Study on lithologic character and mineral identification technology based on UAV hyperspectral image
The unmanned aerial vehicle(UAV)hyperspectral remote sensing technology has achieved rapid development in geological exploration due to its versatility and flexibility.In this paper,The UAV was equipped with a full-spectrum hyperspectral imager(HD_SAVI)to capture hyperspectral image data,The image reached a spatial resolution up to 0.2 meters and was radiometrically corrected using the empirical linear method with the standard reflectance material deployed in the survey area.The corrected hyperspectral image was highly agree with ground-measured spectra and the deviations of typical feature absorption wavelength within one pixel.Lithological sample spectra were collected to set the knowledge base for the rock type identification by deep learning algorithms.Mineral identification was performed using a standard mineral spectral library,and structural identification was carried out using edge detection operators.These was followed by a comparative analysis with results from CASI/SASI airborne hyperspectral geological mapping in the same region.The results indicated that the minerals extracted from both hyperspectral datasets show a high level of consistency in spatial distribution.The low-altitude hyperspectral imagery captured by the UAV system has a higher spatial resolution,allowing for the identification of a larger scale mapping of rock types and minerals.The comparison of lithology identification results with large-scaled geological maps shows that the spatial distribution of lithology is basically consistent,and the boundaries of pluton was relatively clearer.Therefore,unmanned aerial vehicle hyperspectral remote sensing technology can meet the needs of geological prospection on areas of depopulation and inaccessiable transportation,and the large-scaled geological mapping in key areas or their pepherical areas.
full-spectrum hyperspectral imagerempirical linear methodrock type samplesedge detection operatorlarge-scaled geological mapping
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