Detection of iron-bearing mineral assemblages in Nainarmalai granulite region, south India, based on satellite image processing and geochemical anomalies

Gopinathan, P.; Roy, Priyadarsi D.; Subramani, T.; Karunanidhi, D

doi:10.1007/s10661-022-10570-2

Cited by 7 publications

(1 citation statement)

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“…The reflectance data are transformed into four types, logarithm, exponent, first-order differential, and spectral homogenization in order to highlight the soil oxide information contained in the spectral value (Ben-Dor et al, 2006). The logarithm of reflectivity will not change the relative relationship of the data, which can help stabilize the variance, so that the reflectivity is always dispersed in a manner close to the normal distribution, and the logarithmic reflectivity distribution is independent of the mean value (Steinberg et al, 2016;Gopinathan et al, 2022). Since the reflectivity is between 0 and 1, the absolute value is generally taken for ease of calculation (Huang et al, 2021).…”

Section: ) Spectral Transformation Algorithmmentioning

confidence: 99%

Response of soil oxides in complex terrain region to environment revealed by hyperspectral observations

Zhang

Tang

et al. 2023

Front. Environ. Sci.

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Soil oxides are important diagnostic indicators for soil quality assessment, and their content has a positive effect on adsorption of heavy metals, remediation of pollution, and enhancement of organic matter enrichment. Moreover, soil oxides are affected by multiple environmental factors such as soil pH, geomorphological, and elevation, and their distribution is highly regional. In this study, 421 ground soil samples and 2 hyperspectral satellite data were collected. The content distribution of 8 main oxides in soil, including SiO2, Al2O3, Fe2O3, MgO, CaO, Na2O, K2O, and Corg. were obtained according to the process of data preprocessing, spectral transformation, feature extraction, band combination, and model establishment. The results indicated that the homogenization spectral transformation method is the most suitable; The calculation accuracy of complex spectral characteristic parameters is inferior to that of characteristic bands; The difference model is more suitable for the extraction of soil oxide content in this study area; The average content of SiO2 and CaO shows a decreasing trend with the elevation increasing; The average content of SiO2 and Fe2O3 shows an upward trend with the increase of slope; East is the main geomorphic direction of soil oxide enrichment. SiO2, Al2O3, and MgO are the three soil oxides with the highest correlation. The response relationship between soil oxides, topography and pH is discussed, and the distribution rule of soil oxides and environmental determinants are obtained, which provides a set of technical schemes for digital soil research. This study can extract the content of soil components in a large area, analyze the causes, and provide a new technical scheme for soil investigation and treatment.

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