Analysis of ASTER data for mapping bauxite rich pockets within high altitude lateritic bauxite, Jharkhand, India

Guha, Arindam; Singh, Vivek Kumar; Parveen, Reshma; Kumar, K. Vinod; Jeyaseelan, A. T.; Rao, E. N. Dhanamjaya

doi:10.1016/j.jag.2012.08.003

Cited by 44 publications

(37 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Each scene of ASTER covers 60 × 60 km 2 on land [43]. ASTER provides more spectral bands in the SWIR than say Landsat, which therefor increases its ability to spectrally discriminate minerals and rocks on the Earth's surface [2,13,[44][45][46]. We processed a cloud-free ASTER level 1A scene acquired on 24 August 2003 and provided by the Iraq Geological Survey (GEOSURV-Iraq).…”

Section: Data Characteristics and Softwarementioning

confidence: 99%

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

2014

View full text Add to dashboard Cite

Abstract:The mineral ore potential of many mountainous regions of the world, like the Kurdistan region of Iraq, remains unexplored. For logistical and sometimes political reasons, these areas are difficult to map using traditional methods. We highlight the improvement in remote sensing geological mapping that arises from the integration of geomorphic features in classifications. The Mawat Ophiolite Complex (MOC) is located in the NE of Iraq and is known for its mineral deposits. The aims of this study are: (I) to refine the existing lithological map of the MOC; (II) to identify the best discriminatory datasets for lithological classification, including geomorphic features and textures; and (III) to identify potential locations with high concentrations of chromite. We performed a Support Vector Machine (SVM) classification method to allow the joint use of geomorphic features, textures and multispectral data of the Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite. The updated map allowed the identification of a new mafic body and a substantial improvement of the geometry of the known lithological units. The use of geomorphic features allowed for the increase of the overall accuracy from 73% to 79.3%. In addition, we detected chromite occurrences within the ophiolite by applying Spectral Angle Mapping (SAM) technique. We identified two new locations having high concentrations of chromite and verified one of these promising areas and has coarsely crystalline chromite within dunite host rock. The chromium (Cr 2 O 3 ) concentration is ~8.46%. The SAM and SVM methods applied on ASTER satellite data show that these can be used as a powerful tool to explore ore deposits and to further improve lithological mapping in mountainous semi-arid regions.

show abstract

Section: Data Characteristics and Softwarementioning

confidence: 99%

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

2014

View full text Add to dashboard Cite

show abstract

“…For deriving the reflectance profiles of the rocks, a white lambertian surface is used and this surface is generally known as" white reference" in spectroscopy [22]. The methodology for collecting spectral profiles of rocks is well discussed [8][9][10][11]. The same methodology has been followed for collecting spectral profiles.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, absorption features of reflectance spectra collected from remote / space borne sensors can be used as an important tool for spatial mapping of these rocks. Rock spectroscopy has been used in recent past for characterizing rocks based on their spectral features [8][9][10][11][12][13][14]. In some of these cases, this has been achieved by comparing reflectance profile of a rock with the reflectance profiles of its dominant and characteristic constituent minerals to ascertain the diagnostic spectral features of rock.…”

Section: Introductionmentioning

confidence: 99%

Potentials of Spectrometry in Economic Rocks Mapping -A Brief Analysis for Three Economic Rocks of Three Different Geological Provinces of India

D¹,

Guha²,

K³

et al. 2017

J Remote Sensing & GIS

Self Cite

View full text Add to dashboard Cite

In this research article, we have demonstrated how spectrometric properties of diagnostic absorption features of rocks imprinted in their reflectance spectra can be used to delineate economic rocks (limestone, bauxite and gossans) from the adjacent country rocks. Spectral features or absorption features of rocks, discussed in this paper, are identified based on the comparative analysis of spectral feature of diagnostic constituent minerals of these rocks. It has also been observed that the each economic rock can be separated from their respective "background" country rock(s) based on the combination of certain spectrometric properties (wavelength of absorption feature and asymmetry) of their respective diagnostic absorption features imprinted in their reflectance spectra. The study also revealed that the separability of these economic rocks from their respective host rock will be affected if spectral profiles of mixed set up (where economic rocks are linearly mixed with the associated country rocks within the field of view of spectroradiometer) are collected instead of pure rocks. This observation justifies the fact that size of minimum distinguishable unit (i.e., pixel in case of spectral data presented as a image) of spectral measurement should be less than the size of the exposure/target, for effectively separating one pure target i.e., an economic rock from the associated country rocks.

