Andrew Murray’s Work in Geography



Geocomputation / Data Vizualization / Statistics


Expert in ESRI Products

Remote Sensing




Recent Posts

Download our Poster Here! Introduction The impacts of anthropogenic climate change on the global agriculture industry are projected to become more severe through the end of the 21st century as a result of increased climatic variability (Newberry et al., 2016; Hatfield et al., 2014). In fact, it has been estimated that the warming global climate has already reduced global crop production by 1-5% per decade since the 1980s (Porter et al.


Formatting CO2 Data for Use in R In this post I will describe my workflow for formatting CO2 Data for use within R statistical software. CO2 data was collected using two sensors, a Vaisalla GNP-222 and and eosense eosFD Soil CO2 Flux Sensor. While these are the sensors I use, the workflow should be similar regardless of the sensor. The Vaisala collects CO2 readings only. The eosense collects CO2, CO2 Flux, and temperature.


NC State Fair Attendance Check out this interactive plot on NC State Fair Attendance by day of the fair and colored by year. I have been playing around with plotly visualizations and in the spirit of the North Carolina State Fair, wanted to show how the attendance changes by day of the fair and through the years. The code I used to create this plot can be found below.


Check out our work on Carbon Flux in North Carolina freshwater streams. We are using an eosense carbon flux sensor alongside four Vaisala GMP222 CO2 Sensors to understand the rates at which Carbon leaves freshwater systems in a variety of discharge scenarios. Sensor testing is now complete for the eosense carbon flux sensor, as well as our CO2 Soil Sensors. We are currently preparing the instruments for field deployment (Hopefully mid to late October).


Update Follow along with my research on understanding domestic wells at risk to effects from methane migration stemming from hydraulic fracturing activity. This living document is being created in the spirit of open and reproducible research. Most of the analysis is done with the R statistical language and is presented exactly as executed. All of the data is free and publicly accessible. This will allow others to reproduce everything exactly, or plug in their own data.



Deal Me In

Deal Me In is a web application under active development. It is a map-based application meant to help discover daily and happy hour food and drink specials. Users can select the day of the week and explore active specials at restaurants and bars close to them. They can also use the form to add restaurants and bars that they visit. Check back often to see the latest updates.

Selected Publications

Two methods are developed to update estimates of the areal density of well use using readily accessible data. The first uses well logs reported to the states and the addition of housing units reported to the Census Bureau at the county, census tract and census block group scales. The second uses housing units reported to the Census and an estimated well use fraction. To limit the scope and because of abundant data, Oklahoma was used for a pilot project. The resulting well density estimates were consistent among spatial scales, and were statistically similar.
In STOTEN, 2017

Recent Publications

. Comparison of Satellite Reflectance Algorithms for Estimating Phycocyanin Values and Cyanobacterial Total Biovolume in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations. In RSE, 2017.

Article Link

. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations. In RSE, 2016.

Article Link

Recent & Upcoming Talks

I will present a sensitivity analysis using the range of identified casing failure rates to quantify the number of domestic wells potentially at risk of contamination from methane migration from unconventional shale gas development. To estimate exact well locations from census block aggregations , a Monte Carlo simulation is used to approximate the likelihood of specific well locations within a 1 km radius of a well pad. Using lower and upper bounds of failure rates combined with a national database of unconventional gas well operations, potential impacts are quantified and shown as geographical hot spots to identify areas of possible concern relating to the contamination of domestic water supplies. Come check it out!


I am a teaching assistant for the following courses at UNC - Chapel Hill:

  • Geog 110: Blue Planet
  • Geog 111: Weather and Climate


  • 3101 Murray Hall, University of North Carolina, Chapel Hill, 27514, USA
  • Office Hours: Mondays and Wednesdays 9:30 to 11:00 or email for appointment