scholarly journals Shortwave infrared hyperspectral imaging as a novel method to elucidate multi-phase dolomitization, recrystallization, and cementation in carbonate sedimentary rocks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Cole A. McCormick ◽  
Hilary Corlett ◽  
Jack Stacey ◽  
Cathy Hollis ◽  
Jilu Feng ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Spatial Information ◽  
Analytical Techniques ◽  
Endmember Extraction ◽  
Spectral Angle Mapper ◽  
Distribution Maps ◽  
Spectral Contrast ◽  
Saddle Dolomite ◽  
Multi Phase ◽  
Shortwave Infrared

AbstractCarbonate rocks undergo low-temperature, post-depositional changes, including mineral precipitation, dissolution, or recrystallisation (diagenesis). Unravelling the sequence of these events is time-consuming, expensive, and relies on destructive analytical techniques, yet such characterization is essential to understand their post-depositional history for mineral and energy exploitation and carbon storage. Conversely, hyperspectral imaging offers a rapid, non-destructive method to determine mineralogy, while also providing compositional and textural information. It is commonly employed to differentiate lithology, but it has never been used to discern complex diagenetic phases in a largely monomineralic succession. Using spatial-spectral endmember extraction, we explore the efficacy and limitations of hyperspectral imaging to elucidate multi-phase dolomitization and cementation in the Cathedral Formation (Western Canadian Sedimentary Basin). Spectral endmembers include limestone, two replacement dolomite phases, and three saddle dolomite phases. Endmember distributions were mapped using Spectral Angle Mapper, then sampled and analyzed to investigate the controls on their spectral signatures. The absorption-band position of each phase reveals changes in %Ca (molar Ca/(Ca + Mg)) and trace element substitution, whereas the spectral contrast correlates with texture. The ensuing mineral distribution maps provide meter-scale spatial information on the diagenetic history of the succession that can be used independently and to design a rigorous sampling protocol.

scholarly journals Identification of peat type and humification by laboratory VNIR/SWIR hyperspectral imaging of peat profiles with focus on fen-bog transition in aapa mires

2020 ◽  
Author(s):  
L. Granlund ◽  
M. Keinänen ◽  
T. Tahvanainen
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Support Vector ◽  
High Resolution Imaging ◽  
Factors Affecting ◽  
Vector Machines ◽  
Resolution Imaging ◽  
Shortwave Infrared ◽  
Type Classification ◽  
Wide Potential

Abstract Aims Hyperspectral imaging (HSI) has high potential for analysing peat cores, but methodologies are deficient. We aimed for robust peat type classification and humification estimation. We also explored other factors affecting peat spectral properties. Methods We used two laboratory setups: VNIR (visible to near-infrared) and SWIR (shortwave infrared) for high resolution imaging of intact peat profiles with fen-bog transitions. Peat types were classified with support vector machines, indices were developed for von Post estimation, and K-means clustering was used to analyse stratigraphic patterns in peat quality. With separate experiments, we studied spectral effects of drying and oxidation. Results Despite major effects, oxidation and water content did not impede robust HSI classification. The accuracy between Carex peat and Sphagnum peat in validation was 80% with VNIR and 81% with SWIR data. The spectral humification indices had accuracies of 82% with VNIR and 56%. Stratigraphic HSI patterns revealed that 36% of peat layer shifts were inclined by over 20 degrees. Spectral indices were used to extrapolate visualisations of element concentrations. Conclusions HSI provided reliable information of basic peat quality and was useful in visual mapping, that can guide sampling for other analyses. HSI can manage large amounts of samples to widen the scope of detailed analysis beyond single profiles and it has wide potential in peat research beyond the exploratory scope of this paper. We were able to confirm the capacity of HSI to reveal shifts of peat quality, connected to ecosystem-scale change.

scholarly journals Mineral Detection Using Sharpened VNIR and SWIR Bands of Worldview-3 Satellite Imagery

2021 ◽  
Vol 13 (10) ◽  
pp. 5518
Author(s):  
Honglyun Park ◽  
Jaewan Choi
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Near Infrared ◽  
False Negative ◽  
Similarity Score ◽  
Majority Voting ◽  
Similarity Analysis ◽  
Spectral Angle Mapper ◽  
Mineral Detection ◽  
Shortwave Infrared

