Satellite Remote Sensing Analysis Platform

Satellite Remote Sensing Analysis Platform

RemoteSensing

This faculty research team is working to develop an open-source software platform for analysis of remotely sensed data. Students on the team will develop all the components of the platform for enabling its use by a wide variety of users who apply it to wide variety of applications. The components to be developed include:

  1. C++ library for data storage and processing for satellite imagery, elevation maps, land cover maps, vectors and polygons, 2D and 3D meshes and solid models
  2. Python library and applications for command-line and GUI interaction with the library and the datasets
  3. Web library and applications for image and geographic processing, analysis, and web interactions
  4. Integration of existing high-level analysis codes into the platform
  5. Development of educational modules, including written, web-based, video and multi-media versions
  6. Use of data and metadata standards to provide for interoperability with other systems

Activities in each topic area will be tailored to a range of undergraduate and graduate skill levels and knowledge bases. An existing open-source framework will be the inspiration for the new design and implementation effort.

Students who successfully match to this faculty research team will be required to sign the following document in January 2018:

Student IP Agreement for Faculty Research Teams

2018 Terms and Conditions

How to Apply

Project Features

  • Skill level All levels
  • Students 4-11 Students
  • Likely Majors CEE, CLaSP, CE, CS, EE, SI, SNRE
  • Course Substitutions MIDAS, ECE Cognate
  • IP & NDA Required? Yes
  • Summer Opportunity Summer Funding Application
  • Image Processing Library Subteam (3 Students)

    Preferred Skills: interest in/experience with C++ and Linux applications (obtainable in EECS 280)

    • Likely Majors: EE, CSE/CS-LSA, CE, CLaSP, I(SI), GRAD
  • Vector Processing Library Subteam (3 Students)

    Preferred skills: experience with C/C++/Linux, completion of EECS 280

    • Likely Majors: EE, CSE/CS-LSA, CE, CEE, SNRE, GRAD
  • Python Library & GUI Subteam (3 Students)

    Preferred Skills: interest in C/C++, completion of EECS 280

    • Likely Majors: EE, CSE/CS-LSA, CE, I(SI), GRAD
  • Apprentice Researcher (2 Students)

    Requirements: interest in project material, willingness to develop skills. OPEN TO FRESHMEN AND SOPHOMORES ONLY.

    • Likely Majors: Any

Faculty Sponsor: Leland PierceJustin Kasper
Research Scientist, Electrical Engineering and Computer Science
Dr. Leland Pierce is a Research Scientist in the EECS Department who has been involved in remote sensing data processing for the past 25 years. He has been working on the first version of this framework for the past 4 years.