Shallow Thoughts : tags : openstreetmap

Made it to LA Mountain, Finally

30 Day Map Challenge Day 5: A Journey

Last year for the #OpenStreetMap day of the 30 Day Map Challenge, I wrote about a hike that went a little wrong, when we lost our way on the Mitchell Trail and ended up going partway up the trail to LA Mountain.

LA Mountain is so named because Los Alamos High School kids have, for many years, maintained a big "LA" on the mountain that was visible from town. I say "was" because the LA is very hard to see now, and I've been told (but haven't been able to confirm) that's because the Forest Service, which owns the land, said the kids had to stop updating it. I'd seen it from below and always wondered how to get there, so last year, when I realized that was the trail we were on, I vowed to go back soon and go all the way up.

And then, of course, I promptly forgot all about it, until a few days ago when I was reviewing last year's 30 Day Map Challenge projects.

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Tags: mapping, 30DayMapChallenge, openstreetmap
[ 07:58 Nov 05, 2024    More mapping | permalink to this entry | ]

Fetching OpenStreetMap Details with OSMPythonTools

I was talking to a friend about LANL's proposed new powerline. A lot of people are opposing it because the line would run through the Caja del Rio, an open-space piñon-juniper area adjacent to Santa Fe which is owned by the US Forest Service. The proposed powerline would run from the Caja across the Rio Grande to the Lab. It would carry not just power but also a broadband fiber line, something Los Alamos town, if not the Lab, needs badly. On the other hand, those opposed worry about road-building and habitat destruction in the Caja.

I'm always puzzled reading accounts of the debate. There already is a powerline running through the Caja and across the Rio via Powerline Point. The discussions never say (a) whether the proposed line would take a different route, and if so, (b) Why? why can't they just tack on some more lines to the towers along the existing route?

For instance, in the slides from one of the public meetings, the map on slide 9 not only doesn't show the existing powerline, but also uses a basemap that has no borders and NO ROADS. Why would you use a map that doesn't show roads unless you're deliberately trying to confuse people?

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Tags: mapping, GIS, programming, python, Los Alamos, openstreetmap
[ 12:14 Aug 01, 2024    More mapping | permalink to this entry | ]

New Hiking Route: Ancho Rapids to Lower Water Canyon

Can you follow Lower Water Canyon (in the DOE open space lands south of White Rock, NM) all the way to the Rio Grande?

In the decade we've lived here, we've heard that question and asked it ourselves, and have heard a few anecdotal reports. You can follow it down most of the way, but there's a pour-off near the end that you won't want to do without a rope. Or there was a pour-off fifteen years ago that wasn't that big a deal, but it's changed since then and isn't passable now. Or ... well, anyway, the story kept changing depending on who we asked, and nobody seemed to have tried it in many years.

Now I've done it. It's a beautiful hike, and right now there's an abundance of wildflowers in bloom along the canyon.

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Tags: hiking, wildflowers, los alamos, openstreetmap
[ 12:42 May 10, 2024    More hikes | permalink to this entry | ]

First Time Biking the White Ridge Bike Trails

Dave and I finally got around to riding the White Ridge Bike Trails. It's an area north of Albuquerque, adjacent to the Ojito Wilderness (which is also on our to-explore list). Somehow we'd never quite gotten there, but this week was perfect. Here in White Rock our local trails are covered with melting snow, which means they'll be muddy for at least a month even if it doesn't snow any more. But down near Albuquerque they didn't get much snow, and the temperature was forecast as mid-40s, so we hoped conditions would be good.

The map paints trails as Beginner (green), Moderate (blue), Difficult (red), and Severe (black). We're intermediate bikers: pretty comfortable riding over rocks and other modest obstacles, but not good enough to do the super technical stuff like we see at Pajarito. But there's no consistency to bike trail ratings: a lot of trails rated difficult in the bay area were well within our abilities,, while some trails that Los Alamos County puts on their "family friendly" list are so difficult that I can't ride them (we've argued with the county's trail guy, who I don't think is a mountain biker; he insists that they should rated as easy based on some IMBA criterion or other.)

