Dear all,
today I’d like to point to the Rocker project, which provides a suite of Docker images for particular tasks. Even though the Rocker initiative already exists since 2014 and I read about it once in a while, there were not many use cases for me to try it
Hey folks!
Today I am going to show you how to perform a very basic kMeans unsupervised classification of satellite imagery using R. We will do this on a small subset of a Sentinel-2 image.
Sentinel-2 is a satellite launched by the European Space Agency and its data is freely accessible for
Dear all,
I just came across a very useful, fast and efficient function for matching points in one data frame to their nearest neighbours in another data frame. Of course, I’d like to share my newly acquired pearls of wisdom with you.
I’d like to outline the problem definition by providing a
Dear all,
I have slightly revised parts of the code used in my posts on Extreme Value Analysis. While they were correct with respect to the results, some parts of the code written by former me more than two years ago were plainly ugly. I have also removed some redundancies and
Hello,
today I’d like to draw your attention to an upcoming, interesting R package for handling spatial data.
Following the successful release of the sf package, which simplifies and optimizes many aspects of handling spatial (vector) data in R by implementing simple features as native R data (alongside with many R convenience
My favourite supervised classification method for land cover classification until now was the very popular Random Forest. Recently however, I stumbled upon the xgBoost algorithm which made me very curious because of its huge success on the machine learning competition platform Kaggle where it has won several competitions. Since I
Dear all,
when working with linestring features (e.g. river or infrastructure networks), we might want to join two data frames by group and interval. I recently had to perform such a task when I wanted to join traffic volume data of permanent traffic counters (available at https://www.asfinag.at/verkehr/verkehrszaehlung/) on a road
Dear all,
back in 2014, Hadley Wickham’s dplyr tutorial at useR!2014 drew a lot of attention to the %>% (pipe) operator from the magrittr package. While the pipe operator is an essential part of the tidyverse workflow, and is thus well-known to users of packages belonging to the umbrella of
Dear all,
during the process of streamlining my posts on extreme value analysis, I have tried to rework the import of the data sets used for my elaborations. Usually, one would definitely use custom functions to perform tasks like this data import, and I figured that this is also useful in
Hey folks,
sf is an rather new R package for handling and analyzing spatial data in R. While various R packages are available that provide classes and methods for spatial data (e.g. sp, rgdal and rgeos), sf, which is developed by Edzer Pebesma and others, is intended to gradually replace