Western Alps autumn colors 2017

January 27, 2018
by chris

Mapping imagery additions

Over the last days i added a number of images to the OSM images for mapping produced from Sentinel-2 and Landsat data.

There are three new images for the Antarctic:

McMurdo Bay area

This image covers the McMurdo Sound, McMurdo Dry Valleys and Ross island. Data is from February 2017 – end of summer, but with quite a bit of seasonal sea ice cover still present.

There is a lot that can be mapped from this image in terms of topography, glaciers and other things. It can also be used to properly locate features where you only have an approximate position from other data sources. If you compare the image with existing data in OSM you will also see that there is significant mismatch in many cases. Positional accuracy of the image – like the other Antarctic images – is good but not great. In mountainous areas at the edge of the image swath (here: in the northwest) errors can be more than 50m probably on occasion but otherwise will usually be less.

Bunger Hills

Another part of the East Antarctic coast. This requires a bit of experience to distinguish between permanent and non-permanent ice. But existing mapping in the area is poor so there is a lot of room for improvement.

Larsen C ice shelf edge

This is an image for updating the ice shelf edge after the iceberg calving in 2017. The current mapping in OSM here is very crude since based on low resolution images.

Western Alps autumn colors

And then there is another image which is more of an experiment. This is an autumn image from the western Alps that shows autumn colors and could be helpful for leaf_cycle mapping. I am not quite sure how well this works. You probably need some level of local knowledge to be able to interpret the colors correctly. The red-brown colored forested areas are usually deciduous broadleaved forest, in many cases beeches. Larches are more yellow in color and are often mixed with other types of trees which makes them more difficult to identify. Also the different types of trees change their colors at different times – also depending on the altitude – so a single image does not really cover everything and a solid local knowledge is probably important not to misinterpret the colors.

I would be interested in feedback about to what extent this image is useful for mapping leaf_cycle.


January 21, 2018
by chris

On permanence in IT and cartography

Many on my readers probably have heard about the company Mapzen closing down. In that context the Mapzen CEO Randy Meech has published (or more precisely: re-published) a piece on volatileness and permanence in tech business which reminded me of a subject i had intended to write about here for some time.

When i started publishing 3d geovisualizations more than ten years ago these were unique both technically and design wise. By my standards today these early works were severely limited in various ways – both due to my lack of knowledge and experience on the matter and due to the limits in quality of available data and the severe limitations of computer hardware at that time. But at the same time they were in many ways miles ahead of what everyone else was producing in this field (and in some ways still are).

An early 2006 3d Earth visualization from me

Today, more that ten years after these early works, a lot has changed in both the quality of the results and in the underlying technology. But there are also elements that stayed almost the same, in particular the use of POV-Ray as the rendering engine.

A more recent view produced in 2015

Randy in his text contemplated about the oldest companies of the world and if you’d assemble a list of the oldest end user computer programs still in use POV-Ray would be pretty far up with its roots going back to 1987. Not as old as TeX but still quite remarkable.

What makes programs like TeX or POV-Ray prevail in a world where in both cases there has been – in parallel or subsequently – a multi-billion dollar industry established in a very different direction but in a way competing for the same tasks (typesetting text and producing 3d renderings respectively)?

The answer is that they are based on ideas that are timeless and radical in some way and they are none the less specifically developed for production use.

In case of POV-Ray the timeless, radical idea was backwards raytracing in purity. There were dozens of projects following that idea mostly in the 1990s in the field of computer science research but none of them was actually seriously developed for production use. There were also dozens of both open source and proprietary rendering engines being developed for production use making use of backwards rendering techniques but all of them diluted the pure backwards rendering idea because of the attractiveness of scanline rendering centered hardware accelerated 3d as it during that time dominated the commercially important gaming and movie industries.

Because POV-Ray was the only pure backwards renderer it was also the only renderer that could do direct rendering of implicit surfaces. Ryoichi Suzuki, who implemented this by the way indicated back in 2001 that this was based on an idea originally implemented 15 years ago which makes this over 30 years old now. The POV-Ray isosurface implementation is the basis of all my 3d Earth visualizations.

