Project SP15c: Assessing image classification methods to predict land cover

Project SP15c: Assessing image classification methods to predict land cover
Researcher: Kevin Sparks
Position type: Data analysis, Land cover classification, programming
Application deadline: 5:00 p.m. on Wednesday, December 17, 2014

Application URL:

Position description

This project aims to test and compare various computational image classification methods in order to predict land cover types given georeferenced on-the-ground photographs of landscapes. With an increase in the availability of earth imagery (Google Earth, Flickr, etc), there have been recent efforts to incorporate these georeferenced data into land cover classification processes. In order to do this, various classification methods for these images need to be analyzed.

Desired qualifications

You as the data analysis will explore various types of image classification methods, participate in discussions about these methods, and test these methods on georeferenced images of landscapes with the goal of predicting land cover types. The analysis will be done using R statistical software, so candidates must have at least minimal programming experience. Candidates will be expected to submit biweekly reports on the progress of your work, and participate in discussion about land cover and classification techniques.

Required: Minimal programming experience. Applicants must be able to work independently with minimal guidance and supervision.

Preferred: Some statistical experience.

Candidates must be willing to contribute 40–120 total hours of work toward the project over the semester, resulting in 1–3 credit hours applied to the transcript. There is no monetary stipend attached to this assistantship, although the experiences gained in this work will be immediately valuable when applying for graduate school or full-time employment.            

To apply

Prospective candidates should submit application to by 5:00 p.m. on Wednesday, December 17, 2014.
A complete application must include:
1. All required fields of online form:

2. A one-page cover letter identifying the position for which you're applying and stating your interest in conducting research, your academic preparation, the skills you hope to gain from this experience, and contact information of two references.

  • Upload a PDF document named as follows: FirstinitialLastname_letterMMYY.pdf (e.g. jvender_letter1114.pdf)

3. A resume

  • Upload a PDF document named as follows: FirstinitialLastname_resumeMMYY.pdf (e.g. jvender_resume1114.pdf)