Hey there,
when working with very large vector or raster files then it can often take some time for the rendering process – and that’s usually annoying!
So, here are some tips for you, how to speed up your QGIS.
Modern CPUs are multi-core processors. QGIS uses by default
Happy new year 2017!
It’s January 1st and I made the new years resolution to post more this year. 🙂 So here is a short tutorial on how to download SRTM (Shuttle Radar Topography Mission) 90m resolution data (3 arc seconds) for an entire country using the {raster} and {rgeos}
Hey!
Today I am going to finish the series on how to increase the speed of processing raster images with R. In the last two posts I talked about changing the rasterOptions() and about parallelisation using foreach(). Both of these options migth give you a decent speed boost and
Hey there rasterR folks!
I love to code with R – most of my time I am spending on processing raster data with the {raster} package, bceause it’s quite intuitive and easy to use compared to other scripting languages. Sometimes however, when I work on larger datasets or when I
Hey there!
I was recently asked by a user how to calculate the Land Surface Temperature (LST) from Landsat 8 imagery and decided to write an article on this topic. I hope you will enjoy it.
Let’s start with the basics – What is LST?
The Land Surface Temperature (LST) is
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
Dear GIS enthusiasts!
As you already know, R is my favourite tool to work with spatial (raster) data. In some situations however, I am forced to move to a GIS desktop softwarer (Ã la QGIS) to get some basic information on my raster file. Since switching inbetween two softwares is annoying
Hey rasteR people !
Welcome to the second part of my tutorial on how to increase the processing speed of the R {raster} package. In the previous part I showed you how to speed up R by increasing the maxmemory limit. This part will be a little more
Hey there!
Today I would like to do a small comparsion between three raster processing tools:
R, Python (rasterio) and GDAL.
When I started with GIS and raster processing, I didn’t really pay much attention to the performance of the scripts I wrote and tools I used. But now, working
Hey!
Today I will show how powerful the R {raster} package is on another example. The raster package is not only a great tool for raster processing and calculation but also very useful for data acquisition. With the function getData() you can download the following data directly into R and process
