For a geomorphological study that I am working on I want to produce topographic swath profiles across a mountain range, that is, I want the average elevation along a profile plus the min and max values within a certain distance of said profile. I have used three different methods to achieve that and found some nice resources that I’d like to share with you: GMT – Generic Mapping Tools GMT is a powerful suite of command-line small programs to manipulate all kinds of geographic data (Wessel and Smith, 1998; Wessel et al., 2013). A walk through on how to produce…
The goal of this post is to explain, based on practical examples from my professional activities, how I use QGIS, its plugin photo2Shape and the processing toolbox, together with geospatial packages of R (e.g. the package ‘leaflet’) to exploit efficiently georeferenced pictures.
GPX overview: An R function to create an overview of your .gpx files (using leaflet and RgoogleMaps)
Why GPX? For what? It's convenient to record tracks of your hiking/field trips with the GPS of your smartphone, tablet or just GPS as .gpx files. You can use them to georeference your pictures (for example with the great georefencer of Digikam) or use them for any kind of mapping purpose. I'm mainly using Maverick (and sometimes the Offline Logger ) to do that, Maverick creates files named with the form "2015-08-26 @ 11-31-59.gpx", therefore I'm quickly collecting a large amount of such files.
Data analysis in the modern-day computing industry is of great essence as the world tries to understand the data that has been accumulated in many systems across the globe. Extraction of useful information is a task being focused so much in most organizations as this is marking the lifetime for existence in the business world.
Coursera, hail to Coursera. Despite the uprising criticism on MOOCs and their footprint in the educational landscape at universities Coursera created an interesting R learning course. It is divided and scheduled for 4 weeks and has video-tutorials as well as written material. The guys over at RevolutionAnalytics packed it all together: Content: Setting working directory and getting help How to get help Data Types Subsetting Vectorized Operations Reading/Writing Data Control Structures in R Writing Functions Avoiding loops using xapply Plotting Regular expressions Regular expressions in R Classes and methods in R It is a free course and is very userfriendly. The…
As i was preparing myself for getting funding for the trip to the R user conference this year in Albacete, Spain I was coming across a highlightning talk by Josh Paulson about an interactive way of using the power of R without real struggling with R as a programming language: Shiny is a cool webapp which lets the user control the application via some drop-down menus and buttons and R computes the result in the background and displays them as well on the webpage:
Due to an upcoming presentation about “what is R” and “what can I do with R” in my company I was playing around with GUIs as they are a very important way to interact with users and R to present a simple calculator. This will lead hopefully to an understanding of syntax and concepts in R:
Thank’s to Andrej who wrote this comment: “Is it possible to to color the resulting 12 clusters within your original image to get a feel for visual separation?” You can do so:
The main question when using remote sensed raster data, as we do, is the question of NaN-treatment. Many R functions are able to use an option like rm.NaN=TRUE to treat these missing values. In our case the kmeans function in R is not capable to use such a parameter. After reading the tif-files and creating of a layer stack we will go on with a work-around to solve the missing values problem of the non-covered areas of a Landsat picture.
In my last post I was explaining the usage of QGis to do a layerstack of a Landsat-scene. Due to the fact that further research and trying out resulted in frustration I decided to stick with a software I know well: R. So download the needed layers here and open up your flavoured version of R (in my case RStudio).