R - Cultivated crop maps in Rio Grande do Sul, Brazil

Welcome. In this post, I am going to show you how you may create maps of cultivated crops in Rio Grande do Sul state, Brazil.

Last updated on Sep 22, 2021 3 min read R

Generate crop cultivated maps

Crop plantation area from IBGE

Loading the packages

library(readxl)
library(tidyverse)
library(geobr)
library(patchwork)

Load the data and data wrangling

The data downloaded from IBGE there are metadata in the 4 first lines that are not intrest for us skip = 4.
Also, there are info in the last rows, for that we select the 497 municipalities data[1:497,].
Furthermore, the rows (cities) without crop planted, IBGE used “-” or “…” instead input 0, then we have used case_when function.
data <- read_csv('https://raw.githubusercontent.com/luanpott10/Class/main/tabela1612_1.csv', skip = 4)
data <- data[1:497,]

colnames(data) <- c("code","city","rice","corn","soybean")

data <- data |> 
  mutate(rice_crop = case_when(rice == "..." | rice == "-" ~ 0,
                                TRUE ~ as.double(rice))) |> 
  mutate(corn_crop = case_when(corn == "..." | corn == "-" ~ 0,
                                TRUE ~ as.double(corn))) |> 
  mutate(soybean_crop = case_when(soybean == "..." | soybean == "-" ~ 0,
                                TRUE ~ as.double(soybean)))
  
data <- data |> select(code,city,rice_crop,corn_crop,soybean_crop)

Dataset of geobr package from municipalities of Rio Grande do Sul state

cities_RS <- read_municipality(code_muni = "RS", year= 2020)

Ggplot of the cities

ggplot()+
  geom_sf(data=cities_RS)

Joining the IBGE data and the sf object

cities_RS$code_muni <- as.character(cities_RS$code_muni)
data_x <- left_join(cities_RS,data,by= c("code_muni"="code"))

Palettes

pal_soybean <- c('#252525','#ccece6','#99d8c9','#66c2a4','#41ae76','#238b45','#006d2c','#00441b')
pal_corn <- c('#252525','#f7ffa8','#EFFD5F','#FCE205','#FCD12A','#FFC30B','#F9A602','#c48302')
pal_rice <- c('#252525','#caebfc','#9ecae1','#6baed6','#4292c6','#2171b5','#084594','#082954')

Soybean map

(soybean_map <-
  ggplot()+
    geom_sf(data=data_x,aes(fill=soybean_crop))+
    theme_minimal()+
    scale_fill_gradientn(colours=pal_soybean,
                       limits = c(0,150000),
                       na.value='#252525')+
    labs(x= "Longitude", y = "Latitude", title = "Soybean")+
    guides(fill=guide_colorbar(title="Crop area (ha)",barwidth = 1,barheight = 4,
                             frame.colour = "black"))+
    theme(legend.position = c(0.17, 0.2),
        panel.border = element_rect(color="Black", fill = NA),
        panel.background = element_rect(fill = "#f2f2f2"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.title.x = element_text(family = "serif",
                                    colour = "#000000",size = 22.0),
        axis.text.x = element_text(family = "serif",
                                   colour = "#000000",size = 18.0),
        axis.title.y = element_text(family = "serif",
                                    colour = "#000000",size = 22.0),
        axis.text.y = element_text(family = "serif",
                                   colour = "#000000",size = 18.0),
        legend.title = element_text(family = "serif",
                                    colour = '#000000',size = 12.0),
        legend.text = element_text(family = "serif",
                                   colour = '#000000',size = 12.0),
        legend.background = element_rect(fill="#f2f2f2",
                                  linetype="dashed", 
                                  colour ="#f2f2f2")))

Corn map

(corn_map <-
  ggplot()+
    geom_sf(data=data_x,aes(fill=corn_crop))+
    theme_minimal()+
    scale_fill_gradientn(colours=pal_corn,
                       limits = c(0,15000),
                       na.value='#252525')+
    labs(x= "Longitude", y = "Latitude", title = "Corn")+
    guides(fill=guide_colorbar(title="Crop area (ha)",barwidth = 1,barheight = 4,
                             frame.colour = "black"))+
    theme(legend.position = c(0.17, 0.2),
        panel.border = element_rect(color="Black", fill = NA),
        panel.background = element_rect(fill = "#f2f2f2"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.title.x = element_text(family = "serif",
                                    colour = "#000000",size = 22.0),
        axis.text.x = element_text(family = "serif",
                                   colour = "#000000",size = 18.0),
        axis.title.y = element_text(family = "serif",
                                    colour = "#000000",size = 22.0),
        axis.text.y = element_text(family = "serif",
                                   colour = "#000000",size = 18.0),
        legend.title = element_text(family = "serif",
                                    colour = '#000000',size = 12.0),
        legend.text = element_text(family = "serif",
                                   colour = '#000000',size = 12.0),
        legend.background = element_rect(fill="#f2f2f2",
                                  linetype="dashed", 
                                  colour ="#f2f2f2")))

Rice map

(rice_map <-
  ggplot()+
    geom_sf(data=data_x,aes(fill=rice_crop))+
    theme_minimal()+
    scale_fill_gradientn(colours=pal_rice,
                       limits = c(0,75000),
                       na.value='#252525')+
    labs(x= "Longitude", y = "Latitude", title = "Rice")+
    guides(fill=guide_colorbar(title="Crop area (ha)",barwidth = 1,barheight = 4,
                             frame.colour = "black"))+
    theme(legend.position = c(0.17, 0.2),
        panel.border = element_rect(color="Black", fill = NA),
        panel.background = element_rect(fill = "#f2f2f2"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.title.x = element_text(family = "serif",
                                    colour = "#000000",size = 22.0),
        axis.text.x = element_text(family = "serif",
                                   colour = "#000000",size = 18.0),
        axis.title.y = element_text(family = "serif",
                                    colour = "#000000",size = 22.0),
        axis.text.y = element_text(family = "serif",
                                   colour = "#000000",size = 18.0),
        legend.title = element_text(family = "serif",
                                    colour = '#000000',size = 12.0),
        legend.text = element_text(family = "serif",
                                   colour = '#000000',size = 12.0),
        legend.background = element_rect(fill="#f2f2f2",
                                  linetype="dashed", 
                                  colour ="#f2f2f2")))

Crop maps

soybean_map + corn_map + rice_map

R Markdown tidyverse maps
Luan Pierre Pott
Luan Pierre Pott
PhD student in Agricultural Engineering

My research interests include digital agriculture, remote sensing, crop modeling and machine learning

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