Coal and Open-pit surface mining impacts on American Lands Follow-On (COAL-FO)

Name: Lewis John McGibbney
Affiliation: NASA Jet Propulsion Laboratory
Phone: +16264873476
E-mail: lewis.mcgibbney@gmail.com
Website: https://capstone-coal.github.io
Knowledge Required: It is essential that Engineering team have a rooted interest in image processing and analysis technologies as well as an understanding (or aptitude to learn about) scientific data formats such as netCDF, HDF, GIS formats, etc. Students must be reasonably fluent in Python and C/C++ programming languages. Engineering team should be fluent in *nix system navigation and administration. Experience using HPC systems is beneficial. Candidates should be VERY prepared to work with Open Source communities (primarily at the Python communities and possibly communities within the Apache Software Foundation) to find solutions and develop open source solutions based upon their own willing and initiative. All code will be permissively licensed under either the Apache License v2.0 (COAL SDS) or GNU GPLv2 (pycoal library).
Motivation: This project will deliver COAL-FO - Coal and Open-pit surface mining impacts on American Lands Follow On - various improvements to the existing COAL suite of algorithms to identify, classify, characterize, and quantify (by reporting a number of key metrics) the direct and indirect impacts of mining and related destructive surface mining activities across the continental U.S (and further afield).
Description: Coal and Open-pit surface mining impacts on American Lands Follow-On (COAL-FO) is the successor project to the 2016-2017 COAL project. COAL initially aimed to deliver a suite of algorithms to identify, classify, characterize, and quantify (by reporting a number of key metrics) the direct and indirect impacts of mining operations and related destructive surface mining activities across the continental U.S (and further afield). COAL successfully delivered a Python library for processing hyperspectral imagery from remote sensing devices such as the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) and a Science Data System for running COAL pipelines. COAL-FO will utilize recent funding obtained from a recently awarded NSF-funded XSEDE high performance computing (HPC) grant to further improve, validate and document COAL algorithms, execution runtime performance and geospatial output results.
Objectives: (i) Work with the NASA JPL team to utilize imagery from NASA airborne missions such as AVIRIS-Classic and AVIRIS-Next Generation to improve on the existing suite of COAL imagery processing algorithms that identify mining activity across the U.S. dating from ~1980 to present. Examples of such activity are located within the central Appalachian regions of the eastern United States where the U.S. Environmental Protection Agency (EPA) estimated 2,200 square miles (5,700 km2) of Appalachian forests were cleared for MTM sites by the year 2012, with over 500 mountaintops being destroyed due to MTM activity; (ii) Eventually, enable improved accuracy of correlations between proximity of mining activities and their effects e.g. acid mine drainage, to streams, rivers, estuaries, etc. through use of hydrology, dam and reservoir datasets such as the Global Reservoir and Dam Database (GRaND) and other water system datasets such as the National Hydrography Dataset (NHD). EPA impact statements have found that streams in valley filling from mining-affected watersheds contain higher levels of minerals in the water and decreased aquatic biodiversity. Mine-affected streams also have high selenium concentrations, which can bioaccumulate and produce toxic effects (e.g., reproductive failure, physical deformity, mortality), and affect reservoirs below such streams; and (iii) Provide a baseline suite of reporting metrics which will appropriately rank and document the changes within land and solid earth areas and hydrological waterways as observed over time; finally (iv) extend COAL as a set of reusable components which can be used in cloud-based platforms such as the XSEDE HPC resources.
Deliverables: 1. Improve and augment the existing COAL architecture and systems engineering document that defines the scope of the COAL software suite. 2. Provide a schedule of works that defines milestones and timelines for achieving 1 above. 3. Deliver on subtasks which address parallel development of a) Improvements to the suite of imagery processing algorithms that identify, classify, characterize, and quantify mining activity across the U.S. dating from ~1980 to present. b) Tests for such algorithms c) Benchmarking and documenting use of COAL-FO on the XSEDE HPC infrastructure enabled by the startup allocation.
Other comments: 2017-2018 will be our 4th Capstone project engagement with OSU. Our 2014-2015 project iPReS; The Internationalization Product Retrieval Service was a success. Details of iPReS can be found here - http://lewismc.github.io/iPReS/, and our 2015-2016 efforts ARIA-P are documented at http://aria-p.github.io. In 2016-2017 we worked on COAL (described within the COAL-FO proposal) https://capstone-coal.github.io which won two awards, namely the CH2M Multidisciplinary Collaboration Award and an XSEDE Startup Request. We very much look forward to engaging with the current Capstone initiative and look forward to meeting our students.

   D. Kevin McGrath
   Last modified: Fri Oct 20 09:31:13 2017