A análise buscou construir novas centralidades econômicas para as Regiões Metropolitanas do Brasil a partir da geolocalização dos estabelecimentos da RAIS.
Um mapa de calor da densidade foi usado para comparar os dados para os anos de 2002 e 2013 e avaliar a mobilidade dos centros.
google_centro <- dget("../google_centro.R")
google_centro %>%
filter(cidade == 'Belem') -> latlon_rm
my_rast = raster::raster("../rasters/belem3.tif", native = T)
map.centro <- get_map(location = c(lon = latlon_rm$lon,
lat = latlon_rm$lat),
source = "osm", color = "bw", maptype = 'roadmap',
messaging = F, zoom = 12)
## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=-1.455755,-48.49018&zoom=12&size=640x640&maptype=terrain&sensor=false
rast_df = raster::rasterToPoints(my_rast); rast_df = data.frame(rast_df)
names(rast_df) = c('x','y','z')
rast_df %>%
filter(z != 0) -> rast_df
centro.acp = centro12[centro12@data$acp == 'Belem', ]
centro.acp = spTransform(centro.acp, CRS(my_crs))
centro.acp = fortify(centro.acp, region = 'acp')
ggmap(map.centro) +
geom_tile(aes(x = x, y = y, fill = factor(z)), alpha = 0.6,
data = rast_df) +
scale_fill_manual(values = c('#8A3DE8', '#07FF8B', '#AA540E')) +
geom_polygon(data= centro.acp, aes(x=long, y=lat, group=group),
fill=NA, colour="yellow", size = 1 , alpha=1) +
theme_map() +
theme(legend.position="none") +
coord_equal()
raster::values(my_rast) <- ifelse(raster::values(my_rast) == 0,
NA,raster::values(my_rast))
centro.acp = centro12[centro12@data$acp == 'Belem', ]
centro.acp = spTransform(centro.acp, CRS(my_crs))
leaflet() %>%
addTiles() %>%
setView(lat = latlon_rm$lat, lng = latlon_rm$lon, zoom = 11) %>%
addRasterImage(my_rast, colors = c('#8A3DE8', '#07FF8B', '#AA540E'),
opacity = 0.7) %>%
addLegend(colors = c('#8A3DE8', '#07FF8B', '#AA540E'),
values = raster::values(my_rast),
labels = c('Antiga Centralidade',
'Nova Centralidade', 'Centralidade'),
title = "Centralidades entre 2002 e 2013") %>%
addPolygons(data=centro.acp, weight = 2,
fillColor = "yellow",
popup = paste0("<b><center> Centro </b>",
"<br> RM de Belem </center>"))
google_centro <- dget("../google_centro.R")
google_centro %>%
filter(cidade == 'Fortaleza') -> latlon_rm
my_rast = raster::raster("../rasters/fortaleza3.tif", native = T)
map.centro <- get_map(location = c(lon = latlon_rm$lon,
lat = latlon_rm$lat),
source = "osm", color = "bw", maptype = 'roadmap',
messaging = F, zoom = 12)
## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=-3.731862,-38.52667&zoom=12&size=640x640&maptype=terrain&sensor=false
rast_df = raster::rasterToPoints(my_rast); rast_df = data.frame(rast_df)
names(rast_df) = c('x','y','z')
rast_df %>%
filter(z != 0) -> rast_df
centro.acp = centro12[centro12@data$acp == 'Fortaleza', ]
centro.acp = spTransform(centro.acp, CRS(my_crs))
centro.acp = fortify(centro.acp, region = 'acp')
ggmap(map.centro) +
geom_tile(aes(x = x, y = y, fill = factor(z)), alpha = 0.6,
data = rast_df) +
scale_fill_manual(values = c('#8A3DE8', '#07FF8B', '#AA540E')) +
geom_polygon(data= centro.acp, aes(x=long, y=lat, group=group),
fill=NA, colour="yellow", size = 1 , alpha=1) +
theme_map() +
theme(legend.position="none") +
coord_equal()
raster::values(my_rast) <- ifelse(raster::values(my_rast) == 0,
NA,raster::values(my_rast))
centro.acp = centro12[centro12@data$acp == 'Fortaleza', ]
centro.acp = spTransform(centro.acp, CRS(my_crs))
leaflet() %>%
addTiles() %>%
setView(lat = latlon_rm$lat, lng = latlon_rm$lon, zoom = 11) %>%
addRasterImage(my_rast, colors = c('#8A3DE8', '#07FF8B', '#AA540E'),
opacity = 0.7) %>%
addLegend(colors = c('#8A3DE8', '#07FF8B', '#AA540E'),
values = raster::values(my_rast),
labels = c('Antiga Centralidade',
'Nova Centralidade', 'Centralidade'),
title = "Centralidades entre 2002 e 2013") %>%
addPolygons(data=centro.acp, weight = 2,
fillColor = "yellow",
popup = paste0("<b><center> Centro </b>",
"<br> RM de Fortaleza </center>"))