Incorporating Hytools into the current image processing pipeline to produce better vegetation maps that will account for radiometric signals and will parallelize workflow

Project Title: Incorporating Hytools into the current image processing pipeline to produce better vegetation maps that will account for radiometric signals and will parallelize workflow 
Program:
Northeast (308)

Project Image: {Empty}
Tags:
big-data (4), gis (275), hpc-operations (43), image-processing (299), python (69), r (32)

Status: Complete
Project Leader
--------------
Project Leader:
Peter Nelson

Email: peter.nelson@maine.edu
Mobile Phone: {Empty}
Work Phone: (207) 834-8650

Project Personnel
-----------------
Mentor(s):
Larry Whitsel (86)

Student-facilitator(s):
Tolu Oyeniyi (491)

Mentee(s):
{Empty}


Project Information
-------------------
Project Description:
The ability to make use of remote sensing data is of particular interest to the State of Maine, given its large and remote forestry and agricultural resources. Such data occurs at several, vastly different, scales - from satellite imagery all the way down to manual inspections of vegetation. A multi-institution research team led by faculty at the University of Maine at Fort Kent uses aerial drone imagery and technologies referred to as “hyperspectral” cameras or scanners, to identify the species and condition of ground cover across a sizable area of interest. Underlying these technologies is the assumption that each material or target has a unique spectral profile that allows it to be told apart from similar co-occurring targets. The sensors detect dozens or hundreds of spectra in the visible and near infrared red (compared to RGB in a normal camera), which allows for better detection of different targets, including plants, plant stress, chemical signatures of rocks and many other attributes. 

This project enlists a student worker to begin the processes of analyzing and incorporating the hyperspectral image processing pipeline, HyTools, on our cyberinfrastructure to function for our current data. The data to be analyzed includes over 100 Tb of hyperspectral images collected by Unoccupied Aerial Vehicles (UAVs). Configuring HyTools would occur on the Advanced Computing Group (ACG) server cluster. The result will be more useful maps that account for radiometric signals found in the data.


Project Information Subsection
------------------------------
Project Deliverables:
A successful project would get HyTools functioning for the current UAV-based hyperspectral image data set for Maine, convert the programming language of the image processing pipeline into the same programming language used in Hytools, and parallelize any code that is accessible to the research team. In addition, use high performance computing (HPC) to greatly improve the speed that the raw data can be turned into useful maps.


Project Deliverables:
{Empty}

Student Research Computing Facilitator Profile:
Undergraduate student, Tolu Oyeniyi at UMFK is working on this project with Project Leader Asst. Prof. of Biological Sciences and Environmental Studies, Dr. Peter Nelson.

Mentee Research Computing Profile:
{Empty}

Student Facilitator Programming Skill Level: Some hands-on experience
Mentee Programming Skill Level: {Empty}
Project Institution: University of Maine at Fort Kent
Project Address:
Cyr Hall,  University of Maine at Fort Kent
23 University Drive
Fort Kent, Maine. 04743

Anchor Institution: NE-University of Maine
Preferred Start Date: 09/01/2020
Start as soon as possible.: No
Project Urgency: Already behind3Start date is flexible
Expected Project Duration (in months): {Empty}
Launch Presentation: {Empty}
Launch Presentation Date: {Empty}
Wrap Presentation: {Empty}
Wrap Presentation Date: {Empty}
Project Milestones:
{Empty}

Github Contributions: {Empty}
Planned Portal Contributions (if any):
{Empty}

Planned Publications (if any):
TBD

What will the student learn?:
The student will become familiar with:
Dealing with large data sets
High Performance Computing environments
Hytools package and integration with Python and R programming languages

What will the mentee learn?:
{Empty}

What will the Cyberteam program learn from this project?:
Migration of Hyperspectral analysis data sets onto an HPC environment

HPC resources needed to complete this project?:
Project will be conducted on the UMS HPC cluster.

Notes:
{Empty}



Final Report
------------
What is the impact on the development of the principal discipline(s) of the project?:
{Empty}

What is the impact on other disciplines?:
{Empty}

Is there an impact physical resources that form infrastructure?:
{Empty}

Is there an impact on the development of human resources for research computing?:
{Empty}

Is there an impact on institutional resources that form infrastructure?:
{Empty}

Is there an impact on information resources that form infrastructure?:
{Empty}

Is there an impact on technology transfer?:
{Empty}

Is there an impact on society beyond science and technology?:
{Empty}

Lessons Learned:
{Empty}

Overall results:
{Empty}