Shallow Thoughts : tags : osmand

Akkana's Musings on Open Source Computing and Technology, Science, and Nature.

Wed, 03 Apr 2024

Making OsmAnd Overlays with QGIS (2024 Edition)

Several years ago I wrote about Making a Land Ownership Overlay with QGIS and Making Overlay Maps for OsmAnd. I've been using that land use overlay for years. But recently I needed to make several more overlays: land ownership for Utah for a hiking trip, one for the eclipse, and I wanted to refresh my New Mexico land ownership overlay since it was several years out of date. It turns out some things have changed, so here's an update, starting from the point where your intended overlay is loaded as a layer in QGIS.

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[ 18:15 Apr 03, 2024    More mapping | permalink to this entry | ]

Fri, 07 Jan 2022

Editing GPX Track Files from OsmAnd in a Text Editor

I record track files in OsmAnd for most of my hikes. But about a quarter of the time, when I get back to the car, I forget to turn tracking off. So I end up with a track file that shows the hike plus at least part of the car trip afterward. Not very useful for purposes like calculating mileage.

My PyTopo can do simple track edits, like splitting the track into two or deleting from some point to the end. But most of the time it's easier just to edit the GPX file with a text editor.

Eesh, edit GPX directly?? Sounds like something you oughtn't do, doesn't it? But actually, GPX (a form of XML) is human readable and editable. And this specific case, separating the walking from the car trip in an OsmAnd track file, is particularly easy, because OsmAnd helpfully adds a speed to every point it saves.

These instructions seem long, but really, once you've done it once, you'll realize that it's all very straightforward; explaining the steps is harder than doing them.

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[ 14:13 Jan 07, 2022    More mapping | permalink to this entry | ]

Mon, 15 Apr 2019

Making a Land Ownership overlay: Categorized Styles in QGIS

Now that I know how to make 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 interactive 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.

[QGIS categorized layers] 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 result.

Exporting to GeoTIFF

Update: In 2024, some of these steps have changed; see Making OsmAnd Overlays with QGIS (2024 Edition).

You can export the colored layer to GeoTIFF using QGIS' confusing and poorly documented Print Composer. 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 GeoTIFF.

Load into OsmAnd

[Land ownership overlay in OsmAnd] Finally, load the image into OsmAnd's tiles folder as discussed in the previous article, 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.

Update: Here's another, easier, way to show land use on OsmAnd using overlay tiles from the BLM (in the US): Adding BLM Land Use Maps to Osmand on Android. It isn't as general (you can only show something you can get from an online tiled source) and it updates in real-time, meaning it might use cellphone data rather than working entirely offline, but it's still a great option to know about.

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[ 18:13 Apr 15, 2019    More mapping | permalink to this entry | ]

Wed, 10 Apr 2019

Making Overlay Maps for OsmAnd on Linux

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: Displaying 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. Darn!

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

Update in Feb 2024: Several things have changed in QGIS georeferencing (the version I'm using now is 3.28.15-Firenze), so note the updated sections below.

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 Georeferencing Basics, but it omits one important point, which I finally found in BBRHUFT's How 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 should be

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:


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: 

mkdir tiles
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 Google Maps JavaScript libraries. Very cool!

Create the OsmAnd sqlite file

Tarwirdur has written a nice simple Python script to translate from mbtiles to OsmAnd sqlite: mbtiles2osmand.py. 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

[Georeferenced map overlay 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).

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[ 19:08 Apr 10, 2019    More mapping | permalink to this entry | ]

Sun, 14 Aug 2016

Translating track files between mapping formats

I use map tracks quite a bit. On my Android phone, I use OsmAnd, an excellent open-source mapping tool that can download map data generated from free OpenStreetMap, then display the maps offline, so I can use them in places where there's no cellphone signal (like nearly any hiking trail). At my computer, I never found a decent open-source mapping program, so I wrote my own, PyTopo, which downloads tiles from OpenStreetMap.

In OsmAnd, I record tracks from all my hikes, upload the GPX files, and view them in PyTopo. But it's nice to go the other way, too, and take tracks or waypoints from other people or from the web and view them in my own mapping programs, or use them to find them when hiking.

