RockSL: an integrated rock spectral library for better global shared services

ABSTRACT

Spectral data of different rocks and minerals usually show different waveforms and absorption characteristics in visible and infrared wavelengths, which allow identification of mineral species and composition. However, massive spectra of rock/mineral on earth surface were scattered across a variety of spectral libraries worldwide, exhibiting inconsistent data structures and measurement conditions. To advance the data interoperability and the data usability, we collected data and information from six shared libraries with different format and measured field specimen in laboratory to establish an integrated rock spectral library (RockSL). Both the data quality of spectral curves and the integrity of descriptive metadata are considered in the integrated RockSL to be published in GitHub open-source repository. RockSL contains not only the big spectral dataset of rocks and minerals for data service (i.e. data sharing and retrieval) and geological discrimination, but also the characteristics dataset of key parameters/metadata (e.g. particle size, mineral composition and full-band signature, etc.) for exploration of data mining and knowledge discovery. We hope that more researchers will join to improve the availability and practical value of RockSL for remote sensing community. This article introduces the database structure and data processing workflow, and demonstrates a matching service and several examples of characteristic datasets of RockSL.

KEYWORDS:

• Rocks and minerals
• data interoperability
• integrated library
• geological discrimination
• characteristic datasets

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The integrated spectral library (RockSL) described in this article is openly available on GitHub at https://github.com/CSU-PCP-XBS/spectral-dataset-RockSL.

Additional information

Funding

This work was jointly supported by the Key Program of National Nature Science Foundation of China [41930108], Basic Science Center by the National Natural Science Foundation of China [72088101], the innovation leading program of Central South University under Grant 506030101, and the Talents gathering program of Hunan Province China under Grant People’s Government of Hunan province People’s Government of Hunan province 2018RS3013.

Notes on contributors

B.S. Xie

Busheng Xie is a Ph.D. student in Geo-science and Info-Physics school of Central South University. He obtained his bachelor’s degree in Geomatics Engineering from Central South University in China. His current research focuses on data organization, analysis and visualization of hyperspectral remote sensing and geo-science.

S.Y. Zhou

Shengyu Zhou received a MS degree from Central South University in 2021. His research interests include spectral database analysis in mining area.

L.X. Wu

Lixin Wu received a BS degree in mining survey from China University of Mining and Technology, Xuzhou, China in 1988 and MS and PhD degrees in geomatics from China University of Mining and Technology (Beijing), Beijing, China in 1991 and 1997, respectively. He is working with Central South University, Changsha, China as a leading professor of Geomatics in the School of Geoscience and Info-physics. Dr. Wu is currently an academician of the International Eurasian Academy of Sciences (IEAS). He was a former Co-Chair of User Applications in Remote Sensing Committee, IEEE Geoscience, and Remote Sensing Society. He is currently a member of the Global Risk Assessment Framework (GRAF) Expert Group of the United Nations, a member of the Infrastructure Implementation Board of Group on Earth Observation (GEO), the Chairman of WG III-8 of International Society for Photogrammetry and Remote Sensing (ISPRS), a member of the China National Committee of the International Society for Digital Earth (ISDE), the Vice Chairman of the Space Observation Committee of the China Seismology Society, and the Editor-in-Chief of the Journal of Geography and Geo-Information Science (Chinese).

W.F. Mao

Wenfei Mao received the B.S. and master’s degrees from Jilin University, Changchun, China, in 2011 and 2015, respectively, and the Ph.D. degree in digital mine engineering from Northeastern University, Shenyang, China, in 2020.He is currently working as a Post Doctor with Central South University, Changsha, China. His research interests include geohazards remote sensing and remote sensing rock mechanics (RSRM).

W. Wang

Wei Wang was born in 1989 in Hunan, China. He is currently an associate professor in the School of Geoscience and Info-Physics of Central South University. He received his Ph.D. in Photogrammetry and Remote Sensing from Wuhan University in 2017. His research interests include optical and laser remote sensing, remote sensing of atmospheric environment, point cloud processing and application.