In the grand scheme of overall cultural and technological development ten years or 30 years are nothing of course. Eventually POV-Ray and my 3d map design work are almost certainly destined for oblivion. And maybe also the underlying timeless, radical ideas are not as timeless as i indicated. But what you can say with certainty is that the short term commercial success is no indicator for long term viability and significance of an idea for the advancement of society.

Going more specifically into cartography and map design technology – which most of my readers are probably more familiar with – companies like Mapbox/Google/Here/Esri etc. are focused on short term solutions for their momentanous business needs – just like most businesses looking into 3d rendering in the 1990s found in scanline rendering techniques and its implementation in specialized hardware a convenient and profitable way to do the low quality 3d we all know from this era’s computer games and movies.

Hardly anyone, at least no one in a position of power, at a company like Google or Mapbox has the long term vision of a Donald Knuth or an Eduard Imhof. This is not only because they cannot attract such people to work for them but primarily because that would be extremely dangerous for the short term business success.

Mapzen has always presented itself as if it was less oriented for short term business goals than other companies and maybe it was and this contributed to its demise. But at the same time they did not have the timeless and radical ideas and the energy and vision to pursue them to create something like TeX or POV-Ray that could define them and give them a long term advantage over the big players like Google or Mapbox. What they produced were overwhelmingly products following the same short term trends as the other players do in a lemming-like fashion. Not without specific innovative ideas for sure but nothing radical that would actually make it stand out.

Mapzen published a lot of their work as open source software and this way tries to make sure it lives on after the company closes. This is no guarantee however. There are tons on open source programs dozing away in the expanses of the net no one looks at or uses any more.

While open sourcing development work is commendable and important for innovation and progress – TeX and POV-Ray as individual programs would have never lasted this long if they had not been open source – it is important to notice that the deciding factor ultimately is if there is actually

  • a substantially innovative idea being put forward,
  • this idea being consequently developed to its real potential,
  • this idea being implemented and demonstrated in practical use,
  • the idea being shared and communicated publicly and
  • the idea brings substantial cultural or technological advancement over pre-existing and near future alternatives – which unfortunately can, if at all, usually only be determined in retrospect.
waterbody and ford rendering in the alternative-colors style

December 10, 2017
by chris

Water under the bridge

When i wrote about rendering of footways/cycleways in OpenStreetMap based maps recently i indicated there are other changes i made in the alternative-colors style that deserve some more detailed explanation and here i am going to introduce some of them related to waterbody rendering.

Waterbodies in the standard style (and similarlys in nearly all other OSM based maps) have always been rendered in a relatively simple, not to say crude way. Every water related feature is drawn in the same color, water areas traditionally starting at z6, river lines at z8 and streams and smaller artificial waterways at z13. The z8 and z13 thresholds are so firmly established that mappers often decide how to tag waterways specifically to accommodate these thresholds. Since the smaller artificial waterways (ditch and drain) are rendered slightly thinner than streams these tags are frequently abused to map smaller natural waterways. The only significant styling specialty in this traditional framework is that the small waterways starting at z13 get a bright casing so they are better visible on dark backgrounds.

Some time ago a change was introduced to render intermittent waterways with a dashed line. While this seems like a logical styling decision it turned out to work rather badly because of the problems of dashed line styles in combination with detailed geometries as i already explained in context of the footway rendering.

This is the situation that forms the basis of the changes i am going to write about here.

Differentiating waterbody types

As indicated above traditionally the OSM standard style renders all water features in the same color. This color was changed some time ago but it is still one single color that is used for everything – from the ocean to the smallest streams and ditches.

This all one color scheme does not require mappers to think about how they map waterbodies specifically, they can just paint the map blue so to speak. In particular with water area tagging this has lead to a lot of arbitrariness and relatively low data quality in the more detailed, more specific information. As i pointed out in the context of waterbody data use the data cannot really be used for much else than for painting waterbodies in a uniform color. At the same time this makes life very easy for map designers of these relatively simple maps since you don’t have to worry about drawing order or other difficulties.

More specific information about waterbodies would however be very useful for data users so it makes sense to render it to encourage mappers to be more diligent with recording such information. And differentiating different types of waterbodies can help a lot creating a better readable map since what color and styling works best varies depending on the type of waterbody. And since blue color is widely reserved for water related features anyway differentiating by color is well possible.