Anyway, the point is that you can't tell what you'll be able to ride without going there and trying it.

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Tags: bike, MTB, openstreetmap
[ 19:41 Jan 20, 2024    More bike | permalink to this entry | ]

How to Use QGIS to Identify Fire Areas

(A QGIS beginner's tutorial.)

For quite a while I've been wanting a map showing the perimeters of the big local fires. When walking through a burned area, I wonder, was this one from the Cerro Grande fire? Or Las Conchas? Or another fire?

Yesterday, inspired by Ryan Peek's #30DayMapChallenge toot on California Fire Perimeters, I decided to look for the data and load it in QGIS.

Also, I never did an entry for Day 3 of the #30DayMapChallenge, "Polygons", so this is it, not quite three weeks late.

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Tags: mapping, GIS, fire, Los Alamos, 30DayMapChallenge, openstreetmap
[ 12:34 Nov 23, 2023    More mapping | permalink to this entry | ]

Lost and Found: Missed the Mitchell but Found Something Unexpected (also, 30-day Map Challenge #15)

Yesterday's 30-Day Map Challenge theme was OpenStreetMap.

I use (and contribute to) OpenStreetMap quite a bit, and I use OSM basemaps in pretty much all my mapping. (I have used Google in the past, but between their changing or withdrawing APIs every few years, and suddenly deciding to charge for previously free APIs, I switched to using only open source maps.)

But that was yesterday, which was group hiking day, so I was out tramping over mountains instead of sitting at the computer making maps. But a wrong turn on the hike led to a serendipitous discovery that wouldn't have happened without OpenStreetMap.

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Tags: hiking, mapping, pytopo, serendipit, 30DayMapChallenge, openstreetmap
[ 11:08 Nov 16, 2023    More mapping | permalink to this entry | ]

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:

• 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 Georeferencer GDAL.
  Update: both OSM and the Georeferencer are now included by default, so you no longer have to install these plugins.
• 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 interested in.
  Update: Sometimes, including an OpenStreetMap is as easy as clicking on the OpenStreetMap line in the upper left pane of the QGIS window. Other times there is no such line, and you have to use Web > QuickMapServices. I don't know how QGIS decides.
  
  
  (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...
  Update: If it isn't showing the files you want to open, you may need to adjust the Files of type menu to make sure it includes your file type. When I ran it just now, I had two JPG files to georeference. The first time, it showed those files automatically. When I went to open the second file, it showed nothing about I had to change Files of type to JPEG JFIF before I could open the file.
  
  
• 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 map canvas".
• 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 match.
  
• 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. Click OK.
  
• 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:

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

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).

Tags: GIS, mapping, linux, osmand, qgis, openstreetmap
[ 19:08 Apr 10, 2019    More mapping | permalink to this entry | ]

Making New Map Tracks with Google Earth

A few days ago I wrote about track files in maps, specifically Translating track files between mapping formats. I promised to follow up with information on how to create new tracks.

Update: Years later, I added simple track editing to my own map program, PyTopo. It can split an existing track, or create a new track, then can save as GPX.

For instance, I have some scans of old maps from the 60s and 70s showing the trails in the local neighborhood. There's no newer version. (In many cases, the trails have disappeared from lack of use -- no one knows where they're supposed to be even though they're legally trails where you're allowed to walk.) I wanted a way to turn trails from the old map into GPX tracks.

My first thought was to trace the old PDF map. A lot of web searching found a grand total of one page that talks about that: How to convert image of map into vector format?. It involves using GIMP to make an image containing just black lines on a white background, saving as uncompressed TIFF, then using a series of commands in GRASS. I made a start on that, but it was looking like it might be a big job that way. Since a lot of the old trails are still visible as faint traces in satellite photos, I decided to investigate tracing satellite photos in a map editor first, before trying the GRASS method.

