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

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2022-01-31 DOI:10.1080/20964471.2021.2017111
B. Xie, S.Y. Zhou, L. Wu, W.F. Mao, Wen Wang
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引用次数: 2

Abstract

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.
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RockSL:一个集成的岩石光谱库,提供更好的全球共享服务
不同岩石和矿物的光谱数据通常在可见光和红外波段表现出不同的波形和吸收特征,从而可以识别矿物的种类和成分。然而,地球表面岩石/矿物的大量光谱分布在世界各地的各种光谱库中,数据结构和测量条件不一致。为了提高数据的互操作性和数据的可用性,我们收集了6个不同格式的共享库的数据和信息,并在实验室测量了现场样品,建立了一个集成的岩石光谱库(RockSL)。光谱曲线的数据质量和描述性元数据的完整性都被考虑在集成的RockSL中发布到GitHub开源存储库中。RockSL不仅包含用于数据服务(即数据共享和检索)和地质判别的岩石和矿物大光谱数据集,还包含用于数据挖掘和知识发现探索的关键参数/元数据(如粒度、矿物成分和全波段特征等)特征数据集。我们希望有更多的研究人员加入进来,提高RockSL在遥感领域的可用性和实用价值。本文介绍了数据库结构和数据处理流程,并演示了一个匹配服务和几个RockSL的特征数据集示例。
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来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
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