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The kitchen sink.

  1. 🔗Kernel Density Estimation in R

    For a recent project I needed to run a kernel density estimation in R, turning GPS points into a raster of point densities. Below is how I accomplished that.

  2. 🔗Helpful Wordpress Snippets

    Some helpful Wordpress snippets that I am always looking up.

  3. 🔗Cumulative Distribution Function

    Cumulative distribution functions allow you to answer the questions, what percent of my sample is less than or greater than a value. For example I work with sage-brush cover frequently. With a cumulative distribution function I can answer the question, what proportion of my plots with sagebrush have greater than 90% cover.

  4. 🔗Subset Raster Extent w/ R

    A little snippet that helps subset raster extents.

  5. 🔗Remote Sensing Tools

    A collection of tools and documentation on remote sensing.

  6. 🔗Extract Raster Values

    Below is a method to use the raster package extract() function to get a subet of rasterBrick values. To be specific, I need to extract all raster values that are within a polygon boundary. In the past I have used crop(), mask() and then the getValues() functions from the raster package to subset data values within a polygon. But that method returns a data frame with a ton of NA values (anything outside of the crop area in the raster is an NA). This is fine most of the time but the current project that I am working on requires almost all of the memory on my computer. I'm working with extremely large rasters (2Gb). Removing the NA values after the crop(), mask(), and getValues() process crashes my computer. So I need a more effecient process.