Translating between KML, KMZ and GPX

Both OsmAnd and PyTopo can show Garmin track files in the GPX format. PyTopo can also show KML and KMZ files, Google's more complicated mapping format, but OsmAnd can't. A lot of track files are distributed in Google formats, and I find I have to translate them fairly often -- for instance, lists of trails or lists of waypoints on a new hike I plan to do may be distributed as KML or KMZ.

The command-line gpsbabel program does a fine job translating KML to GPX. But I find its syntax hard to remember, so I wrote a shell alias: 

kml2gpx () {
        gpsbabel -i kml -f $1 -o gpx -F $1:t:r.gpx
}
so I can just type kml2gpx file.kml and it will create a file.gpx for me.

More often, people distribute KMZ files, because they're smaller. They're just gzipped KML files, so use "zip" and "unzip" to unpack them. In Python you can use the zipfile module.

(Updated to reflect that it's zip, not gzip.)

Of course, if you ever have a need to go from GPX to KML, you can reverse the gpsbabel arguments appropriately; and if you need KMZ, run zip afterward.

UTM coordinates

A couple of people I know use a different format, called UTM, which stands for Universal Transverse Mercator, for waypoints, and there are some secret lists of interesting local features passed around in that format.

It's a strange system. Instead of using latitude and longitude like most world mapping coordinate systems, UTM breaks the world into 60 longitudinal zones. UTM coordinates don't usually specify their zone (at least, none of the ones I've been given ever have), so if someone gives you a UTM coordinate, you need to know what zone you're in before you can translate it to a latitude and longitude. Then a pair of UTM coordinates specifies easting, and northing which tells you where you are inside the zone. Wikipedia has a map of UTM zones.

Note that UTM isn't a file format: it's just a way of specifying two (really three, if you count the zone) coordinates. So if you're given a list of UTM coordinate pairs, gpsbabel doesn't have a ready-made way to translate them into a GPX file. Fortunately, it allows a "universal CSV" (comma separated values) format, where the first line specifies which field goes where. So you can define a UTM UniCSV format that looks like this: 

name,utm_z,utm_e,utm_n,comment
Trailhead,13,0395145,3966291,Trailhead on Buckman Rd
Sierra Club TH,13,0396210,3966597,Alternate trailhead in the arroyo
then translate it like this: 
gpsbabel -i unicsv -f filename.csv -o gpx -F filename.gpx
I (and all the UTM coordinates I've had to deal with) are in zone 13, so that's what I used for that example and I hardwired that into my alias, but if you're near a zone boundary, you'll need to figure out which zone to use for each coordinate.

I also know someone who tends to send me single UTM coordinate pairs, because that's what she has her Garmin configured to show her. For instance, "We'll be using the trailhead at 0395145 3966291". This happened often enough, and I got tired of looking up the UTM UniCSV format every time, that I made another shell function just for that. 

utm2gpx () {
        unicsv=`mktemp /tmp/point-XXXXX.csv` 
        gpxfile=$unicsv:r.gpx 
        echo "name,utm_z,utm_e,utm_n,comment" >> $unicsv
        printf "Point,13,%s,%s,point" $1 $2 >> $unicsv
        gpsbabel -i unicsv -f $unicsv -o gpx -F $gpxfile
        echo Created $gpxfile
}
So I can say utm2gpx 0395145 3966291, pasting the two coordinates from her email, and get a nice GPX file that I can push to my phone.

What if all you have is a printed map, or a scan of an old map from the pre-digital days? That's part 2, which I'll post in a few days.

Now posted:

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[ 10:29 Aug 14, 2016    More mapping | permalink to this entry | ]

Fri, 16 Aug 2013

Offline mapping with lists of waypoints

Dave and I have been doing some exploratory househunting trips, and one of the challenges is how to maintain a list of houses and navigate from location to location. It's basically like geocaching, navigating from one known location to the next.

