Generating Soil Parent Material Environmental Covariates Using Sentinel – 2A Images for Delineating Soil Attributes
M. Nivas Raj
Department of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
R. Kumaraperumal *
Department of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
S. Pazhanivelan
Water Technology Centre, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
D. Muthumanickam
Department of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
K. P. Ragunath
Water Technology Centre, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
M. Ashmitha Nihar
Department of Remote Sensing and Geographic Information System, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
N. S. Sudarmanian
Krishi Vigyan Kendra, Aruppukottai, Virudhunagar, India.
*Author to whom correspondence should be addressed.
Abstract
Soil mapping procedures typically involve the combination of possible soil-forming SCORPAN factors. Among the factors, parent materials/ mineralogy has been considered important for the soil classification besides the Organisms (O) and Relief (R). Inclusion of the parent material covariate for the Digital soil mapping involves implication through geological maps, spectral derivatives and predictive modelling. In this study, the most prominent parent materials identified were derived using the spectral indices formulated based on the Sentinel – 2A multispectral information. While considering the coarse spatial resolution constraints of the existing Landsat -8 bands that may limit certