Metrópolis
2025-07-09
Información de zonas metropolitanas https://www.gob.mx/conapo/documentos/las-metropolis-de-mexico-2020
https://www.gob.mx/cms/uploads/attachment/file/865680/Cuadros_MM2020.xlsx
Se identificaron 92 metrópolis en el país de tres tipos: 48 zonas metropolitanas, 22 metrópolis municipales y 22 zonas conurbadas https://conapo.segob.gob.mx/work/models/CONAPO/Datos_Abiertos/DT/Metropolis.rar
Cuadros de la delimitación de las metrópolis de México 2020
Contexto geográfico
library(rnaturalearth)
target <- c("Mexico")
sf::sf_use_s2(FALSE)
countries<- ne_countries(scale = 10,returnclass = 'sf') %>%
filter(name %in% target)
countries<-st_transform(countries, CRS("+init=epsg:4326 +proj=longlat
+ +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0"))
polygon = st_cast(countries, "POLYGON", do_split = FALSE)
mex<-polygon$geometry
#plot(mex)
ruta<-"C:/Users/cguer/Documents/Claudia/Midropbox/Investigacion y escritos/karamanis/data/Metropolis/"
infile <- "Metropolis_2020.shp"
nomarchi<-as.filename(paste0(ruta,infile))
datageomet<- read_sf(nomarchi,options = "ENCODING=UTF8")
datageomet= st_transform(datageomet, crs = 4326)
ruta<-"C:/Users/cguer/Documents/Claudia/Midropbox/Investigacion y escritos/karamanis/portraits/torreon/"
infile <- "metropolis"
datacom <- read.csv(paste0(ruta,infile,'.csv'),encoding = "UTF-8")
datageomet2<-merge(datageomet,datacom, by.x = "CVE_MET", by.y = "Clave.de.metrópoli", all.x = TRUE)
ruta<-"C:/Users/cguer/Documents/Claudia/Midropbox/Investigacion y escritos/karamanis/portraits/torreon/"
infile <- "metropolisdatmun"
datacommun <- read.csv(paste0(ruta,infile,'.csv'),encoding = "UTF-8")
# Se convierte en un dato alfanumérico de dos digito como "01", "02",..."32"
codent<-substr(datacommun$Clave.de.la.entidad,1,2)
codent<-sprintf("%02d%s", as.numeric(gsub("[^0-9]+", "", codent)), gsub("[0-9]+", "", codent))
codmun<-substr(datacommun$Clave.de.municipio,1,3)
codmun<-sprintf("%03d%s", as.numeric(gsub("[^0-9]+", "", codmun)), gsub("[0-9]+", "", codmun))
cvegeo<-paste0(codent,codmun)
datacommun$CVEGEO<-cvegeo
#datageomet<-merge(datageomet,datacom, by.x = "CVE_MET", by.y = "Clave.de.metrópoli", all.x = TRUE)
datageomet<-merge(datageomet,datacommun, by.x = "CVEGEO", by.y = "CVEGEO", all.x = TRUE)
breaks2 <- classInt::classIntervals(
datageomet$Densidad.media.urbana,
n = 9,
style = "equal",
intervalClosure="right"
)$brks
g <- ggplot() +
geom_sf(data = mex, fill = NA) +
geom_sf(data = datageomet, aes(fill = TIPO_MET),alpha=.7) +
scale_fill_manual(values = c("#f94144",
"#277da1",
"#f9a64f",
"#90be6d",
"#277da1",
"#f9a64f",
"#277da1",
"#9000ab",
"#277da1",
"#277da1",
"#f9a64f",
"#90beee",
"#577590",
"#f1345b",
"#19456c",
"#10028a",
"#24528a"))+
labs(
title = "Metrópolis en México"
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 30)
)
g
metrop<-"Ocotlcn"
metrop<-"Irapuato"
metrop<-"Guadalajara"
metrop<-"Monterrey"
metrop<-"La Laguna"
datageomet<- datageomet|> filter(NOM_MET %in% c(metrop))
titulo<-paste0("Municipios de ",datageomet$NOM_MET)
g <- ggplot() +
geom_sf(data = datageomet, aes(fill = NOMGEO),alpha=.7) +
scale_fill_manual(values = c("#f94144",
"#277da1",
"#f9a64f",
"#90be6d",
"#277da1",
"#f9a64f",
"#277da1",
"#9000ab",
"#277da1",
"#277da1",
"#f9a64f",
"#90beee",
"#577590",
"#f1345b",
"#19456c",
"#10028a",
"#24528a"))+
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 30)
)
g
datageo_geom <- st_geometry(datageomet)
polygon = st_cast(datageo_geom, "POLYGON")
# plot(polygon)
b<- st_union(polygon)
#plot(b)
c<-st_polygon(b[[1]])
ext_ring <- st_polygon(b[[1]][1])
#plot(ext_ring)Recuperación de archivo de asentamientos en el INEGI Asentamientos humanos INEGI
Colonias https://www.inegi.org.mx/programas/dcah/
ruta<-"C:/Users/cguer/Documents/Claudia/Midropbox/Investigacion y escritos/karamanis/data/conjunto_de_datos/"
infile <- "00as.shp"
nomarchi<-as.filename(paste0(ruta,infile))
nomfil<-"00as"
