GRSG Conference 2022: Orbit to Outcrop
Poster Title: The Influence of changing moisture content on Mineral Classification of Hyperspectral Images
Author: Tingxuan Jiang
Remote sensing studies on minerals and/or rocks often have a factor as changing moisture contents. Without the knowledge on effect of changing moisture content on mineral spectra, remote sensing studies risk in missing information, low representative, and misclassification. Therefore, it is important for geologic remote sensing community to know the systematical effect of varying moisture condition on mineral spectra.
In this paper, we present the systematic effect of changing moisture content on mineral. We collected a lab-acquired dataset and then we will use the dataset to evaluate the effect on spectral features and classification results.
We measured seven pure mineral samples with various moisture content in a dark room using an Analytical Spectral Device (ASD) TerraSpec Halo Mineral Identifier that is fixed in a solid position. The seven pure minerals are vivianite, gypsum, malachite, borax, calcite, kaolinite, and montmorillonite. For sample preparation, we add enough ultra-pure water into each sample until it is oversaturated, let the sample sediment for over 24 hours till no measurable sedimentation, and then remove the standing water of the samples. We frequently measure mass and spectra of each prepared sample while it is drying.
Each sample is weighted before being measured because its moisture content is calculated by weight. Before a sample is measured, we stir it to keep the sample homogeneous because drying forms a crust of the sample which has considerable different moisture content than the samples within the crust. Every time a sample is measured, to keep representative of the measurement, instead of only measure a spot we rotate the sample for four times and make three repeat measurements succeeding each rotation.
The measurement results show two main effects of increasing moisture content on mineral spectra: 1) decreasing reflectance value; 2) decreasing absorption depth of mineral diagnostic features. We are working on explanation of the two effects and then move to evaluate the effects of changing moisture content on mineral classification.