The basic three types of waterbodies i am differentiating are:

  • the ocean
  • standing inland waterbodies (primarily lakes)
  • flowing water (both line and polygon features)

Water colors for ocean (left) standing inland water (middle) and flowing water (right)

This coloring scheme is also visible in the low zoom demo i showed recently.

Rivers use the strongest and darkest color so they are well visible even on strong and structured background while the ocean uses a brighter color not to be too dominating over land colors given that it covers a large area.

visibility of darker river color on dark background

differentiating standing and flowing water at the Rhine

In addition to differentiating by physical type of waterbody for line features i also distinguish between natural and artificial waterways in a relatively subtle form using a slightly brighter blue centerline at the higher zoom levels.

canal rendering with subtly brighter centerline

drain and stream rendering at z18 in comparison

Use of subtlety is of fundamental importance if you want to create a rich map that it still well readable. This distinction between natural and artificial waterways is strong enough to be clearly recognized by the keen observer but at the same time it is not adding a lot of noise that would affect the readability of the map otherwise.

Intermittency of waterbodies

current rendering in the standard style of intermittent rivers at z10

As indicated above the standard style already differentiates intermittent waterways but not in a very good way. I tested various options and ultimately came up with the following approach

  • intermittent waterways start one zoom level later and are slightly thinner than perennial ones at the first zoom levels.
  • at z12-z13 intermittent rivers get a bright color centerline. This is fairly well visible and works much better with detailed geometries than dashing. At z14 and above i use dashing for rivers but with very small gaps between the dashes so the line it still well visible as a continuous geometry. Streams, ditches and drains are rendered with a similar dashing from z13 upwards.
  • intermittent standing water areas get a blue grain pattern with a transparent base so underlying landcover rendering is visible.
  • intermittent flowing water areas get a bright grain pattern on a blue base starting at z14. This ensures the geometry outline is still well visible which is fairly important for readability in case of riverbanks.

intermittent waterway rendering at z13 with bright centerline for rivers and dashing for streams

intermittent riverbank polygons at z15 in combination with intermittent streams and rivers

intermittent lakes at z10

In addition for waterbodies with salt water (salt=yes) the ocean color is used in combination with a weak bright grain pattern. An abstract demo of all of these together here:

intermittent water rendering in the alternative-colors style at z14 – click to see the z15 version

Other changes

In addition to the more fundamental changes described above i also did a lot of tuning for the line widths and other rendering parameters for a more balanced relationship between the different feature types and a more continuous change in appearance when zooming in or out.


Not directly connected to the waterbody changes but still somewhat related – i added rendering of fords. These are shown in the standard style as POIs with an icon starting at z16 which is a fairly unfortunate way of rendering them because:

  • the icon covers the most interesting and most important area of the actual crossing.
  • the icon is rendered for anything that is tagged ford=yes – this can be a big highway or a small footway – or anything else for that matter where the ford tag does not make any sense.
  • z16 is way too late to be of help to the map user in many cases.

POI rendering of fords – a lot of visual noise carrying very little useful information

In other words: This kind of rendering in many situations does not really improve the map.

I used a different approach by rendering fords similar to bridges – after all a ford is a highway crossing a waterway without a bridge. The difficulty is that fords can be tagged on a node while bridges are by convention always mapped as ways. Rendering node based fords similar to bridges requires quite a bit of effort and i am afraid this significantly adds to the already complex road code. But i think the visual results make it worth it.

fords mapped as nodes for footways, tracks and minor roads

As you can see this is usually intuitively recognizable as a ford and the crossing geometry is not obscured by a big and distracting icon.

ford rendering at z15 for various highway types – click for z16 version

December 1, 2017
by chris

OSMF board elections

The OpenStreetMap Foundation tomorrow is going to open board elections for this year’s Annual General Meeting for two seats on the OSMF board. If you are a member of the OSMF i would strongly urge you to vote. If not you might want to consider becoming a member (which however will not allow you to participate in these elections – for that you have to be a member a month before the elections).

