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When working with raster data such as satellite imagery, it is sometimes necessary to combine multiple adjacent, possibly overlapping smaller rasters into a single large raster that covers the entire area of interest. This example demonstrates one way to use R to create a raster image mosaic while also applying a resampling algorithm to align the inputs.
This example demonstrates two R programming techniques for resampling (changing the cell size or spatial resolution) of a raster satellite image. The first technique uses data objects and methods from the sp package. The second technique uses the recently released (Fall, 2009) raster package. We resample the same satellite image, and compare the results of all sampling methods by computing elementary statistics.
This case presents an R script that: 1) Reads and displays in an outline map ESRI point and polygon Shape Files for a three-county Central California region; 2) demonstrates two different R programming methods for generating the Convex Hulls bounding the polygons 'belonging' to each county, 3) calculates the areas of each county and Convex Hull polygon.
This example demonstrates the use of the R geospatial classes to compute polygonal Regions of Interest surrounding collections of spatially-distributed points. Three methods demonstrated.
Two examples demonstrate the use of the R environment to process data sets from GPS devices:
Both examples use methods from the sp and maptools packages.
R includes a rich set of plotting functions that can be applied to spatial data. This example demonstrates how to generate publication-quality maps using these functions, which in many cases can eliminate the need to use dedicated GIS software.
This case demonstrates:
The ESRI Shapefile is a widely used file format for storing vector-based geopatial data (i.e., points, lines, and polygons). This example demonstrates use of several different R packages that provide functions for reading and/or writing shapefiles.