The previous two posts (one,two) have been on Mobile Atlas Creator (MOBAC), a program that can download map data from online services, and convert it into offline formats compatible with some Android map apps. But MOBAC can’t process your own scanned maps, or digital maps / aerial photographs you’ve downloaded off the web.To do that, there’s MAPC2MAPC, a free image conversion program (Windows only) that can turn stand-alone digital map images into several Android-app-compatible formats. Note: The latest version of MAPC2MAPC is no longer free; you might still be able to find the older free version on the web if you search a bit. But to fully understand how to use it, you’ll need to know some basics about how digital map images are calibrated, i.e. how do you know which geographic coordinates are associated with each individual pixel element in the image.
Broadly speaking, digital map images can come in one of two formats:
– Uncalibrated. Just a basic digital image with no information about which geographic coordinates go with which pixel.
– Calibrated (aka “georeferenced” or “registered”). A digital image that comes with basic geographic coordinate calibration data, either embedded in the image file itself, or in a separate file, often plain text, that can be loaded in with the image to tell the program what location each pixel is at.
For both kinds of maps, you’ll also need to know two more pieces of information that describe how the maps was drawn:
– The map’s “projection”. Maps are flat representations of the earth’s curved surface, and the projection describes geometrically both how they are flattened (in a manner usually designed to minimize distortions from the flattening process) and also the coordinate system that assigns a set of numbers to every point. Examples of projections include Universal Transverse Mercator (UTM) (which uses meters for coordinate units), Lambert Conformal Conic (also meters), and equirectangular/Plate Carree (which uses meters).
– The map’s “datum”. A datum is a set of equations that describes both the curvature of the Earth, and also the zero-zero reference point for coordinate systems. As technology has improved, the accuracy of the datum has also improved, which means that positions given in older datums may be a long distance away from the same position in a modern datum. Examples of datums include WGS84, NAD27, and ED50.
Uncalibrated maps will, by definition, lack embedded information about the projection and datum used to draw the map. MAPC2MAPC has a calibration utility that lets you calibrate the map for a limited number of projections (and a larger number of datums); this will also assign geographic coordinates to every pixel. If your map was created with one of those projections, you should use that one to calibrate your map; you will commonly find the projection and datum printed somewhere on the map, often at the bottom near the map title and scale. If the projection is not defined for your uncalibrated map, or it’s drawn in an oddball calibration, using/choosing the wrong projection can result in a distorted and miscalibrated map. MAPC2MAPC includes utilities for this that requires more calibration points, but can “warp” the map into an acceptable shape. One of those utilities lets you select points in Google Earth, and use those for the calibration process. Check the readme.txt file that comes with the MAPC2MAPC program for more info on these functions. There are also a fair number of free programs that can geographically calibrate an uncalibrated image (“georeferencing”); you can find a list of them here.
For many uncalibrated map images, though, the easiest way to calibrate the map for use in MAPC2MAPC might be to create a Google Earth image overlay file in KMZ format, then load it into the program. MAPC2MAPC accepts these KMZ files as input, and if created successfully, they’re already fully calibrated in the equirectangular/Plate Carree projection, WGS84 datum. You will likely find that most maps can be calibrated reasonably well using this process, although not all. Check out this tutorial by Garmin on the process for creating a KMZ image overlay (note: unlike images destined for Garmin units, it doesn’t have to be in JPG format, and it can be up to 100 million pixels in size). You might also check out this YouTube video tutorial and associated linked tutorials on the right of the video’s page.
For calibrated maps, the geographic coordinate data will always be included somehow in a calibration file. For some types of calibrated maps, the projection/datum information will be included in the calibration file, while for others, you’ll have to specify it. If full projection/datum data is needed for any calibration file, it will be requested by the program. Types of calibrated map files accepted by MAPC2MAPC include:
- World files (.tfw, pgw, jgw); these always require projection and datum information
- OziExplorer .map files; these usually have projection/datum information embedded within them
- Google Earth overlay files (KMZ); these are implicitly in a known projection/datum
- … and a bunch of less common ones(e.g. gux, gmi, jpr, etc). Not fully familiar with these formats, but I believe some of them have full calibration/projection/datum data, while others only have calibration data.
The MAPC2MAPC website has PDF documentation of how to load a calibration file for a USGS topo map with a tfw world file obtained from a site like LibreMap; by following this, you’ll get a feeling for how to load similar calibration files.
Tomorrow: Some sources for calibrated maps and aerial imagery, and a walkthrough on downloading and converting a calibrated aerial photo into an Android-app-ready map with MAPC2MAPC.