The reason why this is of particular importance this year is because this year’s candidates for the positions on the board offer in parts fairly contrasting positions on the direction on the OSMF and the OpenStreetMap project in general. You can get an idea of the ideas and views of the candidates in the Q&A on the OSM wiki but you also need to read between the lines because candidates have partly picked up the bad habit from big politics of talking much without saying anything of substance. Sometimes the way how the candidates deal with questions they do not like is more revealing than the actual answers.

Of course replacing two of seven board members will not immediately change the whole OSMF but due to the quite contrasting views and backgrounds of the candidates it will be a significant message in terms of what direction the members support and this way will probably weigh significantly also on the other board members.

Of course even a fundamental change in direction of the OSMF would not necessarily have much influence on the OpenStreetMap project as a whole. One of the most remarkable aspects of OpenStreetMap is how little it depends on central organization and management. But of course if the OSMF and the OSM community start diverging significantly in goals and direction this could create a lot of friction.

Landsat Winter Alaska 2017

November 15, 2017
by chris

Into the light

I have a somewhat different satellite image than usual here:

This is a strip of nine Landsat scenes recording parts of Alaska in early Winter from a few days back. I rotated this to align roughly with the satellite recording direction and you need to scroll down to see the whole image. As you scoll down you move from the limit of the polar night at the northern end towards the southwest and towards the sun across about 1500km.

You will notice a slight bend in the image when doing that – this is because the image coordinate system is not actually aligned to the satellite orbit but a simple oblique mercator projection. Due to the satellite’s sun synchroneous orbit however the satellite ground path is not actually a great circle but kind of spirals around the earth following the sun.

The southern end of this image strip is defined by the end of the Landsat recording which does not extend over the open ocean (it is Landsat after all). The northern end is the limit of normal Landsat recordings at this time of year due to the low sun position.

Here a Sentinel-3 OLCI image from the same day (and this time with north up orientation – also allowing you to identify where exactly the first image is placed) showing a much tighter northern limit.

And for comparison here a false color infrared Sentinel-3 SLSTR image where no recording limit is imposed showing the actual limit of light – but of course not in natural colors.

The two Sentinel-3 images also show an impressive cloud of dust extending SSW from the delta of the Copper River in southern Alaska at the right side of the image. Here a larger view to show this better.

And finally two crops from the first image – the first one from the north showing how you can watch the rivers freezing over at this time of the year near Fort Yukon.

and the second from the south showing the indeed very windy yet sunny weather at Tugidak Island in the south.

November 10, 2017
by chris

Satellite image news

Some news that might be of interest for some of my readers – without any attempt of completeness.

  • The Sentinel-2 package format has changedagain. This change is rather small and will not significantly affect most users. The interesting and funny thing however is the second time stamp saga from the previous change now seems to have gained another twist – now the second time stamp is specialised to ensure a deterministic repeatable name across time for the same product. In other words: It does not have a meaning any more, it is just there to be able to distinguish between several packages with different data but otherwise the same name (which can happen at data strip boundaries).
  • Another thing on Sentinel-2 – it has not been widely advertised but there is a data quality report on Sentinel-2 data updated in more or less regular intervals here. You need to be careful when reading this of course. Regular updates do not mean all information in that report is complete up-to-date. And you have to know how to interpret the information given. Take for example the absolute geolocation accuracy (which i have written about recently as well) – This can only be reliably measured for areas where you have accurate reference data – which does not usually include regions where accuracy tends to be bad. So the <11m at 95.5% confidence is likely not based on an unbiased set of reference locations. The reference locations are not published of course – neither is the source of the reference data used.
  • The USGS is starting to introduce what they call Landsat Analysis Ready Data. This essentially means Landsat imagery reprojected to a common coordinate system for the Unites States and distributed in tiled form. I am not going to review this data since i think this kind of product is conceptually and technically a dead end. It is by definition a regional data product they cannot extend to global coverage and performing double resampling (from the raw Level 0 data to the UTM grid of the orthorectified Level 1 product and then again to the Albers Equal Area projection of the ARD grid) is wasteful and unnecessary. There are obviously advantages for processing and using data in a common grid for larger regions but if the solution for that limits you to areas within the Unites States that is not really a universally usable approach.
  • In the field of commercial earth observation Planet Labs has launched six new SkySat satellites – those are the somewhat larger satellite systems from their acquisition of Terra Bella from Google. I briefly mentioned them in my discussion of Planet Labs some time ago. There is very little information publicly available on actual operation of these satellites. They claim a recording capacity of 185k km^2 per day for the whole fleet of 13 of these satellites. That is not much. With a recording swath width of 8km that amounts to less than 2000km recording length per day per satellite or about 20 seconds of recording per orbit. If this is to be increased in the future is unknown but at the moment it seems that these satellites – being positioned to record at different times of the day and together with a monochrome video recording ability – are mostly intended for what you might call event photography from space.
  • There are two upcoming launches of Earth observation satellites – for November 14 there is the planned launch of JPSS-1 which carries a second VIIRS instrument in addition to the one on Suomi NPP launched in 2011. And in late December there is the planned launch of GCOM-C. Both have been subject to delays – JPSS-1 was originally supposed to launch in 2016, GCOM-C in 2014.