show abstract

“…As one of the most widely used global DEM data sets, ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) is essential to many application fields, such as topography, geomorphology, hydrology, geology and soil erosion (Frey and Paul 2012;Gichamo et al 2012;Guha et al 2013;Chatterjee et al 2014). The feasibilities of ASTER GDEM's applications depend on its vertical accuracy (Dragut and Eisank 2011;Mukherjee et al 2013), which is important because errors can propagate and impact spatial analysis (Leigh et al 2009;Yue et al 2010a).…”

Section: Introductionmentioning

confidence: 99%

Rectification methods comparison for the ASTER GDEM V2 data using the ICESat/GLA14 data in the Lvliang mountains, China

et al. 2015

View full text Add to dashboard Cite

ASTER GDEM data have high spatial resolution and wide coverage, which are significant in topographic analysis and geographic study. ICESat/GLA14 data can improve the vertical accuracy of ASTER GDEM data based on its abundant points with high vertical accuracy. It is essential to seek a proper rectification method for ASTER GDEM data. In this research, taking the Lvliang Mountains of China as the study area, proper rectification method is explored for the latest version of the ASTER GDEM data (ASTER GDEM V2 data). The ICESat/ GLA14 data are regarded as the real data, so the difference between the two datasets is the vertical error data. The key to rectify the ASTER GDEM V2 data is to seek an appropriate interpolation method to simulate a proper surface for the vertical error data. Through analysis and comparison, four interpolation methods including inverse distance weighted (IDW) method, ordinary kriging (OK) method, simple kriging (SK) method and universal kriging (UK) method are first chosen from numerous interpolation methods. Through comparing the vertical error histograms, the samples and the characteristics of the four interpolation methods, the ICESat/GLA14 data in 2005 are selected as the benchmark to rectify the ASTER GDEM V2 data. Then, the vertical error data are calculated using the difference value between the ASTER GDEM V2 data and the ICESat/GLA14 data. Under optimal configuration the vertical error, the chosen four interpolation methods are used to simulate the surface of the vertical error data. Finally, the rectified results for ASTER GDEM V2 data are achieved by adding the interpolated results to the ASTER GDEM V2 data, and the accuracy of the rectified results is appraised using the ground control points on the topographic maps. The research results show that (1) Accuracy of the rectified results is different by using various interpolation methods. The RMSE value range for all the rectified results is 19.5-26.7 m. (2) Among the four methods, SK is the best; the next are OK and UK methods, which have approximately similar performance, but the UK method is a little worse; on the whole, the IDW method has the worst performance. (3) This research not only provides the optimal parameters for different interpolation methods, but also obtains the appropriate rectification method for ASTER GDEM V2 data using ICESat/GLA14 data, which is beneficial for broader range of applications using ASTER GDEM V2 data in topographic and geographic research.

show abstract

Analysis of ASTER data for mapping bauxite rich pockets within high altitude lateritic bauxite, Jharkhand, India

Cited by 44 publications

References 25 publications

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

Improving Lithological Mapping by SVM Classification of Spectral and Morphological Features: The Discovery of a New Chromite Body in the Mawat Ophiolite Complex (Kurdistan, NE Iraq)

Potentials of Spectrometry in Economic Rocks Mapping -A Brief Analysis for Three Economic Rocks of Three Different Geological Provinces of India

Rectification methods comparison for the ASTER GDEM V2 data using the ICESat/GLA14 data in the Lvliang mountains, China

Contact Info

Product

Resources

About