Sure, there are smartphone apps to do things like "show houses for sale near here" against a Google Maps background. But we didn't want everything, just the few gems we'd picked out ahead of time. And some of the places we're looking are fairly remote -- you can't always count on a consistent signal everywhere as you drive around, let alone a connection fast enough to download map tiles.

Fortunately, I use a wonderful open-source Android program called OsmAnd. It's the best, bar none, at offline mapping: download data files prepared from OpenStreetMap vector data, and you're good to go, even into remote areas with no network connectivity. It's saved our butts more than once exploring remote dirt tracks in the Mojave. And since the maps come from OpenStreetMap, if you find anything wrong with the map, you can fix it.

So the map part is taken care of. What about that list of houses?

Making waypoint files

On the other hand, one of OsmAnd's many cool features is that it can show track logs. I can upload a GPX file from my Garmin, or record a track within OsmAnd, and display the track on OsmAnd's map.

GPX track files can include waypoints. What if I made a GPX file consisting only of waypoints and descriptions for each house?

My husband was already making text files of potentially interesting houses: 

404 E David Dr 
Flagstaff, AZ 86001
$355,000
3 Bed 2 Bath
1,673 Sq Ft
0.23 acres
http://blahblah/long_url

2948 W Wilson Dr 
Flagstaff, AZ 86001
$285,000
3 Bed 2 Bath
1,908 Sq Ft
8,000 Sq Ft Lot 
http://blahblah/long_url

... (and so on)
So I just needed to turn those into GPX.

GPX is a fairly straightforward XML format -- I've parsed GPX files for pytopo and for ellie, and generating them from Python should be easier than parsing. But first I needed latitude and longitude coordinates. A quick web search solved that: an excellent page called Find latitude and longitude with Google Maps. You paste the address in and it shows you the location on a map along with latitude and longitude. Thanks to Bernard Vatant at Mondeca!

For each house, I copied the coordinates directly from the page and pasted them into the file. (Though that got old after about the fifth house; I'll write about automating that step in a separate article.)

Then I wrote a script called waymaker that parses a file of coordinates and descriptions and makes waypoint files. Run it like this: waymaker infile.txt outfile.gpx and it will create (or overwrite) a gpx file consisting of those waypoints.

Getting it into OsmAnd

I plugged my Android device into my computer's USB port, mounted it as usb-storage and copied all the GPX files into osmand/tracks (I had to create the tracks subdirectory myself, since I hadn't recorded any tracks. After restarting OsmAnd, it was able to see all the waypoint files.

OsmAnd has a couple of other ways of showing points besides track files. "Favorites" lets you mark a point on the map and save it to various Favorites categories. But although there's a file named favorites.gpx, changes you make to it never show up in the program. Apparently they're cached somewhere else. "POI" (short for Points of Interest) can be uploaded, but only as a .obf OsmAnd file or a .sqlitedb database, and there isn't much documentation on how to create either one. GPX tracks seemed like the easiest solution, and I've been happy with them so far.

Update: I asked on the osmand mailing list; it turns out that on the Favorites screen (Define View, then Favorites) there's a Refresh button that makes osmand re-read favorites.gpx. Works great. It uses pretty much the same format as track files -- I took <wpt></wpt> sequences I'd generated with waymaker and added them to my existing favorites.gpx file, adding appropriate categories. It's nice to have two different ways to display and categorize waypoints within the app.

Using waypoints in OsmAnd

How do you view these waypoints once they're loaded? When you're in OsmAnd's map view, tap the menu button and choose Define View, then GPX track... You'll see a list of all your GPX files; choose the one you want.

You'll be taken back to the map view, at a location and zoom level that shows all your waypoints. Don't panic if you don't see them immediately; sometimes I needed to scroll and zoom around a little before OsmAnd noticed there were waypoints and started drawing them.

Then you can navigate in the usual way. When you get to a waypoint, tap on it to see the description brieftly -- I was happy to find that multiple line descriptions work just fine. Or long-press on it to pop up a persistent description window that will stay up until you dismiss it.

It worked beautifully for our trip, both for houses and for other things like motels and points of interest along the way.

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[ 15:58 Aug 16, 2013    More mapping | permalink to this entry | ]