I updated my satellite sensor chart accordingly. Note i still could not get myself to specify a full coverage interval for the PlantScope satellites. They now show a decent monthly coverage of >90 percent between -60 and 75 degrees latitude for the combination of RapidEye and PlantScope but full coverage means full coverage for me. And demo or it did not happen.

Sentinel-2 2017 coverage

November 1, 2017
by chris

Satellite image aquisitions – yearly report

About a year ago i wrote my report on the first year acquisitions of Sentinel-2 as well as for Landsat on a matching time frame. This was – and still is to my knowledge – the most detailed and accurate analysis of image data available from these satellites. Here is an update of this for a time frame from October 2016 to October 2017.

The October division is meant to include exactly one summer season of both the northern and the southern hemisphere. A calender year based division would always split the southern hemisphere summer season.

Here is the plot for the overall recording volume of all satellites:


Both Landsat satellites have operated during the last year without any notable incidents or interruptions of recordings. Landsat 7 had its last orbit maintainance maneuver in early 2017 and is now in a steadily declining orbit which means the recording time frame will move from the current about 10:15 to earlier times as it has happened for EO-1 previously.

Here are the coverage maps for Landsat 8 day time acquisitions:

The most notable difference to previous years is that Antarctic coverage was significantly reduced during the 2016-2017 summer (see the last year for comparison). You can see that in the line plot on top as a dip in the Landsat 8 line near the end of 2016 which differs significantly from the patterns of the previous years. To my knowledge there has so far not been a statement from the USGS as to why this change was made.

Otherwise not much has changed – we now get routine off-nadir acquisitions for northern Greenland and the Antarctic interior. In Greenland these always happen for the same path which means there is room for improvement by selecting the path dynamically based on weather in the target area. All 2017 northern Greenland off-nadir images are severely affected by clouds.

Also we still have the two one gap in land area coverage at lower latitudes – Rockall and Iony Island (Edit: noticed there is actually one image for Rockall – though not regular coverage. Iony Island is actually the more meaningful omission)


For Sentinel-2A we are looking at the second year of operations and this might lead to expectations of an increased level of routine and therefore reliability. We also get the first images from Sentinel-2B. Here are the numbers for Sentinel-2A and Sentinel-2B separately:

And here the combined numbers with a different color scale.

I should emphasize that these are the images publicly available. As pointed out already in a previous report there are significant differences between the published acquisition plans and the actual recordings and furthermore publication of images is frequently incomplete. Here an example from Sentinel-2B from my detailed statistics page (which i also updated to the current state).

I have not determined precise numbers but it is clear that the volume of both images planned but not recorded and recorded but not published is significant. Especially the latter, in particular in its arbitrariness shown in the image above, seems quite embarrassing.

The acquisition patterns are nearly the same as last year and also the same for Sentinel-2A and Sentinel-2B apparently. To summarize: Most of Europe and Africa as well as Greenland are recorded at every opportunity – which means a ten days intervals for each satellite, the rest of the larger land masses except Antarctica only at every second opportunity except for some seemingly arbitrary small special interest areas where also a ten days interval is recorded. Smaller islands are fully missing. Antarctica has been covered during the 2016-2017 summer but mostly at a much lower frequency than the rest of Earth.

