inst/doc/Spatialize_florabr.R

In florabr: Explore Flora e Funga do Brasil Database

## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  warning = FALSE,
  message  = FALSE,
  eval = FALSE,
  fig.width = 8,
  fig.height = 6
)

## ----Get data, results='hide', message=FALSE, warning=FALSE, echo=FALSE-------
# my_dir <- file.path(file.path(tempdir(), "florabr"))
# dir.create(my_dir)
# get_florabr(output_dir = my_dir, #directory to save the data
#             data_version = "latest", #get the most recent version available
#             overwrite = T) #Overwrite data, if it exists

## ----message=FALSE, warning=F-------------------------------------------------
# library(florabr)
# library(terra)
# #Folder where you stored the data with the function get_florabr()
# #Load data
# bf <- load_florabr(data_dir = my_dir,
#                    data_version = "Latest_available",
#                    type = "short") #short version
# #> Loading version 393.401

## -----------------------------------------------------------------------------
# #Example species
# spp <- c("Araucaria angustifolia", "Adesmia paranensis")
# #Get spatial polygons
# spp_spt <- get_spat_occ(data = bf, species = spp,
#                        state = TRUE, biome = TRUE, intersection = TRUE,
#                        verbose = TRUE)
# #> Getting states of Araucaria angustifolia
# #> Getting biomes of Araucaria angustifolia
# #> Getting biomes of Araucaria angustifolia
# #> Getting states of Adesmia paranensis
# #> Getting biomes of Adesmia paranensis
# #> Getting biomes of Adesmia paranensis

## -----------------------------------------------------------------------------
# par(mfrow = c(3, 2), mar = c(2, 0, 2, 0))
# plot(spp_spt$`Araucaria angustifolia`$states,
#      main = paste0(names(spp_spt)[[1]], " - States"), mar = NA)
# plot(spp_spt$`Araucaria angustifolia`$biomes,
#      main = paste0(names(spp_spt)[[1]], " - Biomes"), mar = NA)
# plot(spp_spt$`Araucaria angustifolia`$states_biomes,
#      main = paste0(names(spp_spt)[[1]], " - Intersection"), mar = NA)
# plot(spp_spt$`Adesmia paranensis`$states,
#      main = paste0(names(spp_spt)[[2]], " - States"), mar = NA)
# plot(spp_spt$`Adesmia paranensis`$biomes,
#      main = paste0(names(spp_spt)[[2]], " - Biomes"), mar = NA)
# plot(spp_spt$`Adesmia paranensis`$states_biomes,
#      main = paste0(names(spp_spt)[[2]], " - Intersection"), mar = NA)

## ----IMG01, eval=TRUE, echo=FALSE---------------------------------------------
knitr::include_graphics("vignettes_img/IMG01.png")

## -----------------------------------------------------------------------------
# data("states")
# states <- terra::unwrap(states)
# data("biomes")
# biomes <- terra::unwrap(biomes)
# par(mfrow = c(2, 1), mar = c(0, 0, 0, 0))
# plot(states, main = "Brazilian states with simplified geometries")
# plot(biomes, main = "Brazilian biomes with simplified geometries")

## ----IMG02, eval=TRUE, echo=FALSE---------------------------------------------
knitr::include_graphics("vignettes_img/IMG02.png")

## ----warning=FALSE, results='hide', message=FALSE-----------------------------
# #Install geobr if necessary and load package
# if(!require(geobr)){
#     install.packages("geobr")
# }
# #Load geobr
# library(geobr)

## ----warning=FALSE, results='hide', message=FALSE-----------------------------
# br_states <- geobr::read_state(simplified = FALSE)
# #Convert br_states from sf to SpatVect
# br_states <- vect(br_states)

## -----------------------------------------------------------------------------
# #Plot only State of Parana as example
# par(mfrow = c(1, 2), mar = c(2, 2, 2, 2))
# plot(br_states[br_states$abbrev_state == "PR"],
#      main = "Not simplified geometries", mar = NA)
# plot(states[states$abbrev_state == "PR"],
#      main = "Simplified geometries",
#      mar = NA)

## ----IMG03, eval=TRUE, echo = FALSE-------------------------------------------
knitr::include_graphics("vignettes_img/IMG03.png")

## ----warning=FALSE, results='hide'--------------------------------------------
# br_biomes <- geobr::read_biomes()
# #Convert br_biomes from sf to SpatVect
# br_biomes<- terra::vect(br_biomes)
# #Drop off coastal system:
# br_biomes <- terra::subset(br_biomes,
#                            br_biomes$name_biome != "Sistema Costeiro")

## ----results='hide'-----------------------------------------------------------
# #See names of biomes
# br_biomes$name_biome
# #Names that must be in the Spatvector to match with Flora e Funga do Brasil:
# biomes$name_biome
# #> [1] "Amazônia"       "Caatinga"       "Cerrado"        "Mata Atlântica"
# #> [5] "Pampa"          "Pantanal"
# #Translate
# br_biomes$name_biome[which(br_biomes$name_biome == "Amazônia")] <- "Amazon"
# br_biomes$name_biome[which(
#   br_biomes$name_biome == "Mata Atlântica")] <- "Atlantic_Forest"

