Application of Gaofen-5 Hyperspectral Data in Uranium Exploration: A Case Study of Weijing in Inner Mongolia, China

Abstract

Gaofen-5 (GF-5) satellite is the world's first full-spectrum hyperspectral satellite to achieve comprehensive observations of the atmosphere and land. The Advanced Hyperspectral Imager (AHSI) carried by GF-5 can acquire 330-chanel imagery covering 390 - 2500 nm. However, the application of GF-5 AHSI imagery in uranium exploration is currently unknown. In this paper, the AHSI imagery was used for prospecting uranium mineralization in the Weijing, Inner Mongolia, China. The matched filter (MF) and threshold segmentation were used for mapping goethite, Al-high, Al-medium and Al-poor sericite. And the principal component analysis (PCA) and gray-level co-occurrence matrix (GLCM) were used to extract the texture information of the study area. Subsequently, combined with geological information, the relationship between alteration information, texture complexity and uranium mineralization was discussed, and it was pointed out that goethite, Al-medium, Al-poor sericite and texture complexity in this area can be used as indicators of uranium mineralization. Finally, three prospects were delineated, which will guide the follow-up uranium exploration in this area and promote the application of GF-5 AHSI data.

Improving Rock Classification with 1D Discrete Wavelet Transform Based on Laboratory Reflectance Spectra and Gaofen-5 Hyperspectral Data

“…Guo et al [12] utilized the semi-supervised self-learning (SSL) method to investigate the capability of Hyperion data in lithological classification with limited samples. Zhang et al [13] mapped areas of acicularite and sericite using GF-5 AHSI data and proposed indicators of uranium mineralization. Shebl et al [14] tested the ability of the PRecursore IperSpettrale della Missione Applicativa hyperspectral data for lithological mapping, and the Support Vector Machine algorithm achieved the highest accuracy.…”