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DREAL Pays de la Loire
Centre de Services de la Donnée
sgbd_datamart
Commits
6925150c
Commit
6925150c
authored
6 months ago
by
Franck.Gaspard
Committed by
Juliette Engelaere-Lefebvre
6 months ago
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adaptation de data-raw/chargement_ocsge à la nouvelle livraison de l'OCSGE
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adaptation de data-raw/chargement_ocsge à la nouvelle livraison de l'OCSGE
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data-raw/chargement_ocsge.R
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6925150c
# chargement_ocsge
# chargement_ocsge
library
(
magritt
)
library
(
magritt
r
)
rm
(
list
=
ls
())
rm
(
list
=
ls
())
...
@@ -17,15 +17,15 @@ con_referentiels <- DBI::dbConnect(
...
@@ -17,15 +17,15 @@ con_referentiels <- DBI::dbConnect(
)
)
# fonction get_ocsge_dep_com ---------
# fonctions get_ocsge_dep_com ---------
# elle decoupe une couche dep ocsge millesimée aux contours des communes de la bd topo
# elle decoupe une couche dep ocsge millesimée aux contours des communes de la bd topo
# et renvoie une ligne par commune, usage et couverture
# et renvoie une ligne par commune, usage et couverture
get_ocsge_dep_com
<-
function
(
dep
,
mil
=
"2016"
)
{
## ocsge ancienne génération -----
query
=
paste0
(
"SELECT com.code_insee, ocsge.couverture, ocsge.usage, ocsge.millesime, "
,
get_ocsge_dep_com_anc_gen
<-
function
(
dep
,
mil
=
"2016"
)
{
query
=
paste0
(
"SELECT com.code_insee, ocsge.couverture, ocsge.usage, ocsge.millesime, "
,
"SUM(ST_Area(ST_intersection(ocsge.the_geom, com.the_geom))) AS surf_intersection_m2 "
,
"SUM(ST_Area(ST_intersection(ocsge.the_geom, com.the_geom))) AS surf_intersection_m2 "
,
"FROM ocsge.n_occupation_sol_"
,
mil
,
"_0"
,
dep
,
" AS ocsge, "
,
"FROM ocs
_
ge
_ancienne_generation
.n_occupation_sol_"
,
mil
,
"_0"
,
dep
,
" AS ocsge, "
,
"bdtopo_v3.n_bdt_commune_s_r52 AS com "
,
"bdtopo_v3.n_bdt_commune_s_r52 AS com "
,
"WHERE ST_intersects(ocsge.the_geom, com.the_geom)"
,
"WHERE ST_intersects(ocsge.the_geom, com.the_geom)"
,
"GROUP BY com.code_insee, ocsge.couverture, ocsge.usage, ocsge.millesime"
,
"GROUP BY com.code_insee, ocsge.couverture, ocsge.usage, ocsge.millesime"
,
...
@@ -33,95 +33,279 @@ get_ocsge_dep_com <- function(dep, mil = "2016") {
...
@@ -33,95 +33,279 @@ get_ocsge_dep_com <- function(dep, mil = "2016") {
DBI
::
dbGetQuery
(
con_referentiels
,
query
)
DBI
::
dbGetQuery
(
con_referentiels
,
query
)
}
}
## ocsge nouvelle génération --------
get_ocsge_dep_com_nouv_gen
<-
function
(
dep
,
mil
=
"2019"
)
{
query
=
paste0
(
"SELECT com.code_insee, ocsge.code_cs, ocsge.code_us, ocsge.millesime, "
,
"SUM(ST_Area(ST_intersection(ocsge.the_geom, com.the_geom))) AS surf_intersection_m2 "
,
"FROM ocs_ge_nouvelle_generation.n_ocsge_occupation_sol_"
,
mil
,
"_s_d"
,
dep
,
" AS ocsge, "
,
"bdtopo_v3.n_bdt_commune_s_r52 AS com "
,
"WHERE ST_intersects(ocsge.the_geom, com.the_geom)"
,
"GROUP BY com.code_insee, ocsge.code_cs, ocsge.code_us, ocsge.millesime"
,
";"
)
DBI
::
dbGetQuery
(
con_referentiels
,
query
)
}
