Geoscience Analysis with R

This post demonstrates geoscience data analysis using R.

# Load necessary libraries
library(ggplot2)
library(sf)

Linking to GEOS 3.11.2, GDAL 3.7.2, PROJ 9.3.0; sf_use_s2() is TRUE

library(raster)

Warning: package 'raster' was built under R version 4.3.3

Loading required package: sp

Warning: package 'sp' was built under R version 4.3.3

# Load a sample shapefile (replace with your own geospatial data)
shapefile_path <- system.file("shape/nc.shp", package = "sf")
geo_data <- st_read(shapefile_path)

Reading layer `nc' from data source 
  `C:\Users\hafez\AppData\Local\R\win-library\4.3\sf\shape\nc.shp' 
  using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
Geodetic CRS:  NAD27

# Plot the geospatial data
plot(geo_data["AREA"], main = "Geospatial Data Visualization")

# Load a sample raster dataset (replace with your own raster data)
raster_data <- raster(system.file("external/test.grd", package = "raster"))

# Plot the raster data
plot(raster_data, main = "Raster Data Visualization")

# Perform a simple spatial operation: calculate the centroid of polygons
centroids <- st_centroid(geo_data)

Warning: st_centroid assumes attributes are constant over geometries

# Add centroids to the plot
plot(geo_data["AREA"], main = "Geospatial Data with Centroids")
plot(centroids, add = TRUE, col = "red", pch = 16)

Warning in plot.sf(centroids, add = TRUE, col = "red", pch = 16): ignoring all
but the first attribute