Amsterdam

Circulaire Metro- en Tramkaart van Amsterdam

Dit weekend wordt de Noord-Zuidlijn geopend. Om dat te vieren, krijgen kopers van Straatkrant Z! een gratis exemplaar van de mooie circulaire Metro- en Tramkaart van Eric Hammink.

Zeven jaar geleden ontwierp Hammink de eerste versie van zijn kaart, gebaseerd op het patroon van de grachten van Amsterdam. Er was sprake van dat het GVB de kaart zou overnemen, maar daar is het blijkbaar niet van gekomen. Een gemiste kans.

De kaart wordt ook gebruikt in Hammink’s routeplanner voor de iPhone.

Circular Metro and Tram map of Amsterdam

This weekend, Amsterdam’s new North-South metro line will open. To celebrate the occasion, Straatkrant Z! offers a free copy of Eric Hammink’s beautiful circular Metro and Tram map of Amsterdam. Z! is a newspaper sold by homeless people.

Seven years ago, Hammink designed the first version of his map, modelled after the pattern of the city’s canals. At the time, there was talk about Amsterdam’s public transport company GVB adopting the map, but apparently they haven’t. A missed opportunity.

The map is also used in Hammink’s iPhone route planner app.

The orientation of Amsterdam’s streets

Eight days from now, Amsterdam will have a new metro line traversing the city from north to south. But what about the orientation of the city’s streets?

Geoff Boeing - who created a Python package for analysing street networks using data from OpenStreetMap - just published a series of polar histograms of American and ‘world’ cities. Amsterdam isn’t among them, but Boeing made his code available, so I used that to create charts for the largest cities in the Netherlands.

While the pattern isn’t nearly as monotonous as in most American cities, I’m still surprised how many streets in Amsterdam run from north to south or from east to west. The Hague has a strong diagonal orientation; Rotterdam doesn’t seem to have a dominant orientation and Utrecht is a bit in between.

With Boeing’s code, you can also do the analysis specifically for roads that are accessible to cyclists, but for Amsterdam that doesn’t make much difference since most roads are.

Discussion

15 July 2018 - There was some really interesting discussion on Twitter in response to my post from last Friday (I use Twitter names to refer to people; most sources are in Dutch).

Curved streets

Both Sanne and Egon Willighagen asked how the chart treats curved streets. I have to admit I hadn’t checked, but the docstring of the add_ege_bearings function explains that it calculates the compass bearing of edges from origin node to destination node, so that implies that streets are treated as if they were straight lines.

Is that a problem? Probably not for many US cities, for they seem to have few curved streets. As for Amsterdam: most people’s mental image of the city is probably dominated by the curved canals of the city centre. However, many neighbourhoods consist of grids of more or less straight streets. So perhaps curved streets have little impact on the analysis after all.

Length versus surface

Hans Wisbrun argues that the chart type is nice, but also deceptive. The number of streets is represented by the length of the wedges, but one may intuitively look at the surface, which increases with the square of the length. In a post from 2013 (based on a tip from Ionica Smeets), he used a chart by Florence Nightingale to discuss the problem.

Rogier Brussee agrees, but argues that a polar chart is still the right choice here, because what you want to show is the angle of streets.

In a more general sense, I think the charts are an exploratory tool that’ll give you an idea how street patterns differ between cities. If you really want to understand what the wedges represent, you’ll have to look at a map.

Beach ridges

That’s what Stephan Okhuijsen did. He noted that the chart for The Hague appears to reflect the orientation of the city’s coastline. Not quite, Christiaan Jacobs replied. The orientation of the city’s streets is not determined by the current coastline, but by the original beach ridges.

I don’t know much about geography (or about The Hague for that matter), but a bit of googling suggests Jacobs is right. See for example this map (from this detailed analysis of one of The Hague’s streets), with the old sand dunes shown in dark yellow.

See also links to previous similar work in this post by Nathan Yau (FlowingData).

Gentrificatie in kaart gebracht

De kaartmakers van de gemeente Amsterdam hebben een kaart gemaakt waarop je de Buurtstraatquote (BSQ) ziet. De BSQ speelt een centrale rol bij de hervorming van de erfpacht, waarmee het sociale grondbeleid van de gemeente wordt uitgehold - maar daar gaat dit artikel niet over. Voor nu ben ik geïnteresseerd in de BSQ als graadmeter voor grondwaarden.

Zoals de gemeente samenvat, zijn «de hoge BSQ’s te vinden in de gewilde locaties in de stad en de lage BSQ’s in de minder gewilde locaties in de stad». De grachtengordel en de omgeving van het Vondelpark hebben hoge BSQ’s; lage BSQ’s zijn te vinden zijn in Zuidoost, Nieuw-West en Noord. Dat viel te verwachten.

Interessanter is de verandering van de BSQ. De gemeente heeft cijfers beschikbaar gesteld over duizenden straten of straatsegmenten, voor de jaren 2014 en 2016. Dat is natuurlijk een korte periode en je kan er niet zomaar van uitgaan dat deze periode representatief is voor lange-termijntrends. Even goed geven de cijfers een interessant beeld.

De grafiek hieronder toont de verdeling van BSQ’s voor meergezinswoningen in 2014 en 2016.

De piek is naar rechts verschoven en de mediaan is gestegen van 28 naar 38. Om politieke redenen is bepaald dat de BSQ nooit lager dan 5 of hoger dan 49 kan zijn, wat verklaart waarom zoveel straten een BSQ van 5 of 49 hebben. Dit impliceert dat de toename van de BSQ waarschijnlijk geen volledig beeld geeft van de stijging van de grondprijzen.