#a<-"SELECT * FROM \"00as\" WHERE (CVE_ENT = '05' OR CVE_ENT = '10') AND (CVE_MUN='035' OR CVE_MUN ='007' OR CVE_MUN='012')"
#a<-"SELECT * FROM \"00as\" WHERE (CVE_ENT = '05' AND CVE_MUN = '035') OR (CVE_ENT='05' AND CVE_MUN ='017') OR (CVE_ENT='10' AND CVE_MUN ='007') OR (CVE_ENT='10' AND CVE_MUN='012')"
a<-"SELECT * FROM \"00as\" WHERE (CVE_ENT = '11' AND CVE_MUN = '015')"
`%notin%` <- Negate(`%in%`)
#datageot<- read_sf(nomarchi,options = "ENCODING=latin1",query=a)
datageot<- read_sf(nomarchi,options = "ENCODING=latin1")
datageot= st_transform(datageot, crs = 4326)
#unique(datageot$TIPO)
datageot<- datageot|> filter(TIPO %notin% c("NINGUNO","CIUDAD"))
compa<-unique(datageomet$TIPO_MET)
if (compa == "Metrópoli municipal") {
datageot<- datageot|> filter(CVE_ENT %in% c(datageomet$CVE_ENT)) |> filter(CVE_MUN %in% c(datageomet$CVE_MUN))
} else {
datageot<-datageot[ext_ring, ]
}
titulo<-paste0("Asentamientos humanos en ",datageomet$NOM_MET)
g <- ggplot() +
#geom_sf(data = tor, fill = NA) +
geom_sf(data = datageomet, aes(fill = NOMGEO),alpha=.7) +
scale_fill_manual(values = c("#f94144",
"#277da1",
"#f9a64f",
"#90be6d",
"#277da1",
"#f9a64f",
"#277da1",
"#9000ab",
"#277da1",
"#277da1",
"#f9a64f",
"#90beee",
"#577590",
"#f1345b",
"#19456c",
"#10028a",
"#24528a"))+
geom_sf(data = datageot, fill = "grey",alpha=.7) +
labs(
title = titulo) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
legend.position = "bottom",
legend.key.width = unit(3, "line"),
legend.key.height = unit(0.5, "line"),
plot.background = element_rect(fill = NA, color = NA),
plot.title = element_text(size = 20, hjust = 0.5, face = "bold"),
plot.subtitle = element_text(size = 16, hjust = 0.5),
plot.caption = element_text(size = 10, hjust = 0.5, margin = margin(20, 0, 0, 0))
)
g
lim<-st_bbox(datageomet)
#lim$ymax<-25.65
q <- opq(bbox = c(lim$xmin, lim$ymin, lim$xmax, lim$ymax))%>%
add_osm_feature(key = "highway") %>%
osmdata_sf()
qosm_sf <- q$osm_lines
st_crs(qosm_sf) <-4326
qosm_sf <- qosm_sf|> filter(highway %in% c("primary","secondary","tertiary"))
#plot(qosm_sf$geometry)
xlim <- c(lim$xmin,lim$xmax)
ylim <- c(lim$ymin,lim$ymax)
titulo<-paste0("Zona metropolitana de ",datageomet$NOM_MET)
g <- ggplot() +
geom_sf(data = datageomet, aes(fill = NOMGEO),alpha=.7) +
# geom_sf(data = recorteosmlayer4, fill = NA,alpha=0.1,linewidth=0.05,color="grey") +
#geom_sf(data = datageot, fill=NA,color="navy",linewidth = 0.5) +
geom_sf(data = qosm_sf, color="navy",fill = NA, linewidth = 0.1) +
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 15)
)+
coord_sf(xlim = xlim, ylim = ylim)
g
pal <- MetBrewer::met.brewer("Johnson")
datageomet$Pobla<-as.numeric(gsub(" ","",datageomet$Población.2020))
#datageomet<- datageomet|> filter(NOM_MET %in% c("Saltillo"))
minipob<-min(datageomet$Pobla)
maxpob<-max(datageomet$Pobla)
g <- ggplot() +
geom_sf(data = datageomet, aes(fill = Pobla,alpha=.7))+
scale_fill_gradientn(colors = pal, na.value = "white", breaks = seq(minipob, maxpob, 150000), limits = c(minipob, maxpob)) +
#geom_sf(data = qosm_sf, color="navy",fill = NA, linewidth = 0.1) +
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 15)
)+
coord_sf(xlim = xlim, ylim = ylim)
g
library(cptcity)
#http://soliton.vm.bytemark.co.uk/pub/cpt-city/notes/formats.html
#http://soliton.vm.bytemark.co.uk/pub/cpt-city/index.html
pals <- find_cpt("blues")
pals <- find_cpt("population")
pals <- find_cpt("cmocean")
#names(basemapa2)[17] ="POBTOTMENOR25000"
library(RColorBrewer)
g <- ggplot() +
geom_sf(data = datageomet, aes(fill = Pobla))+
#scale_fill_gradientn(colors = pal, na.value = "white", breaks = seq(minipob, maxpob, 150000), limits = c(minipob, maxpob)) +
scale_fill_gradientn(name="Población",colours=brewer.pal(6,"PuBu"))+
geom_sf(data = qosm_sf, color="navy",fill = NA, linewidth = 0.1) +
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 15)
)+
coord_sf(xlim = xlim, ylim = ylim)
g
Densidad media urbana
