Built-up changes in lowland Ethiopia

Built-up changes in lowland Ethiopia

Build-up changes in % of woreda between 2000 and 2017.

df_urban$changes_2000_2017 <-  df$`changes_2000_2017 (ha)`
df_urban$urban_changes_percent <- df$`change_percent (%)`
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = df_urban$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  df_urban$REGIONNAME, df_urban$WOREDANAME, round(df_urban$urban_changes_percent, 2)
) %>% lapply(htmltools::HTML)


m <- leaflet(df_urban) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(df_urban$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = df_urban$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

Build-up changes between 2000 and 2017 in Ha

Built-up change in ha between 2000 and 2017

Built-up areas in 2017

bins <- c(0,5, 10, 30, 100, 300, 800, 1200, 1800)
pal <- colorBin("Oranges", domain = df_urban$urban_2017_area, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g ha",
                  df_urban$REGIONNAME, df_urban$WOREDANAME, df_urban$urban_2017_area
) %>% lapply(htmltools::HTML)

df_urban$urban_2017_area[is.nan(df_urban$urban_2017_area)] <- 0

m <- leaflet(df_urban) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(df_urban$urban_2017_area),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = df_urban$urban_2000_area, opacity = 0.7, title = "Build-up in 2017 (ha)", position = "bottomright") %>% addMiniMap()

Built-up areas in 2000

df_urban$urban_2000_area[is.nan(df_urban$urban_2000_area)] <- 0
bins <- c(0,5, 10, 30, 100, 300, 800, 1200, 1800)
pal <- colorBin("Oranges", domain = df_urban$urban_2000_area, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g ha",
                  df_urban$REGIONNAME, df_urban$WOREDANAME, df_urban$urban_2000_area
) %>% lapply(htmltools::HTML)

df_urban$urban_2017_area[is.nan(df_urban$urban_2000_area)] <- 0

m <- leaflet(df_urban) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(df_urban$urban_2000_area),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = df_urban$urban_2000_area, opacity = 0.7, title = "Build-up in 2000 (ha)", position = "bottomright") %>% addMiniMap()

Built-up changes in ha for 2000 and 2017

palette <- brewer.pal(n = 9, name = "PuBuGn")
p_urban <- spplot(df_urban, c('urban_2000_area', 'urban_2017_area'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Built-up changes in ha")

p_urban

#plot_ly(p_urban)

Percent of woreda area in urban for 2000 and 2017

# Plot


df_urban$perc_urban_2000 <- df_urban$urban_2000_area / df_urban$area_ha * 100
df_urban$perc_urban_2017 <- df_urban$urban_2017_area / df_urban$area_ha * 100

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(df_urban, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of woreda area in urban")

Regional built-up changes - Afar

df_urban$changes_2000_2017 <-  df$`changes_2000_2017 (ha)`
df_urban$urban_changes_percent <- df$`change_percent (%)`

afar <- df_urban[df_urban$REGIONNAME=="Afar",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = afar$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  afar$REGIONNAME, afar$WOREDANAME, round(afar$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(afar) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(afar$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = afar$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(afar, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Afar region in urban")

#write.csv(afar, "afar_built-up.csv")

Regional built-up changes - Amhara

amhara <- df_urban[df_urban$REGIONNAME=="Amhara",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = amhara$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  amhara$REGIONNAME, amhara$WOREDANAME, round(amhara$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(amhara) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(amhara$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = amhara$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(amhara, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Amhara region in urban")

write.csv(amhara, "amhara_built-up.csv")

Regional built-up changes - Beneshangul Gumu

Beneshangul <- df_urban[df_urban$REGIONNAME=="Beneshangul Gumu",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = Beneshangul$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  Beneshangul$REGIONNAME, Beneshangul$WOREDANAME, round(Beneshangul$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(Beneshangul) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(Beneshangul$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = Beneshangul$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(Beneshangul, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Beneshangul Gumu region in urban")

