Shapefile and Basemap

Hello


On 5/13/22 12:47, sownal chand wrote:

Hello sir/madam,

I am working with shape file of my country and the issue I am facing
is the shapefile is scattered while plotting it using basemap. I am
using my sample point data which is attached to this email. I hope
that some expert in this area would help in correcting the codes below
to show the shapefile in one location ( its a pacific centered map)

When you raised this question a few weeks ago, it was suggested to avoid
the `sp` package with its SPDF data type, and instead focus on the newer
`sf` package.

There is also a replacement for the raster::getData function in the new
`geodata` package.


Here is a much simpler version of what (I think) you are trying to achieve:


# Load only three libraries

library(sf)
library(tmap)
library(geodata)


# Read your list of data (You should remove the summary line in advance...)

dt <- read.csv("DataR.csv")
dt <- dt[complete.cases(dt),]
dt_sf <- st_as_sf(dt, coords=c("long", "lat"),
                   crs="EPSG:4326")
str(dt_sf)

# Get Fiji boundary from geodata package
fiji <- gadm(country="FIJI", level=2, path=tempdir())
# Convert to sf object for tmap plotting
fiji <- st_as_sf(fiji)


# Visualize with tmap

tmap_mode("view")
tm_basemap("OpenStreetMap.Mapnik") +
         tm_shape(fiji) +
         tm_borders(col="brown", lwd=2) +
         tm_shape(dt_sf) +

         # size of symbols by yearly data. You can choose any year, of
course

         tm_symbols(col="blue", size="Year2", scale=0.1)



If you have a specific problem with a certain shapefile, you'll have to
supply it to the list in order to get further help.


HTH

**************************************************************************************************

library(sp)
library(raster)
library(rgdal)
library(leaflet)

#read.csv
read.csv ("C://Users/Documents/data.csv") -> data.df
head(data.df)

hist(data.df$Year, breaks=20)

#remove NA valuues in the spatial Data Frame
data.df <- na.omit(data.df)
View(data.df)

plot(data.df$long, data.df$lat,
     ylab = "Latitude", xlab="Longitude") #boring!

# Use the cex function to plot circle size as a function of a variable
plot(data.df$long, data.df$lat,
     cex = data.df$Year.7 * 0.045,
     ylab = "Latitude", xlab="Longitude")

data.df_SPDF <- SpatialPointsDataFrame(coords = data.df[,c("long",
"lat")],
                                                data =
data.df[,c("Year", "Year.1", "Year.2","Year.3","Year.4")],
                                                proj4string =
CRS("+init=epsg:4326")) # sets the projection to WGS 1984 using
lat/long. Optional but good to specify

# Summary of object
data.df_SPDF

# SPDFs partition data elements, e.g. the coordinates are stored
separately from the data
head(data.df_SPDF at coords)

head(data.df_SPDF at data)


# You can quickly access the data frame as per a standard data frame,

e.g.

head(data.df_SPDF$Year)


# You can use the plot or spplot function to get quick plots
plot(data.df_SPDF)

spplot(data.df_SPDF, zcol = "Year")

FIJ_Adm_2 <- readOGR("FIJ_Adm_2_shapefile", "FIJ_Adm_2")

# You first need the ISO3 codes for the country of interest.

# The getData function then allows you to retrieve the relevant admin
level boundaries from GADM.
FJI_Adm_2 <- raster::getData("GADM", country="FJI", level=2)

# Plot both country and data points
plot(FJI_Adm_2)
points(data.df$long, data.df$lat,
       cex = data.df$Year * 0.045,
       ylab = "Latitude", xlab="Longitude",
       col="red")

basemap <- leaflet() %>% addProviderTiles("CartoDB.Positron")

basemap %>% addPolygons(data=FJI_Adm_2)

# to change the colors/line weight
basemap %>% addPolygons(data=FJI_Adm_2, color = "red",
                        weight = 1, fillOpacity = 0.2)


# If you want to add points as well
basemap %>% addPolygons(data=FJI_Adm_2, weight = 2,
                        popup = FJI_Adm_2$NAME_2) %>%

  addCircleMarkers(data=data.df_SPDF,
                   color="red", radius = 2)

library(wesanderson) # for a nice color palette
colorPal <- colorNumeric(wes_palette("Zissou1")[1:5],
data.df_SPDF$Year, n = 5)


# colorPal is now a function you can apply to get the corresponding
# color for a value
colorPal(0.6)

basemap %>% addPolygons(data=FJI_Adm_1, weight = 2, fillOpacity=0,
                        popup = FJI_Adm_1$NAME_1) %>%

  addCircleMarkers(data=data.df_SPDF,
                   color = colorPal(data.df$Year),
                   radius = 2,
                   popup = as.character(data.df$Year))%>%

  addLegend(pal = colorPal,
            title = "Average Temp for Year",
            values = data.df_SPDF$Year)

*************************************************************************************************

Thanking you in advance
sownalc

--
Micha Silver
Ben Gurion Univ.
Sde Boker, Remote Sensing Lab
cell: +972-523-665918
https://orcid.org/0000-0002-1128-1325