If you are reading this post – you might know something about satellite imagery. This is a valuable source to power quite a lot of analytics and monitoring applications. In this post I’d like to give you an idea of how all this Big Data stuff can be obtained and processed online, using the single API called #VANE language. What is VANE? The VANE geospatial platform, that’s coming out of the Beta now, is a new project we started at Openweathermap, relying on our expertise in providing well-designed APIs for weather data which is widely used by devs community. The…
Data Lakes has become a popular term in the Big Data community. It’s used to refer to a large storage repository and processing engine. However there is now a technology from NOAA (National Oceanic and Atmospheric Administration of the USA) that turns its existing distributed data network of Petabytes of Open Data into what can be described as a Data Ocean! This technology is called ERDDAP and it provides fixed entry points on the Internet from which data can be searched for, queried and transformed. This functionality is made available via a human interface (web site) and Restful Web Services.
Not long ago I was tasked with finding out how many people live within an arbitrary polygon. In this particular case, the polygon represented the portion of the United States within a drive-time of 10 hours. For this example, the polygon(s) can be anything you wish. This post will act as a tutorial of sorts on how to answer questions like these using python. Sorry to my Deutsch Freunden on this site, but this will be a U.S based answer as using the Census API is a key part of it. This is a classic case of the modifiable area unit problem.…
When it comes to certain tasks the usage of leaflet can be tricky. Of course it claims not to be the ultimate webmapping solution but one of the sleekest ones. But when it comes to csv files and reading data from them I always found it hard to implement given solutions listed in the plugins section of leaflet.
It’s snowing here in Berlin. And I already thought, that we wouldn’t have any white color out there before Christmas Eve. In order to check the weather forecast for the next days, I found www.openweathermap.org. A really nice tool to get current weather data and some more informations based on more than 40.000 weather stations around the globe. Best of all, openweathermap.org provides APIs for several weather-data excerpts for free.
Dear folks, most of you probably know how to map things using software on your pc. Some of you might also know cartoDB. We like their service as our job-page here on digital-geography.com is based on their tables, API and GeoJSON export functionalities. Additionally it’s for free (with some limitations)… The guys from CartoDB now offer an online learning event which will give newbies the chance to map their data in a very interesting online mapping engine.
Today I stumbled upon a “map” on Spiegel Online ( an import news page in Germany ) which shows the spied countries of the NSA. As we already know leaflet quite good and also tried other mapping possibilities I was interested in what they are using for this map which is more informative than this useless map. So looking on the source code: It’s a library called jvectormap.
In a recent post I’ve described a way to geocode in a Google Spreadsheet quite easily. Now let’s move a little bit away from this crazy web 2.0 stuff and get a little bit more desktop orientated: Let us geocode addresses directly in LibreOffice (and OpenOffice probably as well). We will do this using the googlemaps API. If you are really into open stuff we show OSM geocoding as well.
Thanks to a comment on our facebook page: Due to the conflict in state finances in the U,S and A gesocientists are affected: data providers like the USGS and their websites like landcover.org and others are unavailable!
We have already introduced cartoDB which is a platform for storing, administering and visualizing spatial data. One straight feature of cartoDB is the usage of GeoJSON for exporting their tables. In this tutorial I’ll document a working example on consuming this layer with leaflet. But first we will start with the easy part of creating the table in cartoDB.