But finding a working open source map editor turns out to be basically impossible. (Opportunity alert: it actually wouldn't be that hard to add that to PyTopo. Some day I'll try that, but now I was trying to solve a problem and hoping not to get sidetracked.)

The only open source map editor I've found is called Viking, and it's terrible. The user interface is complicated and poorly documented, and I could input only two or three trail segments before it crashed and I had to restart. Saving often, I did build up part of the trail network that way, but it was so slow and tedious restoring between crashes that I gave up.

OpenStreetMap has several editors available, and some of them are quite good, but they're (quite understandably) oriented toward defining roads that you're going to upload to the OpenStreetMap world map. I do that for real trails that I've walked myself, but it doesn't seem appropriate for historical paths between houses, some of which are now fenced off and few of which I've actually tried walking yet.

Editing a track in Google Earth

In the end, the only reasonable map editor I found was Google Earth -- free as in beer, not speech. It's actually quite a good track editor once I figured out how to use it -- the documentation is sketchy and no one who writes about it tells you the important parts, which were, for me:

Click on "My Places" in the sidebar before starting, assuming you'll want to keep these tracks around.

Right-click on My Places and choose Add->Folder if you're going to be creating more than one path. That way you can have a single KML file (Google Earth creates KML/KMZ, not GPX) with all your tracks together.

Move and zoom the map to where you can see the starting point for your path.

Click the "Add Path" button in the toolbar. This brings up a dialog where you can name the path and choose a color that will stand out against the map. Do not hit Return after typing the name -- that will immediately dismiss the dialog and take you out of path editing mode, leaving you with an empty named object in your sidebar. If you forget, like I kept doing, you'll have to right-click it and choose Properties to get back into editing mode.

Iconify, shade or do whatever your window manager allows to get that large, intrusive dialog out of the way of the map you're trying to edit. Shade worked well for me in Openbox.

Click on the starting point for your path. If you forgot to move the map so that this point is visible, you're out of luck: there's no way I've found to move the map at this point. (You might expect something like dragging with the middle mouse button, but you'd be wrong.) Do not in any circumstances be tempted to drag with the left button to move the map: this will draw lots of path points.

If you added points you don't want -- for instance, if you dragged on the map trying to move it -- Ctrl-Z doesn't undo, and there's no Undo in the menus, but Delete removes previous points. Whew.

Once you've started adding points, you can move the map using the arrow keys on your keyboard. And you can always zoom with the mousewheel.

When you finish one path, click OK in its properties dialog to end it.

Save periodically: click on the folder you created in My Places and choose Save Place As... Google Earth is a lot less crashy than Viking, but I have seen crashes.

When you're done for the day, be sure to File->Save->Save My Places. Google Earth apparently doesn't do this automatically; I was forever being confused why it didn't remember things I had done, and why every time I started it it would give me syntax errors on My Places saying it was about to correct the problem, then the next time I'd get the exact same error. Save My Places finally fixed that, so I guess it's something we're expected to do now and then in Google Earth.

Once I'd learned those tricks, the map-making went fairly quickly. I had intended only to trace a few trails then stop for the night, but when I realized I was more than halfway through I decided to push through, and ended up with a nice set of KML tracks which I converted to GPX and loaded onto my phone. Now I'm ready to explore.

Tags: mapping, GIS, openstreetmap
[ 17:26 Aug 17, 2016    More mapping | permalink to this entry | ]

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.

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

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.

Tags: mapping, GIS, geocaching, househunting, programming, osmand, pytopo, openstreetmap
[ 15:58 Aug 16, 2013    More mapping | permalink to this entry | ]

WhereCamp 2011

I spent Friday and Saturday at the WhereCamp unconference on mapping, geolocation and related topics.

