I am excited to announce that I have just released the database configuration and intake code for my APRS mapping project, aprsdb, on Github. It runs on Python 3 and Postgres with the PostGIS extension. So far I have it working on Linux (Debian Stretch), but the tools are all cross-platform so it presumably could be made to work on other operating systems.
APRS, the automatic packet reporting system, is an amateur protocol which exchanges SMS-like messages that often include location data. Because these packets include information about where they came from and how they traveled, analysis of this data can yield insight into propagation conditions. This project was significantly inspired by the work of Jon, NG0E, on the Mountain Lake APRS website, but removes the need for any internet connection. All the data collection and analysis is entirely local, and unlike the APRS Internet Service, no duplicate-filtering is performed.
Work is still underway to create a reasonably portable web front-end for it. I have a proof-of-concept version working that currently displays some static data from mid-July, 2018, when VHF radio propagation was extremely good in the Upper Midwest.
This spring I had the privilege of being a judge at my local science fair. As a high school student, I had participated in the science fair and it was a huge part of my science learning experience. Now that I am qualified to be a judge, it is time for me to give back while avoiding the trap of turning into the dreaded Reviewer #2.*
I scored quite a few different projects, primarily in Earth & Environmental Science. I was pleased to see the large number of students involved in the discipline, and the interest they showed in environmental monitoring and sustainability. However, I was surprised to see the number of projects which focused on pH, but without understanding of pH of rainwater or the influence of carbonates.
Limited or non-existent access to instrumentation was clearly a limiting factor in many of the projects. That observation leads to a question: what can be done to address the disparity in instrument access and to improve the quality of data being used in science fair projects? I believe the long-term answer to that question is to fund our schools and support the teachers and staff who work in them.
Another solution would be to have students use and analyze publicly available data. In many cases, this cut out some of the hands-on portion of making measurements, which detracts from the overall learning goals. Using publicly-available data also means that teachers would need to be more aware of good data resources and ideas for how to go about analyzing that data—each significantly increasing the work load and responsibilities of the teachers. For research projects, it is important to have a low student:teacher ratio, so that the students can have the support they need to succeed in their project. However, publicly available data allow students to do cutting-edge research with the same tools and data used by professional scientists.
Here are a few examples of low-budget, high-quality data projects that could be interesting:
Weather forecast accuracy. Make a daily record of the National Weather Service forecast (for each day forecast) for your area, as well as the almanac data from the closest instrumented NWS station (often an airport). How does forecast accuracy change over time? How accurate is a forecast 72 hours out?
Earth-Observing Satellite data. With a constellation of Earth-observing satellites including Aqua, Terra, Landsat (7 and 8), and formerly EO-1, there are mountains of data waiting to be analyzed. Students can look at crop health locally, at glacial changes, deforestation, volcanic activity, wildfires, and a host of other things. Data are freely available, GIS software is freely available, and the data analysis skills are quite relevant in today’s job market.
Buoy data. As I’ve mentioned here before, there are several fleets of marine buoys which take various oceanographic measurements, such as conductivity-temperature-depth profiles and current measurements. Oceanography isn’t my thing, but I’m sure there are enough papers that use these data that some project ideas could be found. These projects are likely to use GIS.
* Reviewer #2 is known for being overly critical, wanting a paper that isn’t particularly close to the paper that was submitted, having unreasonable or unattainable expectations, and generally being a jerk.
One of a geoscientist’s most useful tools is a geographic information system, or GIS. This is a computer program which allows the creation and analysis of maps and spatial data. Perhaps the most widely used in academia is ArcGIS, from ESRI. However, as a student and hobbyist who likes to support the open-source software ecosystem, I use the free/open-source QGIS.
QGIS can be used to make geologic maps of an area, chart streams, and note where certain geologic features (e.g. volcanic cones) are present. For instance, at the top of this post is a map of Heard Island that I’ve been playing with, from the Australian Antarctic Division. It is composed of three different layers, each published in 2009: an island layer (base, brown), a lagoon layer (middle, blue), and a glacier layer (top, dotted bluish-white).
I believe I have mentioned here previously that one interesting thing about working with Heard Island is that with major surface changes underway (glacial retreat, erosion, minor volcanic activity), the maps become obsolete fairly quickly. This week I have been learning about creating polygons in a layer, so that I can recreate a geologic map from Barling et al. 1994. One issue I’ve come up against, though, is that the 1994 paper has some areas covered in glacier (from 1986/7 field work), whereas my 2009 glacier extent map shows them to be presently uncovered. In fact, even the 2009 map shows a tongue of glacier protruding into Stephenson Lagoon (in the southeast corner), while recent satellite imagery shows no such tongue.
During the Heard Island Expedition in March and April, 2016, I hope that we will have time to go do a little geologic mapping. Creating some datasets showing the extent of glaciation (particularly along the eastern half of the island) and vegetation, as well as updating the geologic map to include portions which were glaciated in 1986/7, would be a worthwhile and seemingly straightforward project.
QGIS itself is much more than a mapping tool (not that I know how to use it), and can analyze numeric data which is spatially distributed, like the concentration of chromium in soil or water samples from different places on a study site. QGIS provides a free way to get your hands dirty with spatial data and mapping, and is powerful enough to use professionally. Users around the globe share information on how to use it, and contribute to its development.
For those looking to go into geoscience as a career, I would strongly recommend learning how to use it. I didn’t learn GIS in college (chemists don’t use it much), and somehow avoided it in grad school. But I regret not having put time in to learn it sooner. There’s all kinds of interesting spatial data, and a good job market for people with a GIS skillset (or so I hear). I have only scratched the surface of QGIS’s capabilities with my use of it, but I definitely intend to keep learning. You can probably follow the day-to-day frustrations and victories on my Twitter account (@i_rockhopper).
 Barling, J.; Goldstein, S. L.; Nicholls, I. A. 1994 “Geochemistry of Heard Island (Southern Indian Ocean): Characterization of an Enriched Mantle Component and Implications for Enrichment of the Sub-Indian Ocean Mantle” Journal of Petrology 35, p. 1017–1053. doi: 10.1093/petrology/35.4.1017