The new look of Google Maps

Hot on the heels of our new style for the Google Maps user interface, today we are pushing out some further improvements to our map design to match the updated look and feel and further improve the usability of our maps.

Amongst the changes you will find a plethora of subtle changes, designed to make the map cleaner, more focused, more visually harmonious, and easier to use. Some highlights to look out for are a brighter and more cheerful color palette, a more integrated and less visually noisy labeling style, subtle improvements to footpaths and minor roads, and cleaner building and land parcel rendering.

Most of these improvements, like many that we’ve made over the last couple of years, are gentle enough that many people won’t even notice the difference. When you add them together, however, and then compare to how the map looked even as recently as two years ago, it’s remarkable to see how dramatic the change is.

Compare how our maps of New York looked in 2009, then again the same time in 2010, and now with the new tiles for 2011. The improved colour scheme and less jarring label outlines help the labels to feel part of the map, as opposed to a distracting overlay. It’s also easier to distinguish the city name, neighborhoods, and roads through subtle changes in label color:

The visually heavy highway shields are now integrated into the road labels, and the brighter and cleaner style shifts the focus onto the road names and prominent landmarks in the area. London is one place that benefits from this:

The style evolution has enabled us to place more information whilst still making the map feel simpler. In the case of Sydney, thinner and cleaner roads, better representation of tunnels, more subtle footpaths in the parks, and more subtle labeling all contribute:

We hope you enjoyed this quick retrospective and find the new improvements to the map style helpful. There are many more than have been highlighted here, so have a look around Google Maps today and see if you can spot any improvements to your local area.

SQL Server: Easy Bulk Loading OS Locator Road Data

I’ve just loaded the Ordnance Survey “OS Locator” dataset (part of Ordnance Survey Open Data) into SQL Server 2008. OS Locator contains details of all the roads in Britain, in a gazetteer-style format. It is a 120Mb delimited text file, containing details of around 790,000 road entities (some roads are split into multiple entities if they cross districts etc.) – including the road name, the coordinates of its bounding box and centrepoint, classification, and the county and area in which it is located. (Note that this dataset doesn’t include the geometry of the shape of the road itself). You can find the technical specifications for the OS Locator dataset here:

Since the file is text-based, there’s a range of options available to import it – you could create an SSIS package, or use the import/export wizard, or one of a variety of third party ETL tools. However, for an absolutely dead-easy way to query the data and create a geometry point representing the centre of each road using purely T-SQL, I used the OPENROWSET bulk function in conjunction with a format file.

Not only is this method easy, but it’s utterly repeatable so (assuming the structure of the source data remains constant) you can run it again each time the underlying data gets refreshed. OPENROWSET allows you to query the text file source directly, as if it were a table in the database, from which you can SELECT columns of data, INSERT them into other tables etc.

The following shows the xml format file I used to specify the columns of data in the OS Locator file:

[php]<?xml version="1.0"?>
<BCPFORMAT xmlns="" xmlns:xsi="">
<FIELD ID="0" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="1" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="2" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="3" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="4" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="5" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="6" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="7" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="8" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="9" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="10" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="11" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="12" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="13" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="14" xsi:type="CharTerm" TERMINATOR=":"/>
<FIELD ID="15" xsi:type="CharTerm" TERMINATOR="\r\n"/>
<COLUMN SOURCE="1" NAME="Classification" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="2" NAME="Centx" xsi:type="SQLINT"/>
<COLUMN SOURCE="3" NAME="Centy" xsi:type="SQLINT"/>
<COLUMN SOURCE="4" NAME="Minx" xsi:type="SQLINT"/>
<COLUMN SOURCE="5" NAME="Maxx" xsi:type="SQLINT"/>
<COLUMN SOURCE="6" NAME="Miny" xsi:type="SQLINT"/>
<COLUMN SOURCE="7" NAME="Maxy" xsi:type="SQLINT"/>
<COLUMN SOURCE="8" NAME="PostSector" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="9" NAME="Settlement" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="10" NAME="Locality" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="11" NAME="Cou_Unit" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="12" NAME="LocalAuth" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="13" NAME="Tile_10k" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="14" NAME="Tile_25k" xsi:type="SQLVARYCHAR"/>
<COLUMN SOURCE="15" NAME="Source" xsi:type="SQLVARYCHAR"/>

Assuming that the format file above is saved as c:OSLocator_formatfile.xml, and the OS Locator download itself is saved as c:OS_Locator2010_2_Open.txt (the filename of the most recent locator download at the time of writing), then you can load the Locator dataset directly in SQL Server, creating a geometry point at the centre of each road in a single query as follows:

[php]SELECT *,
geometry::Point(Centx,Centy,27700) AS Centre
BULK ‘C:OS_Locator2010_2_Open.txt’,
) AS CSV;[/php]

And here’s what the data looks like:


Here’s the spatial results tab displaying the centre points of the first 5,000 rows of data:


And here’s what a small section of Norwich looks like having created a bounding box from the min/max coordinates of each road and overlaying them on Bing Maps (having first transformed the coordinates from EPSG:27700 to EPSG:4326):