Mineralogical Mapping with Accurately Corrected Shortwave Infrared Hyperspectral Data Acquired Obliquely from UAVs

Abstract

While uncrewed aerial vehicles are routinely used as platforms for hyperspectral sensors, their application is mostly confined to nadir imaging orientations. Oblique hyperspectral imaging has been impeded by the absence of robust registration and correction protocols, which are essential to extract accurate information. These corrections are especially important for detecting the typically small spectral features produced by minerals, and for infrared data acquired using pushbroom sensors. The complex movements of unstable platforms (such as UAVs) require rigorous geometric and radiometric corrections, especially in the rugged terrain often encountered for geological applications. In this contribution we propose a novel correction methodology, and associated toolbox, dedicated to the accurate production of hyperspectral data acquired by UAVs, without any restriction concerning view angles or target geometry. We make these codes freely available to the community, and thus hope to trigger an increasing usage of hyperspectral data in Earth sciences, and demonstrate them with the production of, to our knowledge, the first fully corrected oblique SWIR drone-survey. This covers a vertical cliff in the Dolomites (Italy), and allowed us to distinguish distinct calcitic and dolomitic carbonate units, map the qualitative abundance of clay/mica minerals, and thus characterise seismic scale facies architecture.

Imaging Spectroscopy for the Mining Life Cycle: A Guide for Drone Applications

“…All of which is detailed on in the next sections. Only a limited number of publications using UAS-mounted SWIR cameras are currently available (e.g., [80][81][82][83][84]), which means this research field is only just emerging and our understanding of good methodologies remains nascent. Similarly, the best-practice guidelines for the acquisition and correction of coaligned VNIR-SWIR datasets, and accurate georeferencing and geometrical correction of such combined datasets, remain a topic of current research.…”

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

“…The data produced by hyper-spectral cameras are not only useful for investigating the reflected spectral intensity of green plants but also for analyzing the chemical properties of ground targets. Hyper-spectral data can provide information about the chemical composition and water content of soil [48], as well as the chemical composition of ground minerals [49,50]. This is because hyper-spectral cameras can capture data across many narrow and contiguous wavelength bands, allowing for detailed analysis of the unique spectral signatures of different materials.…”

Porosity, strength, and alteration – Towards a new volcano stability assessment tool using VNIR-SWIR reflectance spectroscopy

“…Because remotely sensed spectral imaging via aerial or satellite data can only capture the external portions of rocks or rock masses, model calibration may be required for upscaling efforts. However, the increasing availability of hyperspectral remote sensing data, from satellites (e.g., PRISMA), airborne (e.g., AVIRIS), or ground-based platforms (Kereszturi et al, 2018;Cogliati et al, 2021;Thiele et al, 2022), is opening new avenues for the mapping and analysis of alteration and volcano stability at volcanoes worldwide. Furthermore, remote sensing methods are important as partially lithified pyroclastic rocks (e.g., breccia-horizons and tephra) are often complicated and difficult to measure accurately in the laboratory (Schaefer et al, 2018) and are also subject to eruptionrelated porosity changes and thermal cracking (Vinciguerra et al, 2005;Heap and Violay, 2021;Kanakiya et al, 2021).…”

“…Reflectance spectroscopy has become increasingly used to explore soil and rock types by spectral band analysis, such as in the visible and near-infrared (350-1000 nm; VNIR), shortwave infrared (1000-2500 nm; SWIR) and thermal infrared (7000-13000 nm; TIR) bands relevant for hydrothermal alteration mapping (Rowan et al, 2003;Darmawan et al, 2018;Kereszturi et al, 2018;Müller et al, 2021). In particular, those alteration zones including iron oxide, as well as argillic, phyllic, and propylitic alterations min-erals, can be identified using both multispectral (Loughlin, 1991;Rowan et al, 2003) and hyperspectral data (Clark et al, 2003;Neal et al, 2018;Kereszturi et al, 2020;Thiele et al, 2022). Airborne, drone-based or carry-on devices can also effectively map physico-chemical changes of volcanic rocks and, when combined with effective processing algorithms (e.g., Partial Least Squares Regression) that can handle collinearity and high dimensionality (e.g., Wold et al, 2001), they can become effective platforms for characterising the mineralogy and alteration of volcanic rocks.…”