How do I use these maps?

The maps show the probability of finding an usable ascending air current for a paraglider with the help of thermal trigger points. Each of the maps is optimized for a defined time period. No model data was used (only *.igc flights).
- Adjust the transparency of the background in order to improve visibility of thermal layers.
- Switch to another background layer.
- See where other pilots are flying: Superposition of all paths of flights. This layer is not time dependant.
- Probability for a paraglider to find a usable thermal. Thermal heatmaps are in function of time, specified below.
- Hotspots are good thermal points set to the peak of each area. They can be exported to any common GPS-recorder. Display is in function of time.
- This option affects time dependant layers: The nearer a thermal is to this time of year (month) the better it is shown.
- This option affects time dependant layers: The nearer a thermal is to this time of day (hours since local sunrise) the better it is shown.
What's a trigger point?

A thermal trigger point is a theoretical spot on the surface, where the heated air packages detach from the ground.
Wind shift in flyable heights is approximated linearly. A pilot has to be aware of winds in order to actually hit the thermal. Weather properties such as wind speed, altitude of the cloud base, gradient of the air and so on depend on the given day. However, trigger points (mostly) don't.
What about the weather?
Surprisingly the global weather conditions are of minor importance if one wants to find the thermal trigger point. However, weather is very important for paragliders since pilots mainly chose the area according to the conditions. Given a certain area, most flights are performed under very similar conditions and the positions of the trigger points are roughly the same. The wind component is limited as much as possible by reducing thermals to trigger points.
How good are thermal maps?
The main factor for good thermal maps is the flight density in a given area. It was also discovered that maps are generally better if the topology is the main thermal factor. In some regions, only sparse thermal predictions can be shown, since there is only little information available. For example in the flatlands the prediction quality is generally lower, since there are fewer flights and most of them are performed according to cloud position and not according to static trigger points on the surface. Regions with sparse information were kept transparent in order to reduce clutter. Furthermore, thermals next to popular launch pads are generally overrated (the position, however, is correct). This is caused by the fact, that most pilots only upload a flight if they at least catch the first thermal.
What do I as a pilot need these maps for?
First of all, very good pilots which are familiar with a certain flight area, barely profit from the maps. But the maps proved to be useful for studying a hitherto unknown area: Where do I find my first thermal? Thermal probability is a good idea if no other signs for thermals are available. If one sees a beautiful cumuli, a climbing bird or even other climbing pilots, one has to blame oneself for preferring to follow the thermal maps. A second purpose is the analysis of performed flights (which is especially interesting in GoogleEarth) in order to optimize tactical decisions made by other pilots in previous flights.
What are hotspots?
Hotspots are points where it is likely to find a thermal. They are extracted out of the raster based thermal maps. Again they are time dependent. Their main purpose is an upload into a GPS where they come in handy during flights.
How about soaring?
Soaring is filtered out wherever possible.
How were the maps created?
The initial effort was my masters thesis "
ParaglidingNet - A Sensor Network for Thermal Research". From this the paper "
Ikarus: large-scale participatory sensing at high altitudes" emerged (it's more technically oriented and less to paragliding).
But seriously; this is a lot of theory on sensor networking and such. But what really mattered was to create an open map database for every paragliding pilot out there and to provide simple tools to improve everyones flights.
Do note, however, that in the time since this thesis was written the toold and methods used where heavily optimized and extended to new regions.
Feedback
Please send me your wishes for new features or a note if you found a bug. Needless to say, I'm especially interested in your experiences with the tool while flying.
Links
Flight Databases used:
Software Sources:
Maps (Background and DHM-Input):
Thermal maps used by thirdparties:
More thermal maps
Useless Statistics
last run: 11 May 2013, min distance: approx 10km
total nr of unique flights in database: 682'879
total nr of invalid flights: 15'684 (2%)
total nr of flights with thermals: 562'045 (82%)
total nr of thermals: 4'491'639
average thermals per thermal flight: 8
Licence

All
thermal.kk7.ch Thermal Maps are licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License by
Michael von Känel (info at kk7 ch).
This means that you are free to copy and reuse any of my thermal maps/hotspots (noncommercially) as long as you tell people where they're from and publish modifications under a similar licence.
If you plan on including thermal tiles into your own map server contact me directly. I need to know your expected load and you have to append a
&src=[hostname] to every request.