Google Maps powered geotagging software?

The free Geotag hasn't been mentioned, yet it does exactly that: tagging photos with geolocation based on Google Map selection.

Its main use case is when you have a bunch of untagged photos (taken with a camera without GPS) and a GPS track of the same trip from a separate device. If the camera time was set correctly, Geotag will automatically sync the photos with the track and will assign the location to the photos. (If time was not set correctly, it can be fixed right there as well).

Nevertheless, you can assign location completely manually, and/or fine tune the automatically assigned location. Geotag runs in Java 6+ (and thus is compatible with most platforms) and will send you to the browser with Google Maps (or, alternatively, to Google Earth, if installed) to pick the location. This type of loose integration does not require a special key from Google.

One advantage of Geotag over some other similar stand-alone tools, for me at least, is that it uses Phil Harvey's Exiftool to actually write the EXIF tags. (You need to download it separately). This is a very reliable and powerful tool, which does exactly what it's asked to and doesn't destroy any other metadata nor writes its own markers (a common sin of most other software).

This freeware (Windows v7 or later) will create a KML for all of the geotagged photos in a selected directory and any sub-directories. The resulting KML can be opened in Google Earth. Click the image location icon will open the image within Google Earth. Since the resulting file is a KML, you could add the KML to a Google Map but the images would not be visible in Google Maps.

https://github.com/ShuksanGeomatics/Geotagged_Images_To_KML_OLD

For those with Python skills who want a more Pythonic experience (or want to use the tool on a non-Windows OS machine) you can install this updated version of the code for Python 3. https://github.com/ShuksanGeomatics/Geotagged_Image_Tools

Disclaimer: I am the developer of these tools.

In 2018 Google increased pricing of the Google Maps API. Consequently it's more difficult to find reasonably priced geotagging software that lets you select the location using Google Maps.

• Lightroom has arguably the most intuitive geotagging interface. Geotagging stopped working in the standalone versions of Lightroom, but a quite involved workaround is to replace the Google Maps API key with your own.
• Darktable is a free open-source alternative to Lightroom. It's not as complete, but somehow it still supports geotagging using a GPX log and can display images on Google Maps.
• ACDSee is a photo editor that displays images on Google Maps.
• Photo Mechanic is another photo editor that supports geotagging and placing images on Google Maps. The user interface is not the most convenient, and takes some time to get used to.
• GeoSetter is a freeware tool for geotagging that supports Google Maps, but only in development mode since they increased the API pricing. It hasn't been updated for a while, and the user interface can be confusing, but once you get used to it, geotagging works quite nicely. You can load multiple track logs, and it's able to interpolate between tracks.

1. Go to Google Maps and click on the desired location.

2. The URL will change to something like

   https://www.google.com/maps/@[lat],[long],[alt]z

3. Use exiftool to tag your photo:

   exiftool -GPSLatitude="$lat" -GPSLongitude="$lon" -GPSAltitude="$alt" -GPSAltitudeRef=0 "$file"

---

If you have Google Location History turned on, you can download KML files from Google Timeline or Takeout. Then use exiftool to tag your photos. Replace -00:00 with the value that corresponds to your time zone.

exiftool -if 'not ($GPSLatitude or $GPSLongitude)' -geotag history.kml '-geotime<${createdate}-00:00' -r -ext jpg  .

The maps module in Darktable can use Google Maps, OSM, and several other sources. It is free and open source and runs on Linux, MacOS, and Windows. Photos can be geotagged by dragging and dropping.

Since Darktable is a non-destructive editor, photos must be exported to have the additional information encoded. With JPEG images, it might make sense to consider a workflow that minimizes quality potential issues caused by multiple compression cycles.