# application de la fonction aux 5 départements et aux 2 millésimes -------
# calcul d'ocsge ancienne génération ---------
ocsge_pdl
<-
purrr
::
map2_dfr
(
ocsge_pdl_anc_gen
<-
purrr
::
map2_dfr
(
.x
=
rep
(
c
(
"44"
,
"49"
,
"53"
,
"72"
,
"85"
),
2
),
.x
=
rep
(
c
(
"44"
,
"49"
,
"53"
,
"72"
,
"85"
),
2
),
.y
=
c
(
rep
(
"2013man"
,
5
),
rep
(
"2016"
,
5
)),
.y
=
c
(
rep
(
"2013man"
,
5
),
rep
(
"2016"
,
5
)),
.f
=
~
get_ocsge_dep_com
(
dep
=
.x
,
mil
=
.y
)
)
%>%
.f
=
~
get_ocsge_dep_com_anc_gen
(
dep
=
.x
,
mil
=
.y
)
)
%>%
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
# calcul d'ocsge nouvelle génération ----------
ocsge_pdl_2022
<-
purrr
::
map2_dfr
(
.x
=
rep
(
c
(
"44"
,
"49"
,
"53"
,
"72"
,
"85"
),
1
),
.y
=
c
(
rep
(
"2022"
,
5
)),
.f
=
~
get_ocsge_dep_com_nouv_gen
(
dep
=
.x
,
mil
=
.y
)
)
%>%
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
ocsge_pdl_2020
<-
purrr
::
map2_dfr
(
.x
=
rep
(
c
(
"44"
,
"49"
),
1
),
.y
=
c
(
rep
(
"2020"
,
2
)),
.f
=
~
get_ocsge_dep_com_nouv_gen
(
dep
=
.x
,
mil
=
.y
)
)
%>%
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
ocsge_pdl_2019
<-
purrr
::
map2_dfr
(
.x
=
rep
(
c
(
"53"
,
"72"
,
"85"
),
1
),
.y
=
c
(
rep
(
"2019"
,
3
)),
.f
=
~
get_ocsge_dep_com_nouv_gen
(
dep
=
.x
,
mil
=
.y
))
%>%
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
ocsge_pdl_nouv_gen
<-
dplyr
::
bind_rows
(
ocsge_pdl_2022
,
ocsge_pdl_2020
,
ocsge_pdl_2019
)
%>%
tidyr
::
complete
()
%>%
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
# en cas de connexion par VPN, mieux vaut procéder par étape pour éviter de tout perdre en cas de déconnexion
# en cas de connexion par VPN, mieux vaut procéder par étape pour éviter de tout perdre en cas de déconnexion
# ocsge_44 <- get_ocsge_dep_com(dep = "44", mil = "2016")
ocsge_44_2022
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"44"
,
mil
=
"2022"
)
# ocsge_49 <- get_ocsge_dep_com(dep = "49", mil = "2016")
ocsge_44_2020
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"44"
,
mil
=
"2020"
)
# ocsge_53 <- get_ocsge_dep_com(dep = "53", mil = "2016")
ocsge_49_2022
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"49"
,
mil
=
"2022"
)
# ocsge_72 <- get_ocsge_dep_com(dep = "72", mil = "2016")
ocsge_49_2020
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"49"
,
mil
=
"2020"
)
# ocsge_85 <- get_ocsge_dep_com(dep = "85", mil = "2016")
ocsge_53_2022
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"53"
,
mil
=
"2022"
)
# ocsge_44_2013 <- get_ocsge_dep_com(dep = "44", mil = "2013man")
ocsge_53_2019
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"53"
,
mil
=
"2019"
)
# ocsge_49_2013 <- get_ocsge_dep_com(dep = "49", mil = "2013man")
ocsge_72_2022
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"72"
,
mil
=
"2022"
)
# ocsge_53_2013 <- get_ocsge_dep_com(dep = "53", mil = "2013man")
ocsge_72_2019
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"72"
,
mil
=
"2019"
)
# ocsge_72_2013 <- get_ocsge_dep_com(dep = "72", mil = "2013man")
ocsge_85_2022
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"85"
,
mil
=
"2022"
)
# ocsge_85_2013 <- get_ocsge_dep_com(dep = "85", mil = "2013man")
ocsge_85_2019
<-