This was my second year at WhereCamp. It's always a bit humbling. I feel like I'm pretty geeky, and I've written a couple of Python mapping apps and I know spherical geometry and stuff ... but when I get in a room with the folks at WhereCamp I realize I don't know anything at all. And it's all so interesting I want to learn all of it! It's a terrific and energetic unconference. I

I won't try to write up a full report, but here are some highlights.

Several Grassroots Mapping people were there again this year. Jeffrey Warren led people in constructing balloons from tape and mylar space blankets in the morning, and they shot some aerial photos. Then in a late-afternoon session he discussed how to stitch the aerial photos together using Cargen Knitter.

But he also had other projects to discuss: the Passenger Pigeon project to give cameras to people who will be flying over environmental that need to be monitored -- like New York's Gowanus Canal superfund site, next to La Guardia airport. And the new Public Laboratory for Open Technology and Science has a new project making vegetation maps by taking aerial photos with two cameras simultaneously, one normal, one modified for infra-red photography.

How do you make an IR camera? First you have to remove the IR-blocking filter that all digital cameras come with (CCD sensors are very sensitive to IR light). Then you need to add a filter that blocks out most of the visible light. How? Well, it turns out that exposed photographic film (remember film?) makes a good IR-only filter. So you go to a camera store, buy a roll of film, rip it out of the reel while ignoring the screams of the people in the store, then hand it back to them and ask to have it developed. Cheap and easy.

Even cooler, you can use a similar technique to make a spectrometer from a camera, a cardboard box and a broken CD. Jeffrey showed spectra for several common objects, including bacon (actually pancetta, it turns out).

JW:	See the dip in the UV? Pork fat is very absorbent in the UV. That's why some people use pork products as sunscreen.
Audience member:	Who are these people?
JW:	Well, I read about them on the internet.

I ask you, how can you beat a talk like that?

Two Google representatives gave an interesting demo of some of the new Google APIs related to maps and data visualization, in particular Fusion Tables. Motion charts sounded especially interesting but they didn't have a demo handy; there may be one appearing soon in the Fusion Charts gallery. They also showed the new enterprise-oriented Google Earth Builder, and custom street views for Google Maps.

There were a lot of informal discussion sessions, people brainstorming and sharing ideas. Some of the most interesting ones I went to included

• Indoor orientation with Android sensors: how do you map an unfamiliar room using just the sensors in a typical phone? How do you orient yourself in a room for which you do have a map?
• A discussion of open data and the impending shutdown of data.gov. How do we ensure open data stays open?
• Using the Twitter API to analyze linguistic changes -- who initiates new terms and how do they spread? -- or to search for location-based needs (any good ice cream places near where I am?)
• Techniques of data visualization -- how can we move beyond basic heat maps and use interactivity to show more information? What works and what doesn't?
• An ongoing hack session in the scheduling room included folks working on projects like a system to get information from pilots to firefighters in real time. It was also a great place to get help on any map-related programming issues one might have.
• Random amusing factoid that I still need to look up (aside from the pork and UV one): Automobile tires have RFID in them?

Lightning talks included demonstrations and discussions of global Twitter activity as the Japanese quake and tsunami news unfolded, the new CD from OSGeo, the upcoming PII conference -- that's privacy identity innovation -- in Santa Clara.

There were quite a few outdoor game sessions Friday. I didn't take part myself since they all relied on having an iPhone or Android phone: my Archos 5 isn't reliable enough at picking up distant wi-fi signals to work as an always-connected device, and the Stanford wi-fi net was very flaky even with my laptop, with lots of dropped connections.

Even the OpenStreetMap mapping party was set up to require smartphones, in contrast with past mapping parties that used Garmin GPS units. Maybe this is ultimately a good thing: every mapping party I've been to fizzled out after everyone got back and tried to upload their data and discovered that nobody had GPSBabel installed, nor the drivers for reading data off a Garmin. I suspect most mapping party data ended up getting tossed out. If everybody's uploading their data in realtime with smartphones, you avoid all that and get a lot more data. But it does limit your contributors a bit.