Consiste en la concentració y dispersión poblacional de una determinada área geográfica y se calcula como número de habitantes por unidad de superficie, (habitantes por hectárea), permite comparar la ocupación territorial entre las metrópolis y el cálculo sólo incorpora la porción del territorio clasificado cmo urbano o rural
Para su cálculo se utilizó como dato de superficie el de las áreas geoestadísticas básicas urbanas del Marco Geoestadísitico,
numunip<-nrow(datageomet)
if(numunip > 1) {
breaks2 <- classInt::classIntervals(
datageomet$Densidad.media.urbana,
n = numunip,
style = "quantile"
)$brks
} else {
breaks2 <-1
}
datacol <-datageomet %>%
mutate(centroids = st_centroid(st_geometry(.)))
nc3_coords <- as.data.frame(sf::st_coordinates(datacol$centroids))
nc3_coords$nombre <- datacol$NOMGEO
g <- ggplot() +
geom_sf(data = datageomet, aes(fill = Densidad.media.urbana))+
#scale_fill_gradientn(colors = pal, na.value = "white", breaks = seq(minipob, maxpob, 150000), limits = c(minipob, maxpob)) +
#scale_fill_gradientn(colours=brewer.pal(6,"PuBu"))+
scale_fill_gradientn(name="densidad media",colours = cpt(n = numunip, "cmocean_matter"),breaks = round(breaks2, 0))+
geom_sf(data = qosm_sf, color="navy",fill = NA, linewidth = 0.1) +
geom_text(data = nc3_coords, aes(X, Y-.07, label = nombre), colour = "black",size = 5,check_overlap = TRUE)+
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 15),
legend.position="bottom",
legend.key.width = unit(4, "cm"),
axis.line = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.minor = element_blank(),
plot.background = element_rect(fill = "transparent", color = "transparent"),
# panel.background = element_rect(fill = "transparent", color = "transparent"),
panel.background = element_blank(),
legend.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_blank(),
legend.direction="horizontal"
)+
coord_sf(xlim = xlim, ylim = ylim)
g
bottom =as.numeric(round(lim$ymin,digits=2))
top = as.numeric(round(lim$ymax,digits=2))
left = as.numeric(round(lim$xmin,digits=2))
right = as.numeric(round(lim$xmax,digits=2))
borders<-c(left,bottom,right,top)
#map<-get_stadiamap(borders, zoom = 12, maptype = "stamen_terrain_background")
map<-get_stadiamap(borders, zoom = 12, maptype = "stamen_terrain")
ggmap(map)+
geom_text(data = nc3_coords, aes(X, Y-.07, label = nombre), colour = "black",size = 5,check_overlap = TRUE)+
geom_sf(data = qosm_sf, color="navy",fill = NA, linewidth = 0.1,inherit.aes = FALSE)+
geom_sf(data = datageomet, inherit.aes = FALSE,fill="transparent",color="black",linewidth=1)+
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 15),
legend.position="bottom",
legend.key.width = unit(4, "cm"),
axis.line = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.minor = element_blank(),
plot.background = element_rect(fill = "transparent", color = "transparent"),
# panel.background = element_rect(fill = "transparent", color = "transparent"),
panel.background = element_blank(),
legend.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_blank(),
legend.direction="horizontal"
)
ggmap(map)+
geom_text(data = nc3_coords, aes(X, Y-.07, label = nombre), colour = "black",size = 5,check_overlap = TRUE)+
geom_sf(data = datageot, inherit.aes = FALSE,fill="grey",color="navyblue",linewidth=.2) +
geom_sf(data = datageomet, inherit.aes = FALSE,fill="transparent",color="black",linewidth=1)+
labs(
title = titulo
) +
theme_minimal(
base_family = "body_font",
base_line_size = unit(0.1, "mm")
) +
theme(
plot.title = element_text(size = 15),
legend.position="bottom",
legend.key.width = unit(4, "cm"),
axis.line = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.minor = element_blank(),
plot.background = element_rect(fill = "transparent", color = "transparent"),
# panel.background = element_rect(fill = "transparent", color = "transparent"),
panel.background = element_blank(),
legend.background = element_rect(fill = "transparent", color = "transparent"),
panel.border = element_blank(),
legend.direction="horizontal"
)