get_ocsge_dep_com_nouv_gen
(
dep
=
"85"
,
mil
=
"2019"
)
#
# ocsge_pdl <- dplyr::bind_rows(
ocsge_pdl_nouv_gen
<-
dplyr
::
bind_rows
(
# ocsge_44, ocsge_49, ocsge_53, ocsge_72, ocsge_85,
ocsge_44_2022
,
ocsge_49_2022
,
ocsge_53_2022
,
ocsge_72_2022
,
ocsge_85_2022
,
# ocsge_44_2013, ocsge_49_2013, ocsge_53_2013, ocsge_72_2013, ocsge_85_2013
ocsge_44_2020
,
ocsge_49_2020
,
# ) %>%
ocsge_53_2019
,
ocsge_72_2019
,
ocsge_85_2019
# dplyr::mutate(date = lubridate::make_date(millesime + 1, 01, 01))
)
%>%
dplyr
::
mutate
(
date
=
lubridate
::
make_date
(
millesime
,
06
,
30
))
# sauveagarde provisoire ----------
save.image
(
file
=
"sauvegarde_provisoire.RData"
)
# déconnexion au SGBDR ----------
DBI
::
dbDisconnect
(
con_referentiels
)
DBI
::
dbDisconnect
(
con_referentiels
)
# versement de ocsge_pdl dans le sgbd/datamart.portrait_territoires -------------
# versement de ocsge_pdl dans le sgbd/datamart.portrait_territoires -------------
ocsge_pdl_2013
<-
dplyr
::
filter
(
ocsge_pdl
,
millesime
==
2013
)
ocsge_pdl_2016
<-
dplyr
::
filter
(
ocsge_pdl
,
millesime
==
2016
)
## ocsge ancienne génération ------------
ocsge_pdl_2013
<-
dplyr
::
filter
(
ocsge_pdl_anc_gen
,
millesime
==
2013
)
datalibaba
::
poster_data
(
datalibaba
::
poster_data
(
data
=
ocsge_pdl_2013
,
data
=
ocsge_pdl_2013
,
db
=
"datamart"
,
db
=
"datamart"
,
schema
=
"portrait_territoires"
,
schema
=
"portrait_territoires"
,
table
=
"ocsge_pdl_couverture_usage_2013"
,
table
=
"ocsge_pdl_couverture_usage_2013"
,
post_row_name
=
FALSE
,
post_row_name
=
FALSE
,
overwrite
=
TRUE
,
overwrite
=
TRUE
,
droits_schema
=
TRUE
,
droits_schema
=
TRUE
,
user
=
"does"
user
=
"does"
)
)
ocsge_pdl_2016
<-
dplyr
::
filter
(
ocsge_pdl_anc_gen
,
millesime
==
2016
)
datalibaba
::
poster_data
(
datalibaba
::
poster_data
(
data
=
ocsge_pdl_2016
,
data
=
ocsge_pdl_2016
,
db
=
"datamart"
,
db
=
"datamart"
,
schema
=
"portrait_territoires"
,
schema
=
"portrait_territoires"
,
table
=
"ocsge_pdl_couverture_usage_2016"
,
table
=
"ocsge_pdl_couverture_usage_2016"
,
post_row_name
=
FALSE
,
post_row_name
=
FALSE
,
overwrite
=
TRUE
,
overwrite
=
TRUE
,
droits_schema
=
TRUE
,
droits_schema
=
TRUE
,
user
=
"does"
user
=
"does"
)
)
## ocsge nouvelle génération ------------
ocsge_pdl_2022
<-
dplyr
::
filter
(
ocsge_pdl_nouv_gen
,
millesime
==
2022
)
datalibaba
::
poster_data
(
data
=
ocsge_pdl_2022
,
db
=
"datamart"
,
schema
=
"portrait_territoires"
,
table
=
"ocsge_pdl_couverture_usage_2022"
,
post_row_name
=
FALSE
,
overwrite
=
TRUE
,
droits_schema
=
TRUE
,
user
=
"does"
)
ocsge_pdl_2020
<-
dplyr
::
filter
(
ocsge_pdl_nouv_gen
,
millesime
==
2020
)
datalibaba
::
poster_data
(
data
=
ocsge_pdl_2020
,
db
=
"datamart"
,
schema
=
"portrait_territoires"
,
table
=
"ocsge_pdl_couverture_usage_2020"
,
post_row_name
=
FALSE
,
overwrite
=
TRUE
,
droits_schema
=
TRUE
,
user
=
"does"
)
ocsge_pdl_2019
<-
dplyr
::
filter
(
ocsge_pdl_nouv_gen
,
millesime
==
2019
)
datalibaba
::
poster_data
(
data
=
ocsge_pdl_2019
,
db
=
"datamart"
,
schema
=
"portrait_territoires"
,
table
=
"ocsge_pdl_couverture_usage_2019"
,
post_row_name
=
FALSE
,
overwrite
=
TRUE
,
droits_schema
=
TRUE
,
user
=
"does"
)
# typologie des espaces -------
# typologie des espaces -------
ocsge_type
<-
dplyr
::
select
(
ocsge_pdl
,
couverture
,
usage
)
%>%
## ancienne nomenclature -------------
# ocsge_type <- dplyr::select(ocsge_pdl, couverture, usage) %>%
# dplyr::distinct() %>%
# dplyr::mutate(
# type_espace = dplyr::case_when(
# couverture %in% c("CS1.1.1.1", "CS1.1.1.2", "CS1.1.2.1", "CS1.1.2.2") ~ "espace_artificialise",
# couverture == "CS1.2.1" &
# usage %in% c("US1.1", "US1.3", "US1.4", "US235", "US4.1.1", "US4.1.2", "US4.1.3", "US4.1.4", "US4.2", "US4.3", "US6.1", "US6.2") ~ "espace_artificialise",
# couverture == "CS1.2.1" &
# usage %in% c("US1.2", "US1.5", "US6.3", "US6.4") ~ "autre_surface_naturelle",
# couverture == "CS1.2.2" ~ "surface_en_eau",
# couverture %in% c("CS2.1.1.1", "CS2.1.1.2", "CS2.1.1.3", "CS2.1.2", "CS2.1.3", "CS2.2.1", "CS2.2.2") & usage == "US1.1" ~ "espace_agricole",
# couverture %in% c("CS2.1.1.1", "CS2.1.1.2", "CS2.1.1.3","CS2.1.1", "CS2.1.2", "CS2.1.3") & usage %in% c("US1.3", "US235") ~ "espace_artificialise",
# couverture %in% c("CS2.1.1.1", "CS2.1.1.2", "CS2.1.1.3", "CS2.1.2", "CS2.1.3") &
# usage %in% c("US1.2", "US1.4", "US1.5", "US4.1.1", "US4.1.2", "US4.1.3", "US4.1.4", "US4.1.5", "US4.2", "US4.3", "US6.1", "US6.2", "US6.3", "US6.4") ~ "surface_naturelle_boisee",
# couverture == "CS2.2.1" &
# usage %in% c("US1.3", "US1.4", "US1.5", "US235", "US4.1.1", "US4.1.2", "US4.1.3", "US4.1.4", "US4.1.5", "US4.2", "US4.3", "US6.1", "US6.2") ~ "espace_artificialise",
# couverture == "CS2.2.1" &
# usage %in% c("US1.2", "US6.3", "US6.4") ~ "autre_surface_naturelle",
# couverture == "CS2.2.2" &
# usage != "US1.1" ~ "a_definir",
# TRUE ~ "a_revoir"
# )
# )
## nouvelle nomenclature ---------------
# passage entre les catégories d'usage et de couverture du sol
# vers Artif / Non Artif
# elle a été établie à la demande de la DGALN par l'IGN
# lien vers la nouvelle nomenclature :
# https://artificialisation.developpement-durable.gouv.fr/sites/artificialisation/files/fichiers/2022/05/2022_05_03_Tableau-OCSGE-CouvUsage-ARTIFICIALISATION%5B1%5D.pdf
## ocsge ancienne génération ----------
ocsge_pdl_anc_gen
<-
ocsge_pdl_anc_gen
%>%
dplyr
::
rename
(
code_cs
=
couverture
,
code_us
=
usage
)
%>%
dplyr
::
mutate
(
millesime
=
as.character
(
millesime
))
# unique(ocsge_pdl_anc_gen$code_us)
# [1] "US1.1" "US235" "US6.1" "US6.2" "US4.1.1" "US4.3" "US4.1.2" "US6.3" "US1.2" "US4.1.3" "US4.1.4" "US1.3" "US1.4"
# [14] "US4.2"
# unique(ocsge_pdl_anc_gen$code_cs)
# [1] "CS1.1.1.1" "CS1.1.1.2" "CS1.1.2.1" "CS1.2.1" "CS1.2.2" "CS2.1.1.1" "CS2.1.1.2" "CS2.1.1.3" "CS2.1.2" "CS2.2.1" "CS2.1.3"
# [12] "CS2.1.1" "CS1.1.2.2" "CS2.2.2"
ocsge_type_anc_gen
<-
dplyr
::
select
(
ocsge_pdl_anc_gen
,
code_cs
,
code_us
)
%>%
dplyr
::
distinct
()
%>%
dplyr
::
distinct
()
%>%
dplyr
::
mutate
(
dplyr
::
mutate
(
type_espace
=
dplyr
::
case_when
(
type_espace
=
dplyr
::
case_when
(
co
uverture
%in%
c
(
"CS1.1.1.1"
,
"CS1.1.1.2"
,
"CS1.1.2.1"
,
"CS1.1.2.2"
)
~
"espace_artificialise"
,
co
de_cs
%in%
c
(
"CS1.1.1.1"
,
"CS1.1.1.2"
,
"CS1.1.2.2"
)
~
"espace_artificialise"
,
co
uverture
==
"CS1.2.1"
&
co
de_cs
==
"CS1.