Apart from the spatial distribution of acquisitions (which quite clearly is a conscious political choice) the most striking difference to Landsat is that high latitude acquisitions in Greenland and European Arctic islands are not reduced due to the naturally larger overlap between recording opportunities. In northern Greenland this leads during summer to frequently more than one image per day. While this can be nice for data users interested in those areas and is also kind of compensatory for the otherwise low focus on these regions it is fairly wasteful in terms of recording resources and probably results from blindly sticking to the rule record Europe and Greenland at every opportunity decided on by bureaucrats who have no clue what this actually means in practice.


So overall not that much has changed since last year – which i guess is good news for Landsat and less good news for Sentinel-2 since the latter is still subject to the same problems and limitations as last year. But maybe we just need a few more years to get used to these problems…

Apart from the problems already mentioned Sentinel-2 operations continue to be plagued by delays in data processing and other incidents. While for Landsat you can fairly reliably predict when the next image will be recorded for a certain place on earth and that it will be available a few hours afterwards for Sentinel-2 this is still much less the case.

With all the beating on Sentinel-2 problems it should however be mentioned that with two satellites now operating at a more or less constant level Sentinel-2 now usually offers a higher recording frequency than Landsat 8 (which is a practically sensible comparison since use of data from Landsat 7 is often fairly difficult due to the SLC gaps) – even in the lower priority areas – except for the small islands and Antarctica of course. In other words: if you look for the most recent image from a certain point on Earth it is more likely you find it in the Sentinel-2 archive than from Landsat 8 – despite the fact that delays in processing, missing recordings and missing publications put Sentinel-2 at a significant disadvantage.

And another positive thing about Sentinel-2 – Availability of the download infrastructure has improved a lot in the past months. Longer unscheduled downtimes where no downloads are possible at all are now fairly rare.

Here for reference all the recording visualizations for this and the previous years:

year day night day pixel coverage
2014 LS8, LS7 LS8 LS8
2015 LS8, LS7 LS8 LS8
2016 LS8, LS7 LS8 LS8, S2A
2017 LS8, LS7 LS8 LS8, S2A, S2B, S2 (both)

And also see the detailed recording patterns per orbital period and the daily recording numbers.


October 29, 2017
by chris

Islands in Spring and Autumn

A few satellite image impressions from the last weeks showing islands in spring and autumn. First a view of southwest Iceland from just a few days ago:

Then a clear weather glimpse of South Georgia in spring – with a large iceberg to the northeast:

And finally an image of Onekotan Island in the northern Kuril Islands:

The first two are based on Copernicus Sentinel-2 data, the last is created from Landsat imagery.


October 26, 2017
by chris

Drawing the lines

After doing what i had originally planned for the last OSM Hack Weekend in Karlsruhe before the actual weekend what i actually worked on there was something different – though not unrelated.

Rendering lines in a map is something that at the first glance seems the simplest thing to do but in reality there are quite a number of things that need to be considered for lines in a map to be well readable. One thing in particular is that if you render a dashed or dotted line this is much more difficult to get right than a solid line.

The OSM standard style uses dashing to differentiate tracks by tracktype and footways/cycleways by surface. This works reasonably well at the high zoom levels but it degrades to the point of being completely unreadable as you zoom out in areas with a dense network of paths. Like in these examples:

Now you can try to vary the styling like by adding bright halos, increasing contrast or varying the line width but ultimately a dashed or dotted line always makes it more difficult to identify the paths as continuous lines in areas with a lot of detail. A fundamentally different and possibly better approach would be to only draw the most important ways at these scales. But for that you’d need an assessment of importance, which is not really something you can readily find in the data and which ultimately is quite subjective and likely would not be very intuitive in many situations. Some map users for example might find it helpful if only those paths are shown that are part of a long distance trail. A local map user might on the other hand consider a different path more important because it is the shortest, easiest and most frequently used connection between two villages in the area.