## -----------------------------------------------------------------------------
# spp_spt_2 <- get_spat_occ(data = bf, species = spp,
#                 state = TRUE, biome = TRUE, intersection = TRUE,
#                 state_vect = br_states, #The non-simplified Spatvector
#                 state_column = "abbrev_state", #Column name with states acronyms
#                 biome_vect = br_biomes, #The non-simplified Spatvector
#                 biome_column = "name_biome", #Column name with names of biomes
#                 verbose = TRUE)

## -----------------------------------------------------------------------------
# par(mfrow = c(2, 2), mar = c(2, 2, 2, 2))
# plot(spp_spt$`Araucaria angustifolia`$states,
#      main = paste0(names(spp_spt)[[1]], " - States simplified"), mar = NA)
# plot(spp_spt_2$`Araucaria angustifolia`$states,
#      main = paste0(names(spp_spt)[[1]], " - States non-simplified"), mar = NA)
# plot(spp_spt$`Araucaria angustifolia`$biomes,
#      main = paste0(names(spp_spt)[[1]], " - Biomes simplified"), mar = NA)
# plot(spp_spt$`Araucaria angustifolia`$biomes,
#      main = paste0(names(spp_spt)[[1]], " - Biomes non-simplified"), mar = NA)

## ----IMG04, eval=TRUE, echo = FALSE-------------------------------------------
knitr::include_graphics("vignettes_img/IMG04.png")

## -----------------------------------------------------------------------------
# my_spp <- c("Abatia americana", "Araucaria angustifolia")
# pol_spp <- get_spat_occ(data = bf, species = my_spp,
#                        state = TRUE, biome = TRUE, intersection = TRUE,
#                        verbose = TRUE)
# par(mfrow = c(2, 2), mar = c(2, 0, 2, 0))
# plot(pol_spp$`Abatia americana`$states,
#      main = paste0(names(pol_spp)[[1]], " - States"), mar = NA)
# plot(pol_spp$`Abatia americana`$biomes,
#      main = paste0(names(pol_spp)[[1]], " - Biomes"), mar = NA)
# plot(pol_spp$`Araucaria angustifolia`$states,
#      main = paste0(names(pol_spp)[[2]], " - States"), mar = NA)
# plot(pol_spp$`Araucaria angustifolia`$biomes,
#      main = paste0(names(pol_spp)[[2]], " - Biomes"), mar = NA)

## ----IMG05, eval=TRUE, echo = FALSE-------------------------------------------
knitr::include_graphics("vignettes_img/IMG05.png")

## -----------------------------------------------------------------------------
# data("occurrences")
# #select Abatia americana and Araucaria angustifolia from the dataset
# occ <- subset(occurrences, occurrences$species %in% my_spp)
# head(occ)
# #>                  species         x         y
# #> 1 Araucaria angustifolia -51.15749 -29.58290
# #> 2 Araucaria angustifolia -50.02454 -28.44414
# #> 3 Araucaria angustifolia -46.77204 -23.45729
# #> 4 Araucaria angustifolia -48.98117 -25.49632
# #> 5 Araucaria angustifolia -54.50869 -25.55113
# #> 6 Araucaria angustifolia -50.92680 -27.01826

## -----------------------------------------------------------------------------
# occ_check <- filter_florabr(data = bf, occ = occ,
#                     by_state = TRUE, buffer_state = 20,
#                     by_biome = TRUE, buffer_biome = 20,
#                     by_endemism = TRUE, buffer_brazil = 20,
#                     state_vect = NULL,
#                     biome_vect = NULL, br_vect = NULL,
#                     value = "flag&clean", keep_columns = TRUE,
#                     verbose = FALSE)
# #> Returning list with flagged and cleaned occurrences

## ----warning=FALSE, results='hide'--------------------------------------------
# #Install mapview if necessary and load package
# if(!require(mapview)){
#     install.packages("geobr")
# }
# #Load mapview
# library(mapview)

## ----fig.width= 9-------------------------------------------------------------
# #Convert points to spatvector
# abatia_occ <- subset(occ_check$flagged,
#                      occ_check$flagged$species == "Abatia americana")
# abatia_occ <- vect(abatia_occ, geom = c("x", "y"))
# 
# #Iteractive plot
# mapview(pol_spp$`Abatia americana`$states) +
#   mapview(abatia_occ, zcol = "inside_state",
#           col.regions = c("red", "green"))

## ----IMG06, eval=TRUE, echo = FALSE, fig.pos="H", out.width="90%"-------------
knitr::include_graphics("vignettes_img/IMG06.png")

## ----fig.width= 9-------------------------------------------------------------
# #Iteractive plot
# mapview(pol_spp$`Abatia americana`$biomes) +
#   mapview(abatia_occ, zcol = "inside_biome",
#           col.regions = c("red", "green"))
# 

## ----IMG07, eval=TRUE, echo = FALSE, fig.pos="H", out.width="90%"-------------
knitr::include_graphics("vignettes_img/IMG07.png")

## ----results='hide'-----------------------------------------------------------
# #Get Brazl Polygon
# br <- geobr::read_country()

## ----warning=FALSE------------------------------------------------------------
# #Iteractive plot
# mapview(br) +
#   mapview(abatia_occ, zcol = "inside_br",
#           col.regions = c("red", "green"))

## ----IMG08, eval=TRUE, echo = FALSE, fig.pos="H", out.width="90%"-------------
knitr::include_graphics("vignettes_img/IMG08.png")