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lithological mapping with multispectral data–setup and application of a spectral database for rocks in the Balakot area, Northern Pakistan

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Journal of Mountain Science 2017年第5期14卷 948-963页

作者： Michael FUCHS Adnan A.AWAN Sardar S.AKHTAR Ijaz AHMAD Simon SADIQ Asif RAZZAK Naghmah HAIDER Federal Institute for Geosciences and Natural Resources Stilleweg 230655 HanoverGermany Geological Survey of Pakistan IslamabadPakistan

In the frame of landslide susceptibility assessment, a spectral library was created to support the identification of materials confined to a particular region using remote sensing images. This library, called Pakistan spectral library(pklib) version 0.1, contains the analysis data of sixty rock samples taken in the Balakot region in Northern *** spectral library is implemented as SQLite database. Structure and naming are inspired by the convention system of the ASTER Spectral Library. Usability, application and benefit of the pklib were evaluated and depicted taking two approaches, the multivariate and the spectral based. The spectral information were used to create indices. The indices were applied to Landsat and ASTER data tosupportthespatial delineation of outcropping rock sequences instratigraphic formations. The application of the indices introduced in this paper helps to identify spots where specific lithological characteristics occur. Especially in areas with sparse or missing detailed geological mapping, the spectral discrimination via remote sensing data can speed up the survey. The library can be used not only to support the improvement of factor maps for landslide susceptibility analysis, but also to provide a geoscientific basisto further analyze the lithological spotin numerous regions in the Hindu Kush.

关键词： lithological mapping Multispectral data Spectral library Normalized difference index Northern Pakistan

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Spectral indices derived,non-parametric Decision Tree Classification approach to lithological mapping in the Lake Magadi area,Kenya

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International Journal of Digital Earth 2018年第10期11卷 1020-1038页

作者： Gayantha R.L.Kodikara Tsehaie Woldai Department of Oceanography and Marine Geology Faculty of Fisheries&Marine Science and TechnologyUniversity of RuhunaSri Lanka School of Geosciences University of the WitwatersrandJohannesburgSouth Africa

Here,we demonstrate the application of Decision Tree Classification(DTC)method for lithological mapping from multi-spectral satellite *** area of investigation is the Lake Magadi in the East African Rift Valley in *** work involves the collection of rock and soil samples in the field,their analyses using reflectance and emittance spectroscopy,and the processing and interpretation of Advanced Spaceborne Thermal Emission and Reflection Radiometer data through the DTC *** latter method is strictly non-parametric,flexible and simple which does not require assumptions regarding the distributions of the input *** has been successfully used in a wide range of classification *** DTC method successfully mapped the chert and trachyte series rocks,including clay minerals and evaporites of the area with higher overall accuracy(86%).Higher classification accuracies of the developed decision tree suggest its ability to adapt to noise and nonlinear relations often observed on the surface materials in space-borne spectral image data without making assumptions on the distribution of input ***,the present work found the DTC method useful in mapping lithological variations in the vast rugged terrain accurately,which are inherently equipped with different sources of noises even when subjected to considerable radiance and atmospheric correction.

关键词： Decision Tree Classification ASTER data lithological mapping Lake Magadi

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Leucogranite mapping via convolutional recurrent neural networks and geochemical survey data in the Himalayan orogen

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Geoscience Frontiers 2024年第1期15卷 175-186页

作者： Ziye Wang Tong Li Renguang Zuo State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430074China

Geochemical survey data analysis is recognized as an implemented and feasible way for lithological mapping to assist mineral *** respect to available approaches,recent methodological advances have focused on deep learning algorithms which provide access to learn and extract information directly from geochemical survey data through multi-level networks and outputting end-to-end ***,this study developed a lithological mapping framework with the joint application of a convolutional neural network(CNN)and a long short-term memory(LSTM).The CNN-LSTM model is dominant in correlation extraction from CNN layers and coupling interaction learning from LSTM *** hybrid approach was demonstrated by mapping leucogranites in the Himalayan orogen based on stream sediment geochemical survey data,where the targeted leucogranite was expected to be potential resources of rare metals such as Li,Be,and W *** comparative case studies were carried out from both visual and quantitative perspectives to illustrate the superiority of the proposed model.A guided spatial distribution map of leucogranites in the Himalayan orogen,divided into high-,moderate-,and low-potential areas,was delineated by the success rate curve,which further improves the efficiency for identifying unmapped leucogranites through geological *** light of these results,this study provides an alternative solution for lithologic mapping using geochemical survey data at a regional scale and reduces the risk for decision making associated with mineral exploration.

关键词： lithological mapping Deep learning Convolutional neural network Long short-term memory Leucogranites

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Evaluating pixel-based ***-based image analysis approaches for lithological discrimination using VNIR data of WorldView-3

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Frontiers of Earth Science 2021年第1期15卷 38-53页

作者： Samira SHAYEGANPOUR Majid H.TANGESTANI Saeid HOMAYOUNI Robert K.VINCENT Department of Earth Sciences Faculty of SciencesShiraz UniversityShiraz ***Iran Centre Eau Terre Environnement Insitut National de la Recherche ScientifiqueQuebec QCJ3X1S2Canada Department of Geography Bowling Green State UniversityOhio 43403-0001USA

The object-based against pixel-based image analysis approaches were assessed for lithological mapping in a geologically complex terrain using Visible Near Infrared(VNIR)bands of WorldView-3(WV-3)satellite *** study area is Hormuz Island,southern Iran,a salt dome composed of dominant sedimentary and igneous *** performing the object-based image analysis(OBLA)approach,the textural and spectral characteristics of lithological features were analyzed by the use of support vector machine(SVM)***,in the pixelbased image analysis(PBIA),the spectra of lithological end-members,extracted from imagery,were used through the spectral angle mapper(SAM)*** test samples were used in a confusion matrix to assess the accuracy of classification methods *** showed that OBIA was capable of lithological mapping with an overall accuracy of 86.54%which was 19.33%greater than the accuracy of *** also reduced the salt-and-pepper artifact pixels and produced a more realistic map with sharper lithological *** research showed limitations of pixel-based method due to relying merely on the spectral characteristics of rock types when applied to high-spatial-resolution VNIR bands of WorldView-3 *** is concluded that the application of an object-based image analysis approach obtains a more accurate lithological classification when compared to a pixel-based image analysis algorithm.

关键词： object-based image analysis pixel-based image analysis lithological mapping Worldview-3 Hormuz Island spectral angle mapper support vector machine

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mapping salt diapirs and salt diapir-affected areas using MLP neural network model and ASTER data

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International Journal of Digital Earth 2013年第2期6卷 143-157页

作者： Mohammad H.Tayebi Majid H.Tangestani Hasan Roosta Department of Earth Sciences Shiraz UniversityShirazIran Department of Civil Engineering Islamic Azad UniversityLarestanIran

This study employs visible-near infrared and short wave infrared datasets of Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)to map salt diapirs and salt diapir-affected areas using Multi-Layer Perceptron(MLP)in the Zagros Folded Belt,Iran,and introduces the role of earth observation technology and a type of digital earth processing in lithological mapping and geo-environmental impact *** neural network model with several learning rates between 0.01 and 0.1 was carried out on ASTER L1B data,and the results were compared using confusion *** most appropriate classification image for L1B input to MLP was produced by learning rate of 0.01 with Kappa coefficient of 0.90 and overall accuracy of 92.54%.The MLP result of input data set mapped lithological units of salt diapirs and demonstrated affected areas at the southern and western parts of the Konarsiah and Jahani diapirs,*** observations and X-ray diffraction analyses of field samples confirmed the dominant mineral phases identified *** is concluded that MLP is an efficient approach for mapping salt diapirs and salt-affected areas.

关键词： remote sensing digital earth digital image classification MLP neural network lithological mapping salt diapir ASTER Zagros Iran Geology image processing

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