Now that I know how to
a map overlay for OsmAnd, I wanted a land ownership overlay.
When we're hiking, we often wonder whether we're on Forest Service,
BLM, or NPS land, or private land, or Indian land. It's not easy to tell.
Finding Land Ownership Data
The first trick was finding the data. The New Mexico State Land Office has an
New Mexico Land Status map, but that's no help when walking
around, and their downloadable GIS files only cover the lands
administered by the state land office, which mostly doesn't include
any areas where we hike. They do have some detailed
PDF maps of
New Mexico Lands if you have a printer capable of printing
enormous pages, which most of us don't.
In theory I could download their 11" x 17" Land Status PDF, convert it
to a raster file, and georeference it as I described in the earlier
article; but since they obviously have the GIS data (used for the
interactive map) I'd much rather download the data and save myself
all that extra work.
Eventually I found New Mexico ownership data at
UNM's RGIS page, which has
an excellent collection of GIS data available for download. Click
on Boundaries, then download Surface Land Ownership.
It's available in a variety of formats; I chose the geojson format
because I find it the most readable and the easiest to parse with
Python, though ESRI shapefiles arguably might have been easier in QGIS.
Colorizing Polygons in QGIS
You can run qgis on a geojson file directly. When it loads it shows the
boundaries, and you can use the Info tool to click on a polygon and
see its metadata -- ownership might be BLM, DOE, FS, I, or whatever.
But they're all the same color, so it's hard to get a sense of land
ownership just clicking around.
To colorize the polygons differently, right-click on the layer name and
choose Properties. For Style, choose Categorized.
For Column, pick the attribute you want to use to choose colors:
for this dataset, it's "own", for ownership.
Color ramp is initially set to random.
Click Classify to generate an initial color ramp, then
click Apply to see what it looks like on the map.
Then you can customize the colors by doubleclicking on specific color
swatches. For instance, by unstated convention most maps show Forest
Service land as green, BLM and Indian land as various shades of brown.
Click Apply as you change colors, until you're happy with the
Exporting to GeoTIFF
You can export the colored layer to GeoTIFF using QGIS' confusing
and poorly documented
Create one with: Project > New Print Composer,
which will open with a blank white canvas.
Zoom and pan in the QGIS window so the full extent of the image you
want to export is visible. Then, in the Print Composer,
Layout > Add Map. Click and drag in the blank canvas,
going from one corner to the opposite corner, and some portion of
the map should appear.
There doesn't seem to be any way to Print Composer to import your
whole map automatically, or for you to control what portion of the map
from the QGIS window will show up in the Print Composer when you drag.
If you guess wrong and don't get all of your map, hit Delete, switch
to the QGIS window and drag and/or zoom your map a little, then switch
back to Print Composer and try adding it again.
You can also make adjustments by changing the Extents in
the Item Properties tab, and clicking the Set to map canvas
extent button in that tab will enlarge your extents to cover
approximately what's currently showing in the QGIS window.
It's a fiddly process and there's not much control, but when you
decide it's close enough, Composer > Export as Image... and
choose TIFF format. (Print Composer offers both TIFF and TIF; I don't
know if there's a difference. I only tried TIFF with two effs.) That
should write a GeoTIFF format; to verify that, go to a terminal and
run gdalinfo on the saved TIFF file and make sure it says it's
Load into OsmAnd
Finally, load the image into OsmAnd's tiles folder as discussed in the
then bring up the Configure map menu and enable the overlay.
I found that the black lines dividing the various pieces of land are
a bit thicker than I'd like. You can't get that super accurate "I'm
standing with one foot in USFS land and the other foot in BLM land"
feeling because of the thick black DMZ dividing them. But that's
probably just as well: I suspect the data doesn't have pinpoint
accuracy either. I'm sure there's a way to reduce the thickness of
the black line or eliminate it entirely, but for now, I'm happy with
what I have.
[ 18:13 Apr 15, 2019
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For many years I've wished I could take a raster map image, like a
geology map, an old historical map, or a trail map, and overlay it
onto the map shown in OsmAnd
so I can use it on my phone while walking around.
I've tried many times, but there are so many steps and I never
found a method that worked.
Last week, the ever helpful Bart Eisenberg posted to the OsmAnd list
a video he'd made:
web-based maps with MAPC2MAPC: OsmAnd Maps & Navigation.
Bart makes great videos ... but in this case, MAPC2MAPC
turned out to be a Windows program so it's no help to a Linux user.
But seeing his steps laid out inspired me to try again, and gave me
some useful terms for web searching. And this time I finally succeeded.
I was also helped by a post to the OsmAnd list by A Thompson,
How to get aerial image into offline use?,
though I needed to change a few of the steps.
(Note: click on any of the screenshots here to see a larger version.)
Georeference the Image Using QGIS
The first step is to georeference the image: turn the plain raster image
into a GeoTiff that has references showing where on Earth its corners are.
It turns out there's an open source program that can do that, QGIS.
Although it's poorly documented,
it's fairly easy once you figure out the trick.
I started with the tutorial
but it omits one important point, which I finally found in BBRHUFT's
to Georeference a map in QGIS. Step 11 is the key: the Coordinate
Reference System (CRS) must be the same in the georeferencing window
as it is in the main QGIS window. That sounds like a no-brainer, but
in practice, the lists of possible CRSes shown in the two windows
don't overlap, so unless you follow BBRHUFT's advice and
type 3857 into the filter box in both windows, you'll likely
end up with CRSes that don't match. It'll look like it's working, but
the resulting GeoTiff will have coordinates nowhere near where they
Instead, follow BBRHUFT's advice and type 3857 into the filter
box in both windows. The "WGS 84 / Pseudo Mercator" CRS will show up
and you can use it in both places. Then the GeoTiff will come out in
the right place.