Worldview-3 satellite imagery provides panchromatic images with a high spatial resolution and visible near infrared (VNIR) and shortwave infrared (SWIR) bands with a low spatial resolution. These images can be used for various applications such as environmental analysis, urban monitoring and surveying for sustainability. In this study, mineral detection was performed using Worldview-3 satellite imagery. A pansharpening technique was applied to the spatial resolution of the panchromatic image to effectively utilize the VNIR and SWIR bands of Worldview-3 satellite imagery. The following representative similarity analysis techniques were implemented for the mineral detection: the spectral angle mapper (SAM), spectral information divergence (SID) and the normalized spectral similarity score (NS3). In addition, pixels that could be estimated to indicate minerals were calculated by applying an empirical threshold to each similarity analysis result. A majority voting technique was applied to the results of each similarity analysis and pixels estimated to indicate minerals were finally selected. The results of each similarity analysis were compared to evaluate the accuracy of the proposed methods. From that comparison, it could be confirmed that false negative and false positive rates decreased when the methods proposed in the present study were applied.

scholarly journals Overview of Popular Techniques of Raman Spectroscopy and Their Potential in the Study of Plant Tissues

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1537
Author(s):  
Aneta Saletnik ◽  
Bogdan Saletnik ◽  
Czesław Puchalski
Keyword(s):  
Raman Spectroscopy ◽  
Cell Walls ◽  
Structural Changes ◽  
Spatial Information ◽  
Technological Development ◽  
Analytical Techniques ◽  
High Sensitivity ◽  
Plant Tissues ◽  
Wide Range ◽  
Identification Technique

Raman spectroscopy is one of the main analytical techniques used in optical metrology. It is a vibration, marker-free technique that provides insight into the structure and composition of tissues and cells at the molecular level. Raman spectroscopy is an outstanding material identification technique. It provides spatial information of vibrations from complex biological samples which renders it a very accurate tool for the analysis of highly complex plant tissues. Raman spectra can be used as a fingerprint tool for a very wide range of compounds. Raman spectroscopy enables all the polymers that build the cell walls of plants to be tracked simultaneously; it facilitates the analysis of both the molecular composition and the molecular structure of cell walls. Due to its high sensitivity to even minute structural changes, this method is used for comparative tests. The introduction of new and improved Raman techniques by scientists as well as the constant technological development of the apparatus has resulted in an increased importance of Raman spectroscopy in the discovery and defining of tissues and the processes taking place in them.

scholarly journals Chemometric Tools for NIRS and NIR Hyperspectral Imaging

2012 ◽  
Vol 69 (1) ◽  
Author(s):  
Laura M. DALE ◽  
André THEWIS ◽  
Ioan ROTAR ◽  
Juan A. FERNANDEZ PIERNA ◽  
Christelle BOUDRY ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Agricultural Sector ◽  
Spatial Information ◽  
Imaging System ◽  
Agricultural Products ◽  
Chemical Information ◽  
Special Focus ◽  
Large Area ◽  
Analytical Tools

Nowadays in agriculture, new analytical tools based on spectroscopic technologies are developed. Near Infrared Spectroscopy (NIRS) is a well known technology in the agricultural sector allowing the acquisition of chemical information from the samples with a large number of advantages, such as: easy to use tool, fast and simultaneous analysis of several components, non-polluting, noninvasive and non destructive technology, and possibility of online or field implementation. Recently, NIRS system was combined with imaging technologies creating the Near Infrared Hyperspectral Imaging system (NIR-HSI). This technology provides simultaneously spectral and spatial information from an object. The main differences between NIR-HSI and NIRS is that many spectra can be recorded simultaneously from a large area of an object with the former while with NIRS only one spectrum was recorded for analysis on a small area. In this work, both technologies are presented with special focus on the main spectrum and images analysis methods. Several qualitative and quantitative applications of NIRS and NIR-HSI in agricultural products are listed. Developments of NIRS and NIR-HSI will enhance progress in the field of agriculture by providing high quality and safe agricultural products, better plant and grain selection techniques or compound feed industry’s productivity among others.

scholarly journals Comparison of spectral selection methods in the development of classification models from visible near infrared hyperspectral imaging data