1.
2.1"
&
code_us
==
"US1.3"
~
"espace_non_artificialise"
,
usage
%in%
c
(
"US1.1"
,
"US1.3"
,
"US1.4"
,
"US235"
,
"US4.1.1"
,
"US4.1.2"
,
"US4.1.3"
,
"US4.1.4"
,
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
)
~
"espace_artificialise"
,
code_cs
==
"CS1.1.2.1"
&
couverture
==
"CS1.2.1"
&
code_us
%in%
c
(
"US1.1"
,
"US1.2"
,
"US1.4"
,
"US1.5"
,
"US235"
,
"US2"
,
"US3"
,
"US5"
,
usage
%in%
c
(
"US1.
2
"
,
"US1.
5
"
,
"US
6
.3"
,
"US
6.4"
)
~
"autre_surface_naturelle
"
,
"US
4.
1.
1
"
,
"US
4.
1.
2
"
,
"US
4.1
.3"
,
"US
4.1.4"
,
"US4.1.5
"
,
couverture
==
"CS1.2.2"
~
"surface_en_eau
"
,
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
,
"US6.3"
,
"US6.6"
)
~
"espace_artificialise
"
,
co
uverture
%in%
c
(
"CS
2.1.1.1"
,
"CS2.1.1.2"
,
"CS2.1.1.3"
,
"CS2.1.2"
,
"CS2.1.3"
,
"CS2.2.1"
,
"CS2.2.2"
)
&
usage
==
"US1.1"
~
"espace_agricole
"
,
co
de_cs
%in%
c
(
"CS
1.2.1"
,
"CS1.2.2"
,
"CS1.2.3
"
,
couverture
%in%
c
(
"CS2.1.1.1"
,
"CS2.1.1.2"
,
"CS2.1.1.3"
,
"CS2.1.1"
,
"CS2.1.2"
,
"CS2.1.3"
)
&
usage
%in%
c
(
"US1.3"
,
"US235"
)
~
"espace_artificialise"
,
"CS2.1.1.1"
,
"CS2.1.1.2"
,
"CS2.1.1.3"
,
couverture
%in%
c
(
"CS2.1.1.1"
,
"CS2.1.1.2"
,
"CS2.1.1.3"
,
"CS2.1.2"
,
"CS2.1.3"
)
&
"CS2.1.2"
,
"CS2.1.3"
)
~
"espace_non_artificialise"
,
usage
%in%
c
(
"
US1.2"
,
"US1.4"
,
"US1.5"
,
"US4.1.1"
,
"US4.1.2"
,
"US4.1.3"
,
"US4.1.4"
,
"US4.1.5"
,
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
,
"US6.3"
,
"US6.4"
)
~
"surface_naturelle_boisee"
,
code_cs
%in%
c
(
"
CS2.2.1"
,
"CS2.2.2"
)
&
couverture
==
"CS2.2.1"
&
code_us
%in%
c
(
"US1.1"
,
"US1.2"
,
"US1.3"
,
"US1.4"
,
"US6.3"
,
"US6.6"
)
~
"espace_non_artificialise"
,
usage
%in%
c
(
"
US1.3"
,
"US1.4"
,
"US1.5"
,
"US235"
,
"US4.1.1"
,
"US4.1.2"
,
"US4.1.3"
,
"US4.1.4"
,
"US4.1.5"
,
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
)
~
"espace_artificialise"
,
code_cs
%in%
c
(
"
CS2.2.1"
,
"CS2.2.2"
)
&
couverture
==
"CS2.2.1"
&
code_us
%in%
c
(
"US235"
,
"US2"
,
"US3"
,
"US5"
,
"US4.1.1"
,
"US4.1.2"
,
usage
%in%
c
(
"US1.
