As we are thinking more or less specially I always ask myself: where can I be in the next 30 minutes? Most of current webmaps out there are not answering this quite good using isochrones as example. Most of them taking into account the direct distance which have some major implications if you compare the distance of 30min road trip through the countryside compared with the same time in Paris: about 50km against , right? So I would like to show you, how to get a better idea of reachability using three different approaches but all implemented in Leaflet.
The recent move from the Mongolian Post to use W3W as their new address system shed a new light on the question: Where are addresses located and how to get the correct position of an address in your GIS. In this article I would like to show different possibilities in QGIS, ArcGIS and Leaflet. This post references also mappinggis.
If you create maps you always need to ask yourself: how can I make it as easy as possible to read and still have anything I need in my map… or in short: reduction and abstraction. There are different approaches out there when it comes to web maps. Let me show you how to reduce the number of map elements with a slider in leaflet to filter your data interactively.
Perhaps you have already used in your work OpenWebGIS or just have seen it or read about it. Due to this system exists since 2014. But we will describe OpenWebGIS briefly. It is an open source online/offline geographic information system for work in web browser or mobile app. Since its foundation, a great number of users have benefited from using this system functions.
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.
Some months ago I published qgis2leaf which enables a QGIS user to publish a webmap the easy way. It was integrated into qgis2web which offers a leaflet and a openlayers based output for qgis users. But what about R users? Jean-Francois recently published a longer post about GPX tracks and to publish them using some heavy coding. So let’s welcome leaflet for R: an easy leaflet webmap exporter.
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.
We recently showed some possibilities to work with routing APIs in QGIS. Besides the Google API and the API from OpenRouteService.org Mapbox also offers some nice routing technology with their Directions API. This was recently updated.
When I started to work on QGIS2leaf about one year ago it was a nice idea and my first real dive into Python programming and using the possibilities of pyqgis. So what is the current state and where are we going? Please, come and take a look: Happy Birthday QGIS2leaf!
When it comes to webmapping there are thousands of possible markers you can choose from but when it comes to markers depending on the data, which is inside the shapefile, possibilities are more limited. In leaflet you can define different icons according to the attributes of your data by defining the icon url in an attribute. Let me show you, how to use the data in each feature to create a custom icon like a piechart marker using R.
There are so many applications out there but they probably share one thing: export your data as a XXX-delimited table. And it’s also very easy to create a comma-separated text file out of it. You also have some lat/lon values in this table? Great! Let’s make a heatmap with leaflet.