to store source NA as NA in output (and not 0)
gdal_translate(path_to_builtup_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_builtup_bf"))
## Pedology (raster)
path_to_pedology_civ<-"/home/ptaconet/react/datasets/data_CIV/pedology/pedology.tif"
path_to_pedology_bf<-"/home/ptaconet/react/datasets/data_BF/pedology/pedology.tif"
gdal_translate(path_to_pedology_civ,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_pedology_ci"))
gdal_translate(path_to_pedology_bf,path_to_gpkg_database,ot="Int16",of="GPKG",b=1,co=c("APPEND_SUBDATASET=YES","RASTER_TABLE=lco_pedology_bf"))
## Environmental covariates
# Data dictionnary of environmental covariates :
environmental_covariates_dictionary <- read.csv(system.file("extdata/environmental_covariates_dictionary.csv", package = "malamodpkg"),stringsAsFactors = F,fileEncoding = "latin1")
environmental_covariates_dictionary <- cbind(fid = 1:nrow(environmental_covariates_dictionary), environmental_covariates_dictionary)
dbWriteTable(react_gpkg,"env_dictionary",environmental_covariates_dictionary,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(environmental_covariates_dictionary),table="env_dictionary"))
path_to_bf_folder<-"/home/ptaconet/react/datasets/data_BF"
path_to_civ_folder<-"/home/ptaconet/react/datasets/data_CIV"
# timeseries
paths<-c("envCov_TND_M","envCov_TMD_M","envCov_TNW_M","envCov_TMW_M","envCov_TND_V","envCov_TMD_V","envCov_TNW_V","envCov_TMW_V","envCov_RFD_G","envCov_RFD_T","envCov_EVT","envCov_VNI","envCov_VEI","envCov_SMO")
path_to_bf_ts<-paste0(path_to_bf_folder,"/",paths,".csv")
path_to_civ_ts<-paste0(path_to_civ_folder,"/",paths,".csv")
path_to_ts<-c(path_to_bf_ts,path_to_civ_ts)
data_ts<-path_to_ts %>%
map(~read_csv(.)) %>%
do.call(rbind,.)
data_ts <- cbind(fid = 1:nrow(data_ts), data_ts)
dbWriteTable(react_gpkg,"env_ts",data_ts,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(data_ts),table="env_ts"))
# nightcatch
paths<-c("envCov_RFH","envCov_WDR","envCov_WSP","envCov_LMN","envCov_LNL")
path_to_bf_nightcatch<-paste0(path_to_bf_folder,"/",paths,".csv")
path_to_civ_nightcatch<-paste0(path_to_civ_folder,"/",paths,".csv")
path_to_nightcatch<-c(path_to_bf_nightcatch,path_to_civ_nightcatch)
data_nightcatch<-path_to_nightcatch %>%
map(~read_csv(.)) %>%
do.call(rbind,.)
data_nightcatch <- cbind(fid = 1:nrow(data_nightcatch), data_nightcatch)
dbWriteTable(react_gpkg,"env_nightcatch",data_nightcatch,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(data_nightcatch),table="env_nightcatch"))
# static
paths<-c("envCov_TEL_TSL_TAS_WAC_TCI_TWI","envCov_WAD_WMD_WLS_WAL","envCov_POP","envCov_POH","envCov_BDE","envCov_BCH","envCov_HYS")
path_to_bf_static<-paste0(path_to_bf_folder,"/",paths,".csv")
path_to_civ_static<-paste0(path_to_civ_folder,"/",paths,".csv")
path_to_static<-c(path_to_bf_static,path_to_civ_static)
data_static<-path_to_static %>%
map(~read_csv(.)) %>%
do.call(rbind,.)
data_static <- cbind(fid = 1:nrow(data_static), data_static)
dbWriteTable(react_gpkg,"env_static",data_static,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(data_static),table="env_static"))
# landcover
path_to_lsm_civ<-"/home/ptaconet/react/datasets/data_CIV/envCov_LSM.csv"
path_to_lsm_bf<-"/home/ptaconet/react/datasets/data_BF/envCov_LSM.csv"
lsm<-rbind(read.csv(path_to_lsm_civ,stringsAsFactors = F),read.csv(path_to_lsm_bf,stringsAsFactors = F))
lsm <- cbind(fid = 1:nrow(lsm), lsm)
dbWriteTable(react_gpkg,"env_lsm",lsm,overwrite=TRUE)
data_dictionnary <- rbind(data_dictionnary,data.frame(name=colnames(lsm),table="env_lsm"))
dbSendQuery(react_gpkg,"VACUUM") # It is very important to Vacuum. Not vacuuming may prevent the DB to be opened.
dbDisconnect(react_gpkg)
dbSendQuery(react_gpkg_light,"VACUUM") # It is very important to Vacuum. Not vacuuming may prevent the DB to be opened.
dbDisconnect(react_gpkg_light)
## Create data dictionnary
data_dictionnary$label <- data_dictionnary$type <- data_dictionnary$description <- data_dictionnary$additional_information <- NA
# fill-in some columns
data_dictionnary <- data_dictionnary %>%
mutate(label = case_when(
name=="fid" ~ "unique numeric identifier",
name=="codevillage" ~ "alpha-3 code identifier of the village",
name=="codepays" ~ "alpha-2 code identifier of the country",
)) %>%
mutate(type = case_when(
name %in% c("fid","codevillage") ~ "string"
))
write.csv(data_dictionnary,"data_dictionnary.csv",row.names = F)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.