Op de kaart hieronder zie je de ontwikkeling van de BSQ voor meergezinswoningen in verschillende delen van de stad. Straten waar grote veranderingen misschien geflatteerd zijn door de onder- en bovengrens van de BSQ heb ik weggelaten. Dat geldt voor straten die al in de buurt van de maximale BSQ zaten, met name de Grachtengordel en delen van Zuid. Het geldt ook voor straten, vooral in Zuidoost, waar de BSQ in de buurt van de ondergrens van 5 is gebleven.

Rood betekent dat de BSQ met tenminste de helft is toegenomen; oranje een stijging met minder dan de helft en groen dat de BSQ is gedaald. Er zijn enkele rode gebieden buiten de ring: met name IJburg, bepaalde delen van Nieuw-West en Buitenveldert. Buitenveldert grenst aan de Zuidas en heeft te maken met instroom van expats en studenten.

Binnen de ring stijgt de BSQ in gebieden die vaak worden geassocieerd met gentrificatie, zoals de Kolenkit in West, de Vogelbuurt in Noord en de Indische Buurt in Oost. Verassender is Betondorp, een buurt met lage inkomens waar veel ouderen wonen. In 2015 werd deze buurt nog omschreven als «een van de weinige wijken in Amsterdam waar de oprukkende gentrificatie nog niet heeft toegeslagen». Als de BSQ een graadmeter is, dan zou dat wel eens kunnen veranderen.

Voor methode en technische details, zie de Engelstalige versie van dit artikel.

Gentrification mapped

The map makers of the City of Amsterdam have created a map that shows the Neighbourhood Street Quota or BSQ. The BSQ plays a key role in a highly controversial reform that is eroding the city’s social ground lease policy, but that’s not the topic of this article. For now, I’m interested in the BSQ as an indicator of land value.

As the city government puts it, «the high BSQs are found at popular locations in the city and the low BSQs at less popular locations in the city» (for details see Method, below). Unsurprisingly, the centrally located Centrum and Zuid districts have high BSQs and the peripheral areas have low BSQs.

More interesting is how the BSQ has changed. The city government has provided data for thousands of streets or street segments, for 2014 and 2016. Of course, this is a short time period and the patterns may or may not reflect longer-term developments.

The chart below shows the distribution of BSQs for flats (as opposed to single-family dwellings) for 2014 and 2016.

The peak has moved to the right, as the median value has risen from 28 to 38. For political reasons, the BSQ can never be lower than 5 or higher than 49, which explains the large number of streets with a value of 5 or 49. This implies that rises in BSQ don’t fully reflect how much land values have risen.

The map below shows how much BSQs for flats have risen in different parts of Amsterdam. I omitted streets with low or high BSQs where substantial changes in BSQ may have been hidden by the upper and lower limits. At the high end, this applies to the Canal Belt and much of the Zuid District. At the lower end, this applies to many peripheral areas including almost the entire Zuidoost District.

Red streets indicate an increase of the BSQ by more than a half; orange streets an increase by less than a half and the rare green streets a decrease of the BSQ. There are some red areas outside the ring road: mainly the IJburg expansion to the east; some parts of Nieuw-West; and Buitenveldert. Buitenveldert is a neighbourhood south of the Zuidas business district with a growing number expats and students among its residents.

Within the ring road, BSQs are rising in areas that are often associated with gentrification, such as the Kolenkit in West, the Vogelbuurt in Noord and the Indische Buurt in Oost. Perhaps more surprising is Betondorp, a low-income area with many older residents, described in 2015 as «one of the few neighbourhoods in Amsterdam not yet affected by the advance of gentrification». If the BSQ is an indication, that may be about to change.

Method

A list (pdf) of BSQs for 2016 and 2014 was recently sent to the city council. The BSQs are referred to as 2018 and 2017, but are based on data from 2016 and 2014 respectively (or to be more precise: the ‘2017 BSQ’ uses data from 2015 or 2014, whichever is lowest). The map created by the City of Amsterdam uses the ‘2017 BSQ’.

For each house, the municipality calculates an individual land quota using the formula: land value / (land value + theoretical cost of rebuilding the house). The land value is obtained by subtracting the rebuilding cost from the total value of the house (WOZ).

Subsequently, BSQs are calculated as the average land quota per street (or street segment if a street traverses multiple neighbourhoods). This is done separately for single-family dwellings and flats.

The interpretation of the BSQ is a bit tricky: one should expect higher land values to be reflected in higher BSQs, but the exact relationship will depend on the value of the building and whether that also responds to changes in land value (for example, because more expensive materials are used).

In my analysis, I only used BSQs for flats, and only the streets or street segments for which a BSQ is available for both 2014 and 2016 (thus excluding new urban expansions).

For the map, I also excluded streets where an increase of the BSQ by less than half may be hidden by the lower or upper limit of the BSQ: those with a 2014 value of 5 and a 2016 value of less than 8; and those with a 2014 value above 32 and a 2016 value of 49.

In creating the map I also ignored long streets that traverse multiple neighbourhoods and that therefore have been separated into multiple segments. Constructing street segments from line geometries representing the entire street seemed like a lot of work (perhaps there’s a simple way to do this, but I couldn’t find it).

I used Tabula to extract data from the original pdf; this Python script to process the data, create a csv for the chart and create a shapefile for the map; D3.js for the chart and Qgis to create the map (using Open Street Map map data and Stamen Toner Lite for the background).

Pages