Part 1: Using our mobile phones to collect field data

As we cannot access our Virtual Machines presently, we will switch gears to add in a second assignment.

The APP(s) to be used in the assignment

We have looked at a couple GNSS apps in Android and iOS (GPSLogger and OSMAnd).    We had suggested that you load on or two of the apps and test them out.    We can make use of those apps in projects and data collection, but today we will be introducing another app to be used for the assignment and perhaps in your field of interest outside of the course.

Geopaparazzi and SMASH


Geopaparazzi (because not all paparazzi is evil) is an app that has been around for a long time, and has been explored a fair bit in the GIS Lab over the years.    It is useful for us in this course, as it blends in many of the topics and activities we have carried out so far in the class.


SMASH is the evolution of Geopaparazzi.    This app has been part of the rewrite of Geopaparazzi and is heavily integrated into the Geopaprazzi Survey Server. Unless you are keen to setup your own server, then you will need to figure out how to get the data out of the modified spatialite file ending wth .gpap.

Starting the Assignment

Today we will take a look at the apps and start collecting data. In Tutorial, we will start digging deeper into the app data structures and data storage methods. The assignment requirements will be written up for the tutorial, but for now – let’s have a look at the apps.

The Reference Manuals are very helpful for this assignment, including installing the app

Geopaparazzi (Android only)

Smash (Android and iOS) – Google Play or App Store

Collect data

Use whichever app you wish (both if you are an Android user) to collect some notes and GPS tracks. You should read through the manual to see how to use each app.

Hint: We will be using the form based notes in the future, as we will be creating our own notes.

Project Idea: For those computer scientists in the class, there is a good project idea to rewrite the geoparazzi plugin in python 3 to extract the objects from the gpap file into QGIS.

Part 2: Collecting high resolution Survey Data

In todays lab we are going to be looking at high precision data and how to work with it.

First point of discussion here is to develop good naming conventions early on, when post processing the data we will have many files representing the same data, but in different formats and at different progressions in the correction progress, the hardest part of this lab will be keeping track of which files are which.

Specifically we will be working with decimeter accurate GPS. This is a type of data commonly used in construction and surveying (in many cases it could be centimeter accurate).

How was the data collected:

First we set up a base sation at the university:

This station was set to record an RINEX (Receiver Independent Exchange Format) file of the sattilites.

2nd we used a ‘rover’ to go and collect some points.

Lets take a look at the data we collected and see how good it is.

Open QGIS, and load Ortho_modified as a basemap, Garmin_XX-OCT-20.gpx files, and the Oct_19_Survey, and Oct_20_Survey CSV’s.

How accurate would you describe this data to be? Is there a GPS receiver you think works better?

With our data collected we can start the processing chain.

The first thing we need to consider is that the atmosphere causes GPS signals to bend as they pass through, to correct for this we will make use of stationary GPS run by Natural Resources Canada that monitor how the GPS signals change at stationary points to determin how the atmosphere is bending the signals.

Download the data for todays class from here:

We will use the Canadian Spatial Reference System Precise Point Positioning Tool Now because this processing takes about a day to complete and this lab is too short to receive the files back I have provided you with the e-mail I received back from NRCan. In the Oct_19_CSRS-PPP folder, note that this is a super easy process you simply log in, upload the RINEX file and wait for the e-mail to return.

The file that we are most interested in here is the PDF file, and spifically the estimated position of the base station. This will be used in our corrections, but also for day 2 of survey we do something a little funny we are going to tell the base station where it is, because we put it back in the same place and we care about relitive position. Not that when using RTK or PPK gps, after processing the rover is not directry reporting it’s position, rather reporting whee it is in relation to the base station.

Lets first look at what our data looks like, open qgis, and add the following layers.

  • Ortho_modifed (as your bottom layer)
  • Garmin_19-OCT-20.gpx
  • Oct_19_Survey > GEOG 413 A.csv
  • Oct_20_Survey > GEOG 413 B-CSV.csv

Next we will start using RTK Lib to prepare the rover data.

In the data you downloaded there is a folder called rtklib and inside you will find a program called RRTKCONV-QT open it, select your rover_oct_19.UBX file and press convert, we will then do the same for the Oct_20_UBX file as well. This should give us outputs of and obs, nav, and sbs files. This is converting raw files into something that the rest of the software understands, think of this stage as developing photos.

Next open RTKPOST-QT, we will add the OBS file for the rover on Oct 19th,

And the OBS for the base sation as well as it’s NAV and SBS files

Then click on options at the bottom

In the output tab confirm Lat/Lon/Height is selected

And under positions enter the base sation position from the PPP pdf file.

Press OK to close this menu, then Execute, and finally Plot to veiw the result.

Do the same for October 20th.

At this point we have corrected our GPS data, however our survy CSV files have not yet been updated to do this we will use electron.

Finally Electron updates our survey corrdinates with the corrected data.

Categories: GEOG 413Labs