There were a couple of lowlights. Parking was very tight, and somewhat expensive on Friday, and there wasn't any info on the site except a cheerfully misleading "There's plenty of parking!" And the lunch schedule on Saturday as a bit of a mess -- no one was sure when the lunch break was (it wasn't on the schedule), so afternoon schedule had to be re-done a couple times while everybody worked it out. Still, those are pretty trivial complaints -- sheesh, it's a free, volunteer conference! and they even provided free meals, and t-shirts too!

Really, WhereCamp is an astoundingly fun gathering. I always leave full of inspiration and ideas, and appreciation for the amazing people and projects presented there. A big thanks to the organizers and sponsors. I can't wait 'til next year -- and I hope I'll have something worth presenting then!

Tags: wherecamp, mapping, GIS, tech, openstreetmap
[ 23:40 Apr 24, 2011    More mapping | permalink to this entry | ]

New versions of mapping programs: Pytopo and Ellie

On our recent Mojave trip, as usual I spent some of the evenings reviewing maps and track logs from some of the neat places we explored.

There isn't really any existing open source program for offline mapping, something that works even when you don't have a network. So long ago, I wrote Pytopo, a little program that can take map tiles from a Windows program called Topo! (or tiles you generate yourself somehow) and let you navigate around in that map.

But in the last few years, a wonderful new source of map tiles has become available: OpenStreetMap. On my last desert trip, I whipped up some code to show OSM tiles, but a lot of the code was hacky and empirical because I couldn't find any documentation for details like the tile naming scheme.

Well, that's changed. Upon returning to civilization I discovered there's now a wonderful page explaining the Slippy map tilenames very clearly, with sample code and everything. And that was the missing piece -- from there, all the things I'd been missing in pytopo came together, and now it's a useful self-contained mapping script that can download its own tiles, and cache them so that when you lose net access, your maps don't disappear along with everything else.

Pytopo can show GPS track logs and waypoints, so you can see where you went as well as where you might want to go, and whether that road off to the right actually would have connected with where you thought you were heading.

It's all updated in svn and on the Pytopo page.

Ellie

Most of the pytopo work came after returning from the desert, when I was able to google and find that OSM tile naming page. But while still out there and with no access to the web, I wanted to review the track logs from some of our hikes and see how much climbing we'd done. I have a simple package for plotting elevation from track logs, called Ellie. But when I ran it, I discovered that I'd never gotten around to installing the pylab Python plotting package (say that three times fast!) on this laptop.

No hope of installing the package without a net ... so instead, I tweaked Ellie so that so that without pylab you can still print out statistics like total climb. While I was at it I added total distance, time spent moving and time spent stopped. Not a big deal, but it gave me the numbers I wanted. It's available as ellie 0.3.

Tags: mapping, GIS, programming, python, pytopo, openstreetmap
[ 19:24 Oct 30, 2010    More mapping | permalink to this entry | ]

Pytopo 0.8 released

On my last Mojave trip, I spent a lot of the evenings hacking on PyTopo.

I was going to try to stick to OpenStreetMap and other existing mapping applications like TangoGPS, a neat little smartphone app for downloading OpenStreetMap tiles that also runs on the desktop -- but really, there still isn't any mapping app that works well enough for exploring maps when you have no net connection.

In particular, uploading my GPS track logs after a day of mapping, I discovered that Tango really wasn't a good way of exploring them, and I already know Merkaartor, nice as it is for entering new OSM data, isn't very good at working offline. There I was, with PyTopo and a boring hotel room; I couldn't stop myself from tweaking a bit.

Adding tracklogs was gratifyingly easy. But other aspects of the code bother me, and when I started looking at what I might need to do to display those Tango/OSM tiles ... well, I've known for a while that some day I'd need to refactor PyTopo's code, and now was the time.

