scholarly journals Mineral Mapping at Lonar Crater Using Remote Sensing

2020 ◽  
Vol 64 (02) ◽  
pp. 359-365
Author(s):  
Ranjana Gore ◽  
Abhilasha Mishra ◽  
Ratnadeep Deshmukh
2017 ◽  
Vol 33 (2) ◽  
pp. 255-274 ◽  
Author(s):  
Azam Soltaninejad ◽  
Hojjatollah Ranjbar ◽  
Mehdi Honarmand ◽  
Sara Dargahi

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 328 ◽  
Author(s):  
Na Li ◽  
Xinchen Huang ◽  
Huijie Zhao ◽  
Xianfei Qiu ◽  
Kewang Deng ◽  
...  

To analyze the influence factors of hyperspectral remote sensing data processing, and quantitatively evaluate the application capability of hyperspectral data, a combined evaluation model based on the physical process of imaging and statistical analysis was proposed. The normalized average distance between different classes of ground cover is selected as the evaluation index. The proposed model considers the influence factors of the full radiation transmission process and processing algorithms. First- and second-order statistical characteristics (mean and covariance) were applied to calculate the changes for the imaging process based on the radiation energy transfer. The statistical analysis was combined with the remote sensing process and the application performance, which consists of the imaging system parameters and imaging conditions, by building the imaging system and processing models. The season (solar zenith angle), sensor parameters (ground sampling distance, modulation transfer function, spectral resolution, spectral response function, and signal to noise ratio), and number of features were considered in order to analyze the influence factors of the application capability level. Simulated and real data collected by Hymap in the Dongtianshan area (Xinjiang Province, China), were used to estimate the proposed model’s performance in the application of mineral mapping. The predicted application capability of the proposed model is consistent with the theoretical analysis.


2019 ◽  
Vol 11 (2) ◽  
pp. 428 ◽  
Author(s):  
Ziwu Pan ◽  
Junjie Liu ◽  
Liqun Ma ◽  
Fengrui Chen ◽  
Guchang Zhu ◽  
...  

Predictions of prospectivity based on remote sensing were developed using alteration mineral indicative hyperspectral mapping and remote sensing anomaly filtering, combined with geological characteristics and anomalous mineral field verification. Based on the results of the hyperspectral mineral mapping and the actual geological ground conditions, the results of mapping of altered minerals, such as chlorite, muscovite, kaolinite, and iron oxide were validated, and gold, silver, copper, nickel, and other geochemical anomaly areas were identified for verification work. The results of hyperspectral mineral extraction show that the mineral assemblage closely related to gold deposits in shear zones is muscovite + chlorite + epidote + kaolinite. This alteration mineral assemblage can be used as regional search criteria for shear zone gold mineralisation and was the basis for the discovery of mineralised hydrothermal alteration centres and delineation of four prospective targets. Established on a spectral prospectivity model of the study area, prospective ore-bearing areas have been delineated, which indicate the direction for further geological and mineral resource surveys.


2020 ◽  
Author(s):  
Carsten Laukamp ◽  
Maarten Haest ◽  
Thomas Cudahy

Abstract. The integration of surface and subsurface geoscience data is critical for efficient and effective mineral exploration and mining. Publicly accessible datasets to evaluate the various geoscience analytical tools and their effectiveness for characterisation of mineral assemblages and lithologies or discrimination of ore from waste are however scarce. The open access Rocklea Dome 3D Mineral Mapping Test Data Set (Laukamp, 2020; https://doi.org/10.25919/5ed83bf55be6a) provides an opportunity for evaluating proximal and remote sensing data, validated and calibrated by independent geochemical and mineralogical analyses, for exploration of channel-iron deposits (CID) through cover. We present hyperspectral airborne, surface and drill core reflectance spectra collected in the visible-near infrared and shortwave infrared wavelength ranges (VNIR-SWIR; 350 to 2500 nm), as well as whole rock geochemistry obtained by means of X-Ray fluorescence analysis and loss on ignition measurements of drill core samples. The integration of surface with subsurface hyperspectral data collected in the frame of previously published Rocklea Dome 3D Mineral Mapping case studies demonstrated that about 30 % of exploration drill holes were sunk into barren ground and could have been of better use, located elsewhere, if airborne hyperspectral imagery had been consulted for drill hole planning. The remote mapping of transported Tertiary detritals (i.e. potential hosts of channel iron ore resources) versus weathered in situ Archaean geology (i.e. barren ground) has significant implications for other areas where cover (i.e. regolith and/or sediments covering bedrock hosting mineral deposits) hinders mineral exploration. Hyperspectral remote sensing represents a cost-effective method for regolith landform mapping required for planning drilling programs. In the Rocklea Dome area, vegetation unmixing methods applied to airborne hyperspectral data, integrated with subsurface data, resulted in seamless mapping of ore zones from the weathered surface to the base of the CID – a concept that can be applied to other mineral exploration and mineral deposit studies. Furthermore, the associated, independent calibration data allowed to quantify iron oxide phases and associated mineralogy from hyperspectral data. Using the Rocklea Dome data set, novel geostatistical clustering methods were applied to the drill core data sets for ore body domaining that introduced scientific rigour to a traditionally subjective procedure, resulting in reproducible objective domains that are critical for the mining process. Beyond the already published case studies, the Rocklea Dome 3D Mineral Mapping Test Data Set has the potential to develop new methods for advanced resource characterisation and develop new applications that aid exploration for mineral deposits through cover. The here newly presented white mica and chlorite abundance maps derived from airborne hyperspectral highlight the additional applications of remote sensing for geological mapping and could help to evaluate newly launched hyper- and multispectral spaceborne systems for geoscience and mineral exploration.


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