A post at the geekier end of the spectrum as a couple of small changes to the VeloViewer Explorer Tile calculations are rolled out to fine tune some of those edge-case scenarios where tiles might have been missed. One key area was addressing the very rare occasions where your GPS device didn’t record a point […]
I’ve wanted to produce this view of VeloViewer Explorer Tiles since I first came up with the idea back in 2015 and can only put my lack of action down to being too busy with the professional teams these last few years! Simple idea though: provide a KML output that can be viewed in Google […]
When I meet VeloViewer users out and about, the enjoyment of ticking off VeloViewer Explorer Tiles is the most common feedback I get. Since I came up with the idea of Explorer Tiles back in 2015 1000’s of VeloViewer users have been discovering new roads and trails close to where they live and further afield. […]
In August I was contacted by Karl Andersson, an MA student of Visual and Media Anthropology at Freie Unviversität Berlin who was doing a project on the VeloViewer Explorer functionality along with how and why people use it. The link to his survey was shared and many of the most devoted Explorers responded. Karl has […]
Since the introduction of the Explorer Score and Explorer Max Square there have been requests for some sort of metric to represent the maximum number of connected Explorer tiles. The recent improvement in the calculation of completed Explorer tiles sparked a very active discussion which resulted in the refinement of the concept and the creation of the Explorer Cluster. The Explorer Max Square provides a hard-core challenge but can be tricky for people who live in geographically challenging areas or have key tiles which are completely inaccessible. This is where the Explorer Cluster looks to provided a more level playing field.
The way that completed Explorer tiles are calculated has remained pretty static since its inception in March 2015 which included some, less than precise code to try to get around some of its known limitations (detailed below). I’ve now refined that code to improve the accuracy and also speed up the processing quite considerably and also introduced a method to get a definitive list of tiles for an Activity. This improved accuracy will of course result in a number of tiles that were previously marked as ticked now showing up as unticked (and potentially affecting your max square size) but only tiles that you never actually visited in the first place 🙂
The Explorer Max Square leaderboard has brought together a small but remarkably dedicated international community of riders taking in new roads and trails at every opportunity in order to increase their Explorer Max Square. What drives them to ride across frozen lakes, attempt to access military bases and buy opera tickets to tick off map squares? Let’s ask them!
The VeloViewer Explorer Score and more specifically the Explorer Max Square has acquired a bit of a cult following since its introduction to the site back in March 2015 despite me not having fully explaining what it is all about until now! The Explorer Score rewards those people who explore new roads/trails rather doing the same old loops. Providing non-performance based motivations has always been one of the main goals of VeloViewer and this one really looks to tick that box.
All of the data you see in VeloViewer comes direct from Strava’s API, lots of information is just that raw data from Strava being presented in different ways and then I also calculate lots of other interesting stats (e.g. Explorer Tiles) and visualisations (e.g. 3D profiles). If you are a Strava Subscriber then the Strava […]
Yesterday (30th September 2019) I released an update migrating over to Strava’s updated authentication process. The first time you revisit VeloViewer after this date you will be re-prompted to allow VeloViewer access to your Strava data. The number of options that users agree to allow access to has increased and below I will explain why […]