Mouse Coordinates To Lat/Long

This post is long overdue – a number of people have asked me how to convert between lat/long and mouse coordinates on an HTML page. First, let’s define some terms since otherwise it is easy to get confused:

  • Geodetic coordinate system- A geodetic coordinate system based on the WGS84 datum.
  • World coordinate system – The projected coordinate system – for example, the Mercator projection used by Google.
  • Document coordinate system – The browsers coordinate system, units are in pixels.
  • View coordinate system – The coordinate system of the HTML element, such as a div tag, that contains the map. Units are in pixels.

Since writing out coordinate system gets tedious pretty quickly, I’ll abbreviate it as CS.

A Series of Transformations

Transformations are used to convert coordinates between different coordinate systems. There are two types of transformations commonly used in mapping.

The first is projection transformations which convert to and from a geodetic CS to a projected CS like Mercator or UTM. Projection transformations are often non-linear and require fairly complex math.

The second is affine tranformations. Affine transformations are used to translate (i.e., move), scale, rotate and skew features. Affine transformations are linear and are used by all drawing programs and are often used in games (pick up any book about math for game developers to learn more about affine transformations). They are easy to implement using linear algebra.

So back to the problem at hand. To get from a lat/long value to a pixel value requires a series of transformations:

  1. Geodetic CS -> World CS (projection)
  2. World CS -> View CS (affine)
  3. View CS -> Document CS (affine)

We’ve already know how to transform a point between the Geodetic CS and World CS. And step 3 is easy. But how do we do step #2?

Its done like this:

  1. Translate the world CS center to 0,0
  2. Rotate the map if needed
  3. Scale the map to the view CS
  4. Translate from 0,0 in the view CS to the center of the view CS.

Why the translation to 0,0 first? The image below from O’Reilly’s SVG Essentials book shows the problem. The small rectangle’s top left is at 5,5. Now let’s scale the rectangle by a factor of 2 to make the bigger rectangle. Note that the new rectangle is not only larger, its top left corner has also shifted to 10,10.


Image courtesy of O’Reilly (taken from SVG Essentials)

In addition, if you want to rotate the map, you want it to rotate around the center of the map not the current 0,0 position.

Scale Factor

Assuming you don’t want to rotate the map, the next step is to scale the world CS to the view CS. How do we determine the scaling factor? This is done by introducing another concept, unit size.

The unit size is the physical world distance in centimeters (you can use any unit system you like) represented by one unit of a coordinate system. For the view CS, it is the number of centimeters on the ground represented by one pixel. For the world CS, it is the number of centimeters on the ground represented by one world CS unit (which could be inches or meters or kilometers, etc.). Here is some pseudo code:

// How many centimeters in the physical world does one pixel cover?
var elementUnitDistance = (1/scale) * (1/PIXELS_PER_CM)

// How many centimeters in the physical world does one world unit cover?
var displayUnitDistance = worldCS.getDisplayUnitSize()

var scalingFactor = elementUnitDistance/displayUnitDistance

We make an assumption that there are 72 pixels per inch – to calculate pixels per centimeter divide by 2.54. Note that this assumption will always be off to some degree. If you are using SVG, it provides an API that will return the exact number.

For Google’s Mercator projection, we can figure the unit size like this:

// What is the circumference of the earth at the current latitude in cm?
var latRadians = Math.degreesToRadians(lat)
var circumference = 2 * Math.PI * (Math.cos(latRadians) * EARTH_RADIUS_IN_CM) 

// What is the circumference of the earth in worldCS units?
var worldDistance = 2 * Math.PI * mercator_cs_radius

// Calculate the unit size
var unitSize = earthDistance/worldDistance

Note that Math.degreesToRadians is a custom extension to Javascript’s Math object.

As I discussed previously, the scaling factor for Google Maps is always 1. Why is that? Because the Google Mercator projection is also in pixels, so obviously one pixel equals one pixel. The biggest advantage of doing this is that Google can pre-render map tiles to greatly improve performance. It also avoids having to pick a value for pixels per inch. The disadvantage is that you cannot zoom to an arbritrary scale on a map – you can only go to Google’s predefined zoom levels.

If you use other projections, or other GIS systems, then you’ll have to calculate the scaling factor.

An Example

Let’s work through an example. We want to render a map centered on the Colorado State Capital building in downtown Denver at Google’s zoom level 16 (which means a preset scale of 1/5206.6). The map should be shown in a div tag which is 500 pixels wide and 500 pixels high. The top left of the div tag is located at 100,100 in the document CS.

The longitude/latitude of the Colorado state capital is -104.985 and 39.739 (I picked these values off a map so the may be a bit inaccurate). From what we learned before, we can quickly calculate this to be an x value of 3495974 and a y value of 6367308 in Google’s Mercator projection for zoom level 16.

So, what is the latitude and longitude of the top left of the div tag? We just reverse the steps described above.

// starting point in document CS
var x = 100
var y = 100

// Convert from document CS to view CS
x = x - 100
y = y - 100

// Translate view CS center to 0,0
x = x - 250
y = y - 250

// Scale from view CS to document CS
var viewScale = 1 // always for Google
x = x * viewScale
y = y * viewScale

// Translate 0,0 in world CS to world CS center
x = x + 3495974
y = y + 6367308

// Convert from world CS to geodetic CS
var long = convertMercatorToWGS84Long(x)
var lat = convertMercatorToWGS84(y)

// answer is:
// long = -104.99
// lat = 39.74