2
"
,
"US
6.3
"
,
"US
6.4"
)
~
"autre_surface_naturelle
"
,
"US
4.
1.
3
"
,
"US
4.1.4
"
,
"US
4.1.5
"
,
couverture
==
"CS2.2.2"
&
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
)
~
"espace_artificialise"
,
usage
!
=
"US
1.1
"
~
"
a_definir"
,
code_cs
==
"CS2.1.1"
&
code_us
=
=
"US
235
"
~
"
espace_non_artificialise"
,
# ajouté pour le cas de "44014" en 2013
TRUE
~
"a_revoir"
TRUE
~
"a_revoir"
)
)
)
)
# chargement de la liste des depcom COGiter région PDL et région PDL + epci -------
## ocsge nouvelle génération ------------
source
(
"R/levels_facteurs_com.R"
)
# unique(ocsge_pdl_nouv_gen$code_us)
# [1] "US1.1" "US2" "US3" "US4.3" "US5" "US6.1" "US6.2" "US4.1.1" "US4.1.2" "US6.3" "US1.2" "US235" "US1.4"
# [14] "US4.2" "US4.1.3" "US4.1.4" "US1.3"
# unique(ocsge_pdl_nouv_gen$code_cs)
# [1] "CS1.1.1.1" "CS1.1.1.2" "CS1.1.2.1" "CS1.2.1" "CS1.2.2" "CS2.1.1.1" "CS2.1.1.2" "CS2.1.1.3" "CS2.1.2" "CS2.2.1" "CS2.1.3"
# [12] "CS1.1.2.2"
ocsge_type_nouv_gen
<-
dplyr
::
select
(
ocsge_pdl_nouv_gen
,
code_cs
,
code_us
)
%>%
dplyr
::
distinct
()
%>%
dplyr
::
mutate
(
type_espace
=
dplyr
::
case_when
(
code_cs
%in%
c
(
"CS1.1.1.1"
,
"CS1.1.1.2"
,
"CS1.1.2.2"
)
~
"espace_artificialise"
,
code_cs
==
"CS1.1.2.1"
&
code_us
==
"US1.3"
~
"espace_non_artificialise"
,
code_cs
==
"CS1.1.2.1"
&
code_us
%in%
c
(
"US1.1"
,
"US1.2"
,
"US1.4"
,
"US1.5"
,
"US235"
,
"US2"
,
"US3"
,
"US5"
,
"US4.1.1"
,
"US4.1.2"
,
"US4.1.3"
,
"US4.1.4"
,
"US4.1.5"
,
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
,
"US6.3"
,
"US6.6"
)
~
"espace_artificialise"
,
code_cs
%in%
c
(
"CS1.2.1"
,
"CS1.2.2"
,
"CS1.2.3"
,
"CS2.1.1.1"
,
"CS2.1.1.2"
,
"CS2.1.1.3"
,
"CS2.1.2"
,
"CS2.1.3"
)
~
"espace_non_artificialise"
,
code_cs
%in%
c
(
"CS2.2.1"
,
"CS2.2.2"
)
&
code_us
%in%
c
(
"US1.1"
,
"US1.2"
,
"US1.3"
,
"US1.4"
,
"US6.3"
,
"US6.6"
)
~
"espace_non_artificialise"
,
code_cs
%in%
c
(
"CS2.2.1"
,
"CS2.2.2"
)
&
code_us
%in%
c
(
"US235"
,
"US2"
,
"US3"
,
"US5"
,
"US4.1.1"
,
"US4.1.2"
,
"US4.1.3"
,
"US4.1.4"
,
"US4.1.5"
,
"US4.2"
,
"US4.3"
,
"US6.1"
,
"US6.2"
)
~
"espace_artificialise"
,
TRUE
~
"a_revoir"
)
)
# calcul des indicateurs communaux -----------
# calcul des indicateurs communaux -----------
source_ocsge
<-
ocsge_pdl
%>%
dplyr
::
left_join
(
ocsge_type
)
%>%
# chargement de la liste des depcom COGiter région PDL et région PDL + epci
source
(
"R/levels_facteurs_com.R"
)
source_ocsge_anc_gen
<-
ocsge_pdl_anc_gen
%>%
