hyperspectral for coal mining

Based on the theory of coal-bed methane(CBM) geology, the micro-seeps of hydrocarbon cause geochemical alterations in rocks and soil. In this study, the hyperspectral instrument, Hyperion, was used to detect the alterations and hydrocarbons on the land surface of CBM reservoirs. Our study area is in the Qinshui Basin, China. Utilizing Hyperion datasets, the endmember spectra …

Hyperspectral For Coal Mining . Mining & Energy Hyperspectral Intelligence. For mining companies who want to work efficiently while conforming to social distancing rules and travel restrictions, the geoLOGr is a hyperspectral rock analyzer that produces accurate and objective drill core logs for less than $10/meter in an automated and easy-to ...

COAL is a Python library for processing hyperspectral imagery from remote sensing devices such as the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS). COAL provides a suite …

A 91-Channel Hyperspectral LiDAR for Coal/Rock ... Sep 12, 2019 A 91-Channel Hyperspectral LiDAR for Coal/Rock Classification Abstract: During the mining operation, it is a critical task in coal mines to significantly improve the safety by precision coal mining sorting and rock classification from different layers.

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation—partial least …

Introduction to Hyperspectral Imaging ,（pixel）（light intensity）。,、、pixel。（stack of images）。 …

Jan 17, 2016· Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation—partial least squares regression (PLSR) method effectively solves the information loss problem of correlation—multiple linear stepwise regression, but ...

Abstract. Coal mining has environmental impacts on surrounding areas, including heavy metal contamination of soil. This study explores the feasibility of using hyperspectral remote …

Monitoring of hydrochemical parameters of lignite mining . Coal mine drainage is a matter of serious concern Hellier 1999 Azcue 1999 gives an overview of well defined case studies around the world Geochemical and hydrochemical characterizations of mine sites are important for remediation protecting the surrounding environment and monitoring these sites together with …

It implies that a technique for rapidly and accurately classifying coal/rock in-site needs to be investigated and established, which is of significance for improving the coal mining efficiency and safety. In this letter, a 91-channel hyperspectral LiDAR (HSL) using an acousto-optic tunable filter (AOTF) as the… View on IEEE ntnuopen.ntnu.no

Hyperspectral image processing applications 、、。。,： Hyperspectral Image Analysis Using Maximum Abundance Classification and Classify Hyperspectral Image Using Library Signatures and SAM. …

Hyperspectral sensors look at objects using a vast portion of the electromagnetic spectrum. Certain objects leave unique 'fingerprints' in the electromagnetic spectrum. Known as spectral signatures, these 'fingerprints' enable …

Hyperspectral Imaging In The Mining Industry Every object, whether natural or man-made, reflects and absorbs a specific and unique spectral wavelength. This means that it is possible to separate materials like Hematite from Goethite. …

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression Authors Lixin Lin 1 2 3, Yunjia Wang 4 5 6, Jiyao Teng 1 2 3, Xuchen Wang 7 Affiliations 1 School of Environment Science and Spatial Informatics, China …

A 91-Channel Hyperspectral LiDAR for Coal/Rock Classification. Abstract: During the mining operation, it is a critical task in coal mines to significantly improve the safety by precision coal …

In order to get the threshold, aerial hyperspectral images were obtained. The spatial patterns of six soil heavy metals (Cu, Zn, As, Sn, Cr and Cd) were obtained by establishing random forest …

Hyperspectral sensors look at objects using a vast portion of the electromagnetic spectrum. Certain objects leave unique 'fingerprints' in the electromagnetic spectrum. Known as spectral …

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation—partial least squares regression (PLSR) method effectively solves the information loss problem of correlation—multiple linear stepwise regression, but results of the correlation analysis must be …

Coal mining has environmental impacts on surrounding areas, including heavy metal contamination of soil. This study explores the feasibility of using hyperspectral remote sensing to determine the heavy metal (Cr, Ni, Cu, Zn, Cd, Pb) content of soils in a coal-mining area in the city of Zoucheng, Shandong Province, China.

This project will produce maps of surface mineralogy at 15 m spatial resolution covering the largest contiguous area of hyperspectral imagery that has ever been assembled for the U.S., over 380,000 sq. km. in California and Nevada.

Principle of hyperspectral coal and rock identification With the deepening of coal rank, an increase in the degree of aromatic condensation has been observed, along with a reduction in bridge bonds, side chains, and functional groups, which indicate a reduction in the content of ash and volatilization.

Hyperspectral imaging offers a spatial detection method of the mining surface and allows for a classification of mineral- and element distributions to aid an efficient extraction and material...