Mapping Pacific centered map for Spatial analysis

Hi:


I've prepared an alternative to your code, with some ideas that might
help. Following Roger's comment, I transformed the spatial layers to
EPSG:3460. The code is attached.


I also have a few comments. Inline, below:


On 13/03/2022 11:26, sownal chand wrote:

Hello Micha,

Thank you for your prompt response. I am attaching my codes and sample
data for your reference.
As I mentioned earlier, I am trying to interpolate climate data using
IDW and visualize the Climate change that is happening in My country
from the past 55years till date (2021).
Moving forward, I am new to spatial interpolation using R and would
like to write codes in R so that it is easy to notice the changes in
the average temperature, Max, Min temperature, rainfall and
other climate variables.

First, you're using some older packages (rgdal and rgeos). Today it
makes sense to switch to the newer sf without those dependencies.

# import libraries
library(raster)
library(ggmap)
library(RgoogleMaps)
library(rgdal)
library(ggplot2)
library(rnaturalearth)
library(dplyr)
library(tidyr)
library(gstat)
library(rgeos)
library(scales)
options(stringsAsFactors = FALSE)

# Fiji geo data & study Area
# download
#Draft map of Fiji
Fiji_studyarea <- readOGR("../input/fijishp/FJI_adm2.shp")
extent(Fiji_studyarea)

# import climate data - netcdf format
Temp <- read.csv("../input/TempData/53YearsTemper.csv")
Temp
str(Temp)

This data file is in "wide" format. In the example I show how to make it
"tidy" for further plotting and analysis.

# check out our one years data
Temp$Year.3

# remove NA values
Temp <- Temp %>%
  drop_na()
Temp

# create spatial points object
Temp_sp <- Temp
class(Temp_sp)

# convert the data into spatial coordinates
coordinates(Temp_sp) <- ~long + lat
class(Temp_sp)

# view spatial points
plot(Temp_sp$Year,
     main = "Average Temperature for year 1965")

Next, you have data from only a few, widely spaced stations, and IDW
might not be the best interpolation method. But that's for you to decide.

##### IDW interpolation ##### From here the code gives errors as the
interpolation area is very small.
# establish an extent within which you want to interpolate
x_range <- as.numeric(c(290.00, 360.00))  # min/max longitude of the
interpolation area
y_range <- as.numeric(c(-23.00, -17.00))  # min/max latitude of the
interpolation area

With gstat you can now use a stars object as target grid. See my example.

# create an empty grid of values ranging from the xmin-xmax, ymin-ymax
grd <- expand.grid(x = seq(from = x_range[1],
                   to = x_range[2],
                   by = 0.1),
                   y = seq(from = y_range[1], to = y_range[2],
                       by = 0.1))  # expand points to grid
class(grd)

# crs = 3832, # https://epsg.io/3832 Pacific centered CRS

# interpolate the data
idwTemp_pow1 <- idw(formula = Temp$Year ~ 1,
           locations = Temp_sp,
           newdata = grd,
           idp = 1)

# plot the data
plot(idw_pow1,
     col = terrain.colors(55))


Please can you assist in correcting these errors. and the shapefile
does not show on the map. OR you can give a better option of codes to
follow doing this.

Really appreciate your assistance and thanking you in advance

Final comment. You mentioned a time series analysis to follow climate
change. You'll have to decide how you want to go about this. Are you
going to prepare interpolations for each year, then do a pixel by pixel
change detection? In my example I show a simple time series plot of
temperature data, by station.


HTH

Regards, Micha

On Sun, 13 Mar 2022 at 20:45, Micha Silver <tsvibar at gmail.com> wrote:


    On 13/03/2022 01:41, sownal chand wrote:

    > Hello Sir/Madam,
    >
    > I am Sownal Chand, from Fiji Islands and am currently working on

    a project

    > which involves spatial analysis of climate data (Temperature,

    rainfall,

    > etc). I have been able to write codes in R for Point

    interpolations of

    > these parameters but I require some assistance in mapping these

    raster

    > files on the southwest pacific maps. For example, a map of Fiji

    Islands  (

    > https://www.pinterest.com/pin/740982944911004875 ) and I am

    facing some

    > difficulties in making these plots.
    >
    > I hope that some expert would be willing to help me with this

    and the map's

    > CRS setting is a bit confusing and I am a beginner in this area

    ( i. e,

    > spatial analysis using R). I have been looking at tutorials and

    codes to


    There are tons of online resources. You could, for example, refer to:

    https://geocompr.robinlovelace.net/

    > crop country boundaries and shapefiles and still found lots of

    errors in my

    > codes.

    You have raised a few different questions. Would you mind to post
    what
    you have done so far, and point out the errors and difficulties?

    > Hoping to find solutions to my problems and learn from this.
    >
    > yours sincerely
    > sownalc
    > Contact: sownalchand at gmail.com
    > PH +679 2960779
    >
    >       [[alternative HTML version deleted]]
    >
    > _______________________________________________
    > R-sig-Geo mailing list
    > R-sig-Geo at r-project.org
    > https://stat.ethz.ch/mailman/listinfo/r-sig-geo

    --
    Micha Silver
    Ben Gurion Univ.
    Sde Boker, Remote Sensing Lab
    cell: +972-523-665918

--
Micha Silver
Ben Gurion Univ.
Sde Boker, Remote Sensing Lab
cell: +972-523-665918