dplyr
::
left_join
(
ocsge_type_anc_gen
)
%>%
dplyr
::
select
(
depcom
=
code_insee
,
date
,
variable
=
type_espace
,
valeur
=
surf_intersection_m2
)
%>%
dplyr
::
group_by
(
date
,
depcom
,
variable
)
%>%
dplyr
::
summarise
(
valeur
=
sum
(
valeur
),
.groups
=
"drop"
)
%>%
dplyr
::
mutate_if
(
is.character
,
as.factor
)
%>%
dplyr
::
mutate
(
depcom
=
forcats
::
fct_expand
(
depcom
,
com_reg
))
%>%
tidyr
::
complete
(
depcom
,
date
,
variable
,
fill
=
list
(
valeur
=
NA
),
explicit
=
FALSE
)
%>%
dplyr
::
mutate
(
depcom
=
forcats
::
fct_expand
(
depcom
,
com_reg_et_vois
))
%>%
tidyr
::
complete
(
depcom
,
date
,
variable
,
fill
=
list
(
valeur
=
NA
))
%>%
tidyr
::
pivot_wider
(
names_from
=
variable
,
values_from
=
valeur
)
source_ocsge_nouv_gen
<-
ocsge_pdl_nouv_gen
%>%
dplyr
::
left_join
(
ocsge_type_nouv_gen
)
%>%
dplyr
::
select
(
dplyr
::
select
(
depcom
=
code_insee
,
depcom
=
code_insee
,
date
,
date
,
...
@@ -132,10 +316,15 @@ source_ocsge <- ocsge_pdl %>%
...
@@ -132,10 +316,15 @@ source_ocsge <- ocsge_pdl %>%
dplyr
::
summarise
(
valeur
=
sum
(
valeur
),
.groups
=
"drop"
)
%>%
dplyr
::
summarise
(
valeur
=
sum
(
valeur
),
.groups
=
"drop"
)
%>%
dplyr
::
mutate_if
(
is.character
,
as.factor
)
%>%
dplyr
::
mutate_if
(
is.character
,
as.factor
)
%>%
dplyr
::
mutate
(
depcom
=
forcats
::
fct_expand
(
depcom
,
com_reg
))
%>%
dplyr
::
mutate
(
depcom
=
forcats
::
fct_expand
(
depcom
,
com_reg
))
%>%
tidyr
::
complete
(
depcom
,
date
,
variable
,
fill
=
list
(
valeur
=
0
),
explicit
=
FALSE
)
%>%
tidyr
::
complete
(
depcom
,
date
,
variable
,
fill
=
list
(
valeur
=
NA
),
explicit
=
FALSE
)
%>%
dplyr
::
mutate
(
depcom
=
forcats
::
fct_expand
(
depcom
,
com_reg_et_vois
))
%>%
dplyr
::
mutate
(
depcom
=
forcats
::
fct_expand
(
depcom
,
com_reg_et_vois
))
%>%
tidyr
::
complete
(
depcom
,
date
,
variable
,
fill
=
list
(
valeur
=
NA
))
%>%
tidyr
::
complete
(
depcom
,
date
,
variable
,
fill
=
list
(
valeur
=
NA
))
%>%
tidyr
::
pivot_wider
(
names_from
=
variable
,
values_from
=
valeur
)
tidyr
::
pivot_wider
(
names_from
=
variable
,
values_from
=
valeur
)
source_ocsge
<-
dplyr
::
bind_rows
(
source_ocsge_nouv_gen
,
source_ocsge_anc_gen
)
# versement de ocsge dans le sgbd/datamart.portrait_territoires et metadonnées -------------
# versement de ocsge dans le sgbd/datamart.portrait_territoires et metadonnées -------------
...
...
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