2019 ◽  
Author(s):  
Aoife Gowen ◽  
Jun-Li Xu ◽  
Ana Herrero-Langreo
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Spatial Information ◽  
Hyperspectral Image ◽  
Imaging Spectroscopy ◽  
Model Performance ◽  
Data Sampling ◽  
Classification Models ◽  
Imaging Data ◽  
Selection Of

Applications of hyperspectral imaging (HSI) to the quantitative and qualitative measurement of samples have grown widely in recent years, due mainly to the improved performance and lower cost of imaging spectroscopy instrumentation. Data sampling is a crucial yet often overlooked step in hyperspectral image analysis, which impacts the subsequent results and their interpretation. In the selection of pixel spectra for the calibration of classification models, the spatial information in HSI data can be exploited. In this paper, a variety of sampling strategies for selection of pixel spectra are presented, exemplified through five case studies. The strategies are compared in terms of the proportion of global variability captured, practicality and predictive model performance. The use of variographic analysis as a guide to the spatial segmentation prior to sampling leads to the selection of representative subsets while reducing the variation in model performance parameters over repeated random selection.

Classification of Landscape Sensitivity in the Territory of Cremona

2013 ◽  
Vol 4 (3) ◽  
pp. 63-79 ◽  
Author(s):  
Pier Luigi Paolillo ◽  
Umberto Baresi ◽  
Roberto Bisceglie
Keyword(s):  
Spatial Information ◽  
Analytical Techniques ◽  
Urban System ◽  
Multidimensional Analysis ◽  
Environmental Constraints ◽  
Synthetic Indicators ◽  
Territorial Planning ◽  
Landscape Sensitivity ◽  
The Right

Centrality of landscape, in territorial planning, has been influencing for years, the testing of innovative analytical techniques aimed to gather peculiarities of urban and suburban context. The advent of Spatial Information System created the possibility to produce more detailed studies analyzing a lot of information dealing with territorial phenomena of crucial importance in spatial planning. The development of analytical systems based on multidimensional analysis may represent the right way to synthesize different phenomena that interact locally, in order to obtain the intrinsic sensitivity of a specific landscape as a result. In the case of Cremona Urban Variant, the production of thematic maps has allowed the construction of six synthetic indicators, dealing with specific aspects of Cremona landscape. The indicators are: i) insularisation of non – built spaces, ii) morphological / structural values, iii) perceptual landscape aspects, iv) permanence of urban system, v) degree of imperativeness of environmental constraints, vi) integrity of land use.

scholarly journals Characterising the Microstructure of an Additively Built Al-Cu-Li Alloy

Materials ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5188
Author(s):  
Iris Raffeis ◽  
Frank Adjei-Kyeremeh ◽  
Uwe Vroomen ◽  
Silvia Richter ◽  
Andreas Bührig-Polaczek
Keyword(s):  
Volume Fraction ◽  
Analytical Techniques ◽  
High Strength ◽  
High Energy ◽  
Phase System ◽  
X Ray Diffraction ◽  
Powder Bed ◽  
X Ray ◽  
Conventional View ◽  
Multi Phase

Al-Cu-Li alloys are famous for their high strength, ductility and weight-saving properties, and have for many years been the aerospace alloy of choice. Depending on the alloy composition, this multi-phase system may give rise to several phases, including the major strengthening T1 (Al2CuLi) phase. Microstructure investigations have extensively been reported for conventionally processed alloys with little focus on their Additive Manufacturing (AM) characterised microstructures. In this work, the Laser Powder Bed Fusion (LPBF) built microstructures of an AA2099 Al-Cu-Li alloy are characterised in the as-built (no preheating) and preheat-treated (320 °C, 500 °C) conditions using various analytical techniques, including Synchrotron High-Energy X-ray Diffraction (S-HEXRD). The observed dislocations in the AM as-built condition with no detected T1 precipitates confirm the conventional view of the difficulty of T1 to nucleate on dislocations without appropriate heat treatments. Two main phases, T1 (Al2CuLi) and TB (Al7.5Cu4Li), were detected using S-HEXRD at both preheat-treated temperatures. Higher volume fraction of T1 measured in the 500 °C (75.2 HV0.1) sample resulted in a higher microhardness compared to the 320 °C (58.7 HV0.1) sample. Higher TB volume fraction measured in the 320 °C sample had a minimal strength effect.

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