#write.csv(Beneshangul, "Beneshangul_built-up.csv")

Regional built-up changes - Dire Dawa

Dire_Dawa <- df_urban[df_urban$REGIONNAME=="Dire Dawa",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = Dire_Dawa$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  Dire_Dawa$REGIONNAME, Dire_Dawa$WOREDANAME, round(Dire_Dawa$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(Dire_Dawa) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(Dire_Dawa$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = Dire_Dawa$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(Dire_Dawa, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Dire Dawa region in urban")

#write.csv(Dire_Dawa, "Dire_Dawa_built-up.csv")

Regional built-up changes - Gambela

Gambela <- df_urban[df_urban$REGIONNAME=="Gambela",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = Gambela$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  Gambela$REGIONNAME, Gambela$WOREDANAME, round(Gambela$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(Gambela) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(Gambela$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = Gambela$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(Gambela, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Gambela region in urban")

#write.csv(Gambela, "Gambela_built-up.csv")

Regional built-up changes - Oromia

Oromia <- df_urban[df_urban$REGIONNAME=="Oromia",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = Oromia$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  Oromia$REGIONNAME, Oromia$WOREDANAME, round(Oromia$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(Oromia) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(Oromia$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = Oromia$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(Oromia, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Oromia region in urban")

write.csv(Oromia, "Oromia_built-up.csv")

Regional built-up changes - SNNPR

SNNPR <- df_urban[df_urban$REGIONNAME=="SNNPR",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = SNNPR$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  SNNPR$REGIONNAME, SNNPR$WOREDANAME, round(SNNPR$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(SNNPR) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(SNNPR$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = SNNPR$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(SNNPR, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of SNNPR region in urban")

write.csv(SNNPR, "SNNPR_built-up.csv")

Regional built-up changes - Somali

Somali <- df_urban[df_urban$REGIONNAME=="Somali",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = Somali$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  Somali$REGIONNAME, Somali$WOREDANAME, round(Somali$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(Somali) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(Somali$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = Somali$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(Somali, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Somali region in urban")

write.csv(Somali, "Somali_built-up.csv")

Regional built-up changes - Tigray

Tigray <- df_urban[df_urban$REGIONNAME=="Tigray",]
bins <- c(0, 0.005, 0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 1.7)
pal <- colorBin("PuOr", domain = Tigray$urban_changes_percent, bins = bins)
labels <- sprintf("%s , <strong>%s</strong><br/>%g percent of woreda",
                  Tigray$REGIONNAME, Tigray$WOREDANAME, round(Tigray$urban_changes_percent, 3)
) %>% lapply(htmltools::HTML)


m <- leaflet(Tigray) %>%
 addProviderTiles(providers$CartoDB.Positron) %>%
  setView(lng=39.296289, lat =9.150055, zoom = 6)
m %>%
  addPolygons(fillColor = ~pal(Tigray$urban_changes_percent),
              weight = 1,
              opacity = 1,
              color = "white",
              dashArray = "3",
              fillOpacity = 0.7,
              highlight = highlightOptions(
                weight = 5,
                color = "#666",
                dashArray = "",
                fillOpacity = 0.7,
                bringToFront = TRUE),
              label = labels,
              labelOptions = labelOptions(
                style = list("font-weight" = "normal", padding = "3px 8px"),
                textsize = "15px",
                direction = "auto")) %>%
  addLegend(pal = pal, values = Tigray$urban_changes_percent, opacity = 0.7, title = "Build-up changes in % of woreda between 2000 and 2017", position = "bottomright") %>% addMiniMap()

# Plot

palette <- brewer.pal(n = 9, name = "YlOrRd")
spplot(Tigray, c('perc_urban_2000', 'perc_urban_2017'), names.attr = c("2000", "2017"),
       col.regions = palette, cuts = length(palette) - 1, as.table=TRUE,
       main = "Percent of Tigray region in urban")

#write.csv(Tigray, "Tigray_built-up.csv")