Some time has past since I last wrote a DEM comparison, comparing ALOS World with SRTM 1 and GDEM V2 with SRTM 3. But as NASA and METI released the lates version of the ASTER GDEM dataset, I will compare this once again for a certain area in central Mongolia. But this time, the competitor will be SRTM 1.
It’s been a while, since I last developed things for qgis2web. To be honest: I lost focus on the whole project after we decided to merge qgis2leaf with the openlayers exporter back in 2015. Tom Chadwin and many others did a great job and managed to develop the state of-the-art plugin when it comes to publishing content right from within QGIS. But as I was lucky I had the chance to develop some interesting things for QGIS2web in the last weeks.
In the past I was working on different plugins to connect with multiple APIs and use their isochrone endpoints in QGIS. Let me summarize some of my findings and share my opinion on HERE, Azure Maps, Bing Maps, ORS, Esri and Iso4App.
The ArcGIS REST API provides some interesting endpoints which can be used for free with a developer account. But how to do this in QGIS as you might not have a licensed ArcGIS Desktop license at hand: A short example using isochrones or “service areas” as Esri calls them.
The OSM based QuickOSM plugin offers a great way to download some data from OSM. As an alternative I am developing HQGIS which offers an easy way to get geocoded addresses, routes, isochrones and POIs for your everyday work based on the HERE API and the HERE datasets. Now the plugin offers support for the processing toolbox as well. Follow me on a short insight into POI search around desired addresses.
API’s are getting more and more important as some (maybe the majority?) of GIS users don’t want to handle large datasets, don’t want to care about addresses and geo-coordinates, don’t want to create an own routing algorithm… As most of you might use Google, OSM or HERE for geocoding purposes I would like to introduce Azure Maps for this as well.
Currently I am trying to improve my coding skills in Python. Of course you can read some books, attend some Udemy course but in the end it boils down to practical training. Codeacademy is most likely the first place to go to for practical learning. Now there is a new, quite un-fancy boy in town: CodingBat
The last days I needed to work with other geoenthusiasts on a PostGIS database. Unfortunately, as you upload a layer from QGIS you will be the owner of the new created table and no one is able to alter it by default. Here I show you, how to change this using some “trigger functions” and some shared roles.
When using QGIS along with PostGIS you might want to publish data directly from inside QGIS into your PostGIS database. This is not only convenient as you don’t need to change the software of use but also easier as it only takes a drag and drop in QGIS instead of any commandline/fancytool. Yet it comes with a disadvantage: the number of inserts from QGIS into the db is limited to 200 per transaction. So it will take some time to insert a bigger dataset with 150.000 points or so. So how to overcome this?
Let’s assume you like cruise ships, tanker, ferries or you’re so fortunate and own a fleet of vessels cruising over the oceans. But where the heck are the ones you’re interested in. First you can visit MarineTraffic and search for the Vessels you’re interested in. But what if you want to keep track of those vessels or if you want to put them on your “own” map. Now Python comes in handy and I’ll show you how to gather coordinates and put them on a map using the ArcGIS API for Python.
QUickOSM is my weapon of choice when it comes to downloading data from OSM in QGIS. The tool offers an easy way to access tag/key combinations with a designated spatial query. As I was asked how many bus stops Berlin has, I was interested in a similar approach for ArcGIS. So I created my own little tool: OSMQuery.
The Copernicus Program provides an interesting alternative data source for your work with Landsat data… Sentinel images: Copernicus will deliver an unprecedented volume of free data, provide new operational services and foster new business opportunities and job creation. The data itself is collected since 2014 (Sentinel 1A) and the operation is scheduled to deliver data till 2020 at least. But how to get the data into the GIS of your choice.
Back in 2016 Uber surpised the geo market with its solution “deck.gl“, a “predecessor” of kepler.gl: WebGL2 powered geospatial visualization layers The visuals were quite stunning: You can find some more information about deck.gl 4.0 at the Uber blog. Kepler.gl is build on top of this Uber framework: a data-agnostic, high-performance web-based application for visual exploration of large-scale geolocation data sets. Built on top of deck.gl, [it] can render millions of points representing thousands of trips and perform spatial aggregations on the fly.
We’re happy to announce the release of v4.5 of openrouteservice, which exposes unique services for two of our core API’s, routing and isochrones. Now you can restrict routes to avoid crossing borders and get instant population counts on isochrones.