If you're starting from a PDF, you may need to convert it to a raster format
like PNG or JPG first. GIMP can do that.
So, the full QGIS steps are:
Start qgis, and bring up Project > Project Properties.
- Click on CRS, type 3857 in the filter box,
and make sure the CRS is set to WGS 84 / Pseudo Mercator.
- (optional) While you're in Project Properties, you may want to
click on General and set
Display Coordinates Using: Decimal degrees.
By default qgis always uses "meters" (measured from where?)
which seems like a bizarre and un-useful default.
- In Plugins > Manage and Install Plugins...,
install two plugins: Quick Map Services and
- Back in the main QGIS window, go to Web > QuickMapServices
(that's one of the plugins you just installed) and pick
a background map, probably something from OpenStreetMap.
Once you find one that loads, navigate to the area you're
(All the OpenStreetMap tile sets print "API Key Required" all over
everything. You can get an API key from Thunderforest -- I use one
for PyTopo -- but it won't help you here, because nobody seems to
know how to get QGIS to use an API key, though I found dozens of
threads with people asking. If you find a way, let me know.)
Start the georeferencer:
Raster > Georeferencer > Georeferencer....
It may prompt you for a CRS; if so, choose WGS 84 / Pseudo Mercator
if it's available, and if it's not, type 3857 in the filter box
to find it.
- In the Georeferencer window, File > Open Raster...
- Select matching points. This part is time consuming but fun.
Zoom in to your raster map in the Georeferencer window and pick a
point that's easy to identify: ideally the intersection of two
roads, or a place where a road crosses a river, or similar
identifying features. Make sure you can identify the same point
in both the Georeferencer window and the main QGIS window
(see the yellow arrows in the diagram).
Click on the point in the Georeferencer window, then click "from
- In the main QGIS window, click on the corresponding point.
You can zoom with the mousewheel and pan by middle mouse dragging.
Repeat for a total of four to eight points.
You'll see yellow boxes pop up in both windows showing the matching points.
If you don't, there's something wrong; probably your CRSes don't
In the Georeferencer window, call up
Settings > Transformation Settings.
Choose a Transformation type (most people seem to like Thin Plate Spline),
a Resampling method (Lanczos is good), a target SRS (make sure it's
3857 WGS 84 / Pseudo Mercator to match the main window).
Set Output raster to your desired filename, ending in .tiff.
Be sure to check the "Load in QGIS when done" box at the bottom.
- File > Start Georeferencing. It's quite fast, and will
create your .tiff file when it's finished, and should load the TIFF
as a new layer in the main QGIS window.
Check it and make sure it seems to be lined up properly with
geographic features. If you need to you can right-click on the layer
and adjust its transparency.
In the Georeferencer window, File > Save GCP Points as...
in case you want to go back and do this again. Now you can close
the Georeferencer window.
- Project > Save to save the QGIS project, so if you want
to try again you don't have to repeat all the steps.
Now you can close qgis. Whew!
Convert the GeoTiff to Map Tiles
The ultimate goal is to convert to OsmAnd's sqlite format, but there's
no way to get there directly. First you have to convert it to map tiles
in a format called mbtiles.
QGIS has a plug-in called QTiles but it didn't work for me: it briefly
displayed a progress bar which then disappeared without creating any files.
Fortunately, you can do the conversion much more easily with
gdal_translate, which at least on Debian is part of
the gdal-bin package.
gdal_translate filename.tiff filename.mbtiles
That will create tiles for a limited range of zoom levels (maybe only
one zoom level). gdalinfo will tell you the zoom levels in the
file. If you want to be able to zoom out and still see your overlay,
you might want to add wider zoom levels, which you can do like this:
gdaladdo -r nearest filename.mbtiles 2 4 8 16
Incidentally, gdal can also create a directory of tiles suitable for
a web slippy map, though you don't need that for OsmAnd. For that,
use gdal2tiles, which on Debian is part of
the python-gdal package:
gdal2tiles filename.tiff tiles
Not only does it create tiles, it also includes multiple HTML files
you can use to display those tiles using the Leaflet, OpenLayers or
Create the OsmAnd sqlite file
Tarwirdur has written a nice simple Python script to translate from
mbtiles to OsmAnd sqlite:
Download it then run
mbtiles2osmand.py filename.mbtiles filename.sqlitedb
So easy to use! Most of the other references I saw said to use
Mobile Atlas Creator (MOBAC)
and that looked a lot more complicated.
Incidentally, Bart's video says MAPC2MAPC calls the format
"Locus/Rmaps/Galileo/OSMAND (sqlite)", which might be useful to know
for web search purposes.
Install in OsmAnd
Once you have the .sqlitedb file, copy it to OsmAnd's tiles folder
in whatever way you prefer. For me, that's
adb push file.sqlitedb $androidSD/Android/data/net.osmand.plus/files/tiles
where $androidSD is the /storage/whatever location of
my device's SD card.
Then start OsmAnd and tap on the icon in the upper left for your current mode
(car, bike, walking etc.) to bring up the Configure map menu.
Scroll down to Overlay or Underlay map, enable one of
those two and you should be able to choose your newly installed map.
You can adjust the overlay's transparency with a slider that's visible
at the bottom of the map (the blue slider just above the distance scale),
so you can see your overlay and the main map at the same time.
The overlay disappears if you zoom out too far, and I haven't yet figured
out what controls that; I'm still working on those details.
Sure, this process is a lot of work. But the result is worth it.
Check out the geologic layers we walked through on a portion of
a recent hike in Rendija Canyon (our hike is the purple path).
[ 19:08 Apr 10, 2019
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