Mineral Identification and Mapping by Synthesis of Hyperspectral VNIR/SWIR and Multispectral TIR Remotely Sensed Data with Different Classifiers

doi:10.1109/JSTARS.2020.2999057

CORC > 兰州理工大学 > 兰州理工大学 > 土木工程学院

	Mineral Identification and Mapping by Synthesis of Hyperspectral VNIR/SWIR and Multispectral TIR Remotely Sensed Data with Different Classifiers
	Ni, Li 2; Xu, Honggen 1; Zhou, Xiaoming 3
刊名	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
	2020
卷号	13 页码:3155-3163
关键词	Infrared radiation Minerals Photomapping Continuous spectrum Mineral identification Multi-spectral data Orthogonal subspace projection Remotely sensed data Short wave infrared Spectral angle mapping Spectral feature fitting
ISSN号	19391404
DOI	10.1109/JSTARS.2020.2999057
英文摘要	Hyperspectral data, which have fine continuous spectrum, have been recognized to be more suitable for the detailed identification and classification of land surface, especially for minerals. The combination of the hyperspectral visible/near-infrared (VNIR) and shortwave infrared (SWIR) data with the hyperspectral thermal infrared (TIR) data is proven to be an effective way. However, how those effects are and what are the effects of introduction of multispectral TIR data on the minerals identification and classification are not well studied. To fully evaluate those effects, this article tries to use both simulated data and real data to testify the practicability of introduction of multispectral TIR data for the accuracies of mineral identification and classification. Four classifiers, i.e., spectral angle mapping, spectral feature fitting, orthogonal subspace projection, and adaptive coherence/cosine estimator, are selected in the experiment. Compared with the results using hyperspectral data alone, the introducing of multispectral TIR data in identification and classification has improved accuracies for both the simulated and real data. The overall accuracies are improved about 4%-13% for the simulated data and about 1%-5% for the real data by using different classifiers. Those improvements prove that the spectral diagnosed characteristics in TIR region even for multispectral data help identify and classify minerals. Although the improvements for real data are not well obvious due to the low spatial resolution, the multispectral TIR data are still effective supplements for hyperspectral VNIR and SWIR data in mineral identification and classification. © 2008-2012 IEEE.
语种	英语
出版者	Institute of Electrical and Electronics Engineers
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/115721]
专题	土木工程学院
作者单位	1.Wuhan Center of China Geological Survey (Central South China Innovation Center for Geosciences), Wuhan; 430205, China; 2.Aerospace Information Research Institute, Key Laboratory of Digital Earth Science, Chinese Academy of Sciences, Beijing; 100094, China; 3.School of Civil Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Ni, Li,Xu, Honggen,Zhou, Xiaoming. Mineral Identification and Mapping by Synthesis of Hyperspectral VNIR/SWIR and Multispectral TIR Remotely Sensed Data with Different Classifiers[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2020,13:3155-3163.
APA	Ni, Li,Xu, Honggen,&Zhou, Xiaoming.(2020).Mineral Identification and Mapping by Synthesis of Hyperspectral VNIR/SWIR and Multispectral TIR Remotely Sensed Data with Different Classifiers.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,13,3155-3163.
MLA	Ni, Li,et al."Mineral Identification and Mapping by Synthesis of Hyperspectral VNIR/SWIR and Multispectral TIR Remotely Sensed Data with Different Classifiers".IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13(2020):3155-3163.