Now that we have the boundaries, we can calculate the coordinates on the image. For Germany, we have to set $swap_y to true. With the two “swap” flags, you can indicate that the coordinates are on opposite sites of 0° latitude or 0° longitude, so the maximum value would be used for the left boundary for example and the minimum for the right boundary. 'ymax' => $swap_y ? min( $dst_points_y ) : max( $dst_points_y ), 'ymin' => $swap_y ? max( $dst_points_y ) : min( $dst_points_y ), 'xmax' => $swap_x ? min( $dst_points_x ) : max( $dst_points_x ), 'xmin' => $swap_x ? max( $dst_points_x ) : min( $dst_points_x ), $dst_point = $proj->transform( $dst_projection, $src_point ) $src_point = new Point( $point, $point, $src_projection )
#Image convert between map projections code#
Fortunately for the amCharts map, they have it in the source code of the SVG itself:
With these points, we then use the min/max values for the latitude and longitude. So for the map of Germany, we would need to find the places all the way in the North, East, South and West. But if you don’t have such data or don’t know where to find them, you can just try to get a GPS coordinate for the points on the edges. You can probably find those boundaries on with a search engine or use an open API like the one from OpenStreetMaps and other services. Unfortunately for the map from Wikipedia there are no such coordinates given. If we are lucky, we would get the coordinates of these points from the provider of the map. Now we need to get the min and max coordinates on the map. But how would you use them now? If we want to put them on the SVG map, we have to calculate the pixel coordinates on that image. $dst_berlin = $proj->transform( $dst_projection, $src_berlin ) Īll right, we have some new numbers now.
#Image convert between map projections free#
That’s why, for this blog post, I have chosen the free SVG map from amCharts: Unfortunately, it uses a different projection system. We can find a nice map of Germany with borders to all states. Wikipedia is usually a good source, and maps are usually released using a Creative Commons license. You can find them on different platforms. This can be anything, an aerial photo, a satellite image or an image. So now that we have talked a bit about the theory, let’s talk about code. But as it’s easier to make calculations with numbers, the first format is easier to continue with. You might also have seen a location in degrees, minutes and seconds like 52° 30' 58.59" (latitude) and 13° 22' 39.7338" (longitude). You might have seen coordinates like this before. For the Brandenburg Gate in Berlin this might be around 52.5162746 (latitude) and 13.3777041 (longitude). When giving the position of a place on earth, you usually use the World Geodetic System 1984 (WGS 84) with the latitude and longitude values for a specific place.
It’s also referred to by identifier EPSG:3857, which we will need a little later. One of the most common ones is the Mercator projection which is used by Google Maps, Bing Maps, OpenStreetMap and many other services.
As our monitors are flat (and before that paper maps), there are man different “ map projections“. Map projectionsĮven though some people believe the earth is flat, the earth is round. I did that manually in the past, but as the maps has grown to 100 markers, I was looking for a way to do that programmatically. For a project, I recently had to add markers of cities to a map of Germany. This blog post will be a start of a little post series.
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