Code Record

2019-11-05

[DOI: 10.21982/42yk-c774] pycoal
McGibbney, Lewis
Python library for processing hyperspectral imagery from remote sensing devices such as the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS & AVIRISNG). The toolkit provides a suite of algorithms and CLI for classifying land cover, identifying mines and other geographic features, and correlating them with environmental data sets.

Code Link: pycoal.zip
Code Size: 40208773 bytes
Code MD5 Checksum: 036dc6c97bb937e357cc3d72ecae56a9


Code Access Instructions: The project website at (https://capstone-coal.github.io/) contains all documentation and examples. The source code is also available from https://github.com/capstone-coal/pycoal. pycoal is packaged and made available on both Pypi and Conda.

Appears in: [1] Brown, T. A., McGibbney, L. J. (2017), Coal and Open-pit surface mining impacts on American Lands (COAL), Abstract IN31B-0082 presented at 2017 Fall Meeting, AGU, New Orleans, LA, 11-15 Dec.

[2] McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT MINING IMPACTS ON AMERICAN LANDS (COAL): A PYTHON LIBRARY FOR PROCESSING HYPERSPECTRAL IMAGERY", 2017 Conference on Big Data from Space (BiDS'17) Research, Technology and Innovation, 28-30 November 2017 Centre de Congrès Pierre Baudis, Toulouse, France

[3] McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT SURFACE MINING IMPACTS ON AMERICAN LANDS (COAL)", 2017 Conference on Big Data from Space (BiDS'17) Research, Technology and Innovation, 28-30 November 2017 Centre de Congrès Pierre Baudis, Toulouse, France

[4] McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT SURFACE MINING IMPACTS ON AMERICAN LANDS (COAL)", 2017 HyspIRI Science and Applications Workshop, 17-19 October 2017 California Institute of Technology Beckman Institute Auditorium 1200 E California Blvd Pasadena, CA

[5] McGibbney, L. J., Brown, T. A., Clayton, H. A., Wang, X. (2017) "COAL AND OPEN-PIT MINING IMPACTS ON AMERICAN LANDS (COAL): A PYTHON LIBRARY FOR PROCESSING HYPERSPECTRAL IMAGERY", Oregon State University Undergraduate Engineering Expo 2017, 19 May 2017 Kelley Engineering Center, Johnson Hall, Oregon State University

Code Languages: Python

To compile code: Python 3.7 or later. Available on Conda in following specifications: linux-64, win-32, win-64, osx-64.

Sensor Categories: Microwave Spectrometer

Geophysical Model: Inverse

Geophysical Categories: Land: Forest Biomass/Structure, Land: Land Cover/Land Use, Land: Crops, Land: Urban Map/Structures, Land: GIS, Land: Other

Keywords: coal,open surface mining,surface mining activities,python,classification algorithm,classification,hyperspectral pixel classification