Surprisingly, I completed most of the refactoring on the trip. But even after the refactoring, displaying those OSM tiles turned out to be a lot harder than I'd hoped, because I couldn't find any reliable way of mapping a tile name to the coordinates of that tile. I haven't found any documentation on that anywhere, and Tango and several other programs all do it differently and get slightly different coordinates. That one problem was to occupy my spare time for weeks after I got home, and I still don't have it solved.

But meanwhile, the rest of the refactoring was done, nice features like track logs were working, and I've had to move on to other projects. I am going to finish the OSM tile MapCollection class, but why hold up a release with a lot of useful changes just for that?

So here's PyTopo 0.8, and the couple of known problems with the new features will have to wait for 0.9.

Tags: programming, python, gtk, pygtk, mapping, GIS, openstreetmap
[ 20:49 Jun 20, 2009    More programming | permalink to this entry | ]

Garmin Vista Cx on Ubuntu "Hardy"

I got myself a GPS unit for Christmas.

I've been resisting the GPS siren song for years -- mostly because I knew it would be a huge time sink involving months of futzing with drivers and software trying to get it to do something useful.

But my experience at an OpenStreetMap mapping party got me fired up about it, and I ordered a Garmin Vista Cx.

Shopping for a handheld GPS is confusing. I was fairly convinced I wanted a Garmin, just because it's the brand used by most people in the open source mapping community so I knew they were likely to work. I wanted one with a barometric altimeter, because I wanted that data from my hikes and bike rides (and besides, it's fun to know how much you've climbed on an outing; I used to have a bike computer with an altimeter and it was a surprisingly good motivator for working harder and getting in better shape).

But Garmin has a bazillion models and I never found any comparison page explaining the differences among the various hiking eTrex models. Eventually I worked it out:

Garmin eTrex models, decoded

C

Color display. This generally also implies USB connectivity instead of serial, just because the color models are newer.

H

High precision (a more sensitive satellite receiver).

x

Takes micro-SD cards. This may not be important for storing tracks and waypoints (you can store quite a long track with the built-in memory) but they mean that you can load extra base maps, like topographic data or other useful features.

Vista, Summit

These models have barometric altimeters and magnetic compasses. (I never did figure out the difference between a Vista and a Summit, except that in the color models (C), Vistas take micro-SD cards (x) while Summits don't, so there's a Summit C and HC while Vistas come in Cx and HCx. I don't know what the difference is between a monochrome Summit and Vista.)

Legend, Venture

These have no altimeter or compass. A Venture is a Legend that comes without the bundled extras like SD card, USB cable and base maps, so it's cheaper.

For me, the price/performance curve pointed to the Vista Cx.

Loading maps

Loading base maps was simplicity itself, and I found lots of howtos on how to use downloadable maps. Just mount the micro-SD card on any computer, make a directory called Garmin, and name the file gmapsupp.img. I used the CloudMade map for California, and it worked great. There are lots of howtos on generating your own maps, too, and I'm looking forward to making some with topographic data (which the CloudMade maps don't have). The most promising howtos I've found so far are the OSM Map On Garmin page on the OSM wiki and the much more difficult, but gorgeous, Hiking Biking Mapswiki page.

Uploading tracks and waypoints

But the real goal was to be able to take this toy out on a hike, then come back and upload the track and waypoint files.

I already knew, from the mapping party, that Garmins have an odd misfeature: you can connect them in usb-storage mode, where they look like an external disk and don't need any special software ... but then you can't upload any waypoints. (In fact, when I tried it with my Vista Cx I didn't even see the track file.) To upload tracks and waypoints, you need to use something that speaks Garmin protocol: namely, the excellent GPSBabel.

So far so good. How do you call GPSbabel? Luckily for me, just before my GPS arrived, Iván Sánchez Ortega posted a useful little gpsbabel script to the OSM newbies list and I thought I was all set.