One solution for tracks and paths at z13/14 i had already quickly tested some time ago is to drop the dashing and use continuous lines at these scales. This severely limits the possibilities to distinguish between different classes of paths – you can essentially only use the line width and color to differentiate and at narrow line widths it becomes more and more difficult to distinguish different colors because all pixels contain a mixture of background and line color.

One thing that prevented implementing this approach was the fact that cycleways in the standard style are traditionally rendered in blue color and a solid blue line looks just too much like a water feature intuitively. The use of blue color for cycleways has always been a sore spot but attempts to change that in the past were always hampered by the lack of other options. In particular the use of purple for boundaries creates severe limitations. Since i got rid of the purple boundaries i have some more freedom in that matter now.

Finding the right balance in colors, line widths and – at the higher zoom levels – the dashing patterns is difficult but i think the results are quite agreeable. This modification puts a stronger emphasis on footways and cycleways in the map but that in my eyes is mainly compensation for the under-representation they have in the standard style at the moment.

At z13 all lines are solid, the tracks vary in width slightly to indicate the tracktype but this variation is not large enough to reliably identify the individual track types although you can usually distinguish grade1 from grade4. Footways and cycleways are the same color (red) which can be distinguished from the track brown in nearly all situations.

(same areas in the standard style: here, here and here)

Overall the map image is much clearer and less noisy. You can better identify individual tracks and paths and their routes and connections, in particular in densely mapped areas although you loose the ability to differentiate between different types in not so densely mapped areas.

At z14 styling is very similar, the line width variation for tracks is somewhat stronger and i start using dashing for tracks without tracktype indicating to the mapper that important information is missing here.

(same areas in the standard style: here, here and here)

At z15 a white casing is added like it is also done in the standard style. Tracks are the same as in the standard style but cycleways are purple now and both cycleways and footways are stronger and differentiate clearly by surface type with long dashing for paved, short dashing for unpaved and alternating long/short for unspecified surface.

(same areas in the standard style: here and here)

I also considered differentiating out a third class of paths. The standard style some time ago removed that but this leads to the somewhat peculiar situation that highway=path + foot=designated + bicycle=designated is shown in cycleway color while highway=path without foot or bicycle tags is shown in footway color. But unfortunately mapping is often very inconsistent in this matter so this would not necessarily improve usability that much. The meaning of the colors essentially is:

  • purple: usable by bike, usually also on foot
  • red: usable on foot, maybe also by bike

At higher zoom levels the line width is slowly increased just like for tracks and the dashing is also slightly enlarged for better readability.

The style modifications for this can be found here.

I hope this description gives a tiny bit of insight into how map style design works when you systematically analyze and address problems. The actual coding is not that much work but analyzing the map rendering and identifying the problems on the one hand and adjusting and testing the various parameters, observing how the results affect the map viewing experience and how the different colors interact with each other in different geographic settings at different latitudes and resulting scales on the other hand are those things that are hard work.

In case you wonder what you can do as a mapper to allow for better readable rendering of tracks/footways/cycleways:

  • tag tracktype and surface where you know it.
  • tag access restrictions, in particular foot=* and bicycle=* as they apply.
  • although not currently rendered further information, in particular width=*, smoothness=* and sac_scale=* could be used to better differentiate rendering.

Tracks, footways and cycleways are not the only place where the standard style uses dashing and also not the only place where this leads to problems. Other situations where this leads to problems are administrative boundaries and intermittent waterways. There are already some improvement in these areas as well in the alternative-colors style. Maybe i will write about this in a future post.


October 19, 2017
by chris

New Zealand mosaic and 3d views

I here introduce a new satellite image mosaic i produced of New Zealand.

This is based on Sentinel-2 images from 2015 to 2017 and otherwise shares many of the characteristics of my previous mosaics like the high level of cloud freeness, seamless ocean depiction and assembly with priority to snow minimum and vegetation maximum.

What’s new is there is a significant improvement to the atmosphere correction methodology which i here used for the first time on a larger project. This results in a more uniform and more balanced color rendering overall. It is also the first time i produced the matching vegetation map at the Sentinel-2 resolution of 10m.

Here a few sample crops, more can be found on the mosaic description page on

I also produced a few new 3d views based on this mosaic, here two examples:

More 3d views can be found in the catalog on