Data Collection I

Introduction:

In the previous assignment, we were assigned to create a geodatabase to suit our microclimate sampling exercise. The purpose of this week's lab was to test the use of GPS with our previously created databases and work out any kinks that we might run in to before next week, when we'll be collecting the microclimate data. We familiarized ourselves with the process of readying a geodatabase for use in ArcPad, deploying it to our GPS units, collecting data, and checking the data back in. We used Juno Trimble GPS units, inputting data from a Kestrel weather meter.

Juno Trimble GPS unit. This unit uses ESRI's ArcPad application, which allows for GPS collection into a geodatabase. In this case, the one from last week's exercise.

Kestrel weather meter, which can be used to read temperature, wind speed, wind chill, dew point, percent humidity and a number of other climate figures.

Methods:

The majority of this lab was done from inside, readying the geodatabase for use in the field. As described in the previous exercise, this step is especially important because it reduces unnecessary work while in the field.

First, I connected the Trimble unit to the computer, and readied my geodatabase for deployment. This involved opening ESRI Arc GIS, enabling the 'ArcPad Data Manager' toolbar, adding a basemap, and including my microclimate point feature class described in the previous exercise. For the basemap, I used a 2013 aerial image of the area, zoomed into the UW-Eau Claire campus. Upon "getting data for ArcPad," only the extent of the area that I was zoomed into would be included. In this step I also checked out the microclimate feature class, and ultimately created a package that is deployable for ArcPad. I copied this package (a file on Windows File Explorer) into my student folder as a copy in case the deployment didn't occur properly. I also copied it onto the Trimble unit's memory card. This made it available for use in the field.

The Get Data for ArcPad tool. This tool essentially takes the feature class and background image shown, checking them out for editing, and creating a package that is compatible with ArcPad. This package is then copied onto the GPS unit, and it will allow for digitization in the microclimate feature class. Play the video below for further information on data deployment. 

We were to go into the field in groups of two, so that we could assist each other in collecting points, but as soon as I got outside I realized I had an issue. My microclimate feature class had no projection defined, so the GPS functionality didn't have a spatial reference for my points. This meant that I couldn't digitize, so I had to go back inside to reasses. I had to use the define projection tool in ArcToolbox on my microclimate feature class, defining as WGS 1984. I figured that this GCS would be compatible with the Trimble Units, because they take points in a GCS as well. By the time I had edited my feature class and went through the above process again, most of my classmates had already completed taking their data. This meant that I had to go out alone and take my own Kestrel temperature, wind speed, wind chill, dew point, and percent humidity readings. I recorded these in my ArcPad session for only three different points on the South side of campus.

The final step was to re-check in our data, using a similar tool as was used to check it out earlier in the exercise. This part worked smoothly, and my points were added back into an ArcMap session.

Discussion:

There were quite a few hitches that the class encountered in this lab, and it is good that we did now, as opposed to having them happen when we do our real data collection in the next exercise. I learned the valuable lesson that for features to be edited in ArcPad, they must have a projection defined. Also, I noticed that my GROUND_COVER field was actually called NOTES. That is an issue because I also have an actual NOTES field as well. This will need to be resolved before next week's data collection exercise. At the end of the exercise this week, we voted on one student's geodatabase as being usable for the rest of the class for further microclimate surveying on campus. This means that all students will be using the same geodatabase with the same domains, basemaps and feature classes, which will minimize discrepancies in the final dataset.

Conclusion:

This exercise was valuable because it allowed us to work out common issues that can occur when using GPS units to digitize data. Knowing how to deal with these issues is a very important skill to have when doing geospatial field work. Also, the exercise included valuable information on how to operate a Kestrel weather meter, and refreshed my memory on operating a GPS unit to digitize point features. Proper deployment of data is also very important, and the class experienced some of the issues associated with it.