But once I actually had the Vista in hand, complete with track and waypoints from a walk around the block, it turned out it wasn't quite that simple -- because Ubuntu didn't create the /dev/ttyUSB0 that Iván's script used. A web search found tons of people having that problem on Ubuntu and talking about various workarounds, involving making sure the garmin_usb driver is blacklisted in /etc/modprobe.d/blacklist (it was already), adding a /etc/udev/rules.d/45-garmin.rules file that changes permissions and ownership of ... um, I guess of the file that isn't being created? That didn't make much sense. Anyway, none of it helped.

But finally I found the fix: keep the garmin_usb driver blacklisted use "usb:" as the device to pass to GPSBabel rather than "/dev/ttyUSB0". So the commands are:

gpsbabel -t -i garmin -f usb: -o gpx -F tracks.gpx
gpsbabel -i garmin -f usb: -o gpx -F waypoints.gpx

Like so many other things, it's easy once you know the secret! Viewing tracklogs works great in Merkaartor, though I haven't yet found an app that does anything useful with the elevation data. I may have to write one.

Tags: gps, mapping, GIS, linux, ubuntu, udev, openstreetmap
[ 16:31 Jan 04, 2009    More mapping | permalink to this entry | ]

OpenStreetMap mapping parties

Latest obsession: mapping with OpenStreetMap.

Last month, OpenStreetMap and its benefactor company CloudMade held a "mapping party" in Palo Alto. I love maps and mapping (I wrote my own little topographic map viewer when I couldn't find one ready-made) and I've been wanting to know more about the state of open source mapping. A mapping party sounded perfect.

The party was a loosely organized affair. We met at a coffeehouse and discussed basics of mapping and openstreetmap. The hosts tried to show us newbies how OSM works, but that was complicated by the coffeehouse's wireless net being down. No big deal -- turns out the point of a mapping party is to hand out GPSes to anyone who doesn't already have one and send us out to do some mapping.

I attached myself to a couple of CloudMade folks who had some experience already and we headed north on a pedestrian path. We spent a couple of hours walking urban trails and marking waypoints. Then we all converged on a tea shop (whose wireless worked a little better than the one at the coffeehouse, but still not very reliably) for lunch and transfer of track and waypoint files.

This part didn't work all that well. It turned out the units we were using (Garmin Legend HCx) can transfer files in two modes, USB mass storage (the easy way, just move files as if from an external disk) or USB Garmin protocol (the hard way: you have to use software like gpsbabel, or the Garmin software if you're on Windows). And in mass storage mode, you get a file but the waypoints aren't there.

The folks running the event all had Macs, and there were several Linux users there as well, but no Windows laptops. By the time the Macs both had gpsbabel downloaded over the tea shop's flaky net, it was past time for me to leave, so I never did get to see our waypoint files. Still, I could see it was possible (and one of the Linux attendees assured me that he had no trouble with any of the software; in fact, he found it easier than what the Mac people at the party were going through).

But I was still pretty jazzed about how easy OpenStreetMap is to use. You can contribute to the maps even without a GPS. Once you've registered on the site, you just click on the Edit tab on any map, and you see a flash application called "Potlatch" that lets you mark trails, roads or other features based on satellite images or the existing map. I was able to change a couple of mismarked roads near where I live, as well as adding a new trail and correcting the info on an existing one for one of the nearby parks.

If you prefer (as, I admit, I do) to work offline or don't like flash, you can use a Java app, JOSM, or a native app, merkaartor. Very cool! Merkaartor is my favorite so far (because it's faster and works better in standalone mode) though it's still fairly rough around the edges. They're all described on the OSM Map Editing page.

Of course, all this left me lusting after a GPS. But that's another story, to be told separately.

Tags: gps, GIS, mapping, open source, openstreetmap
[ 13:00 Jan 03, 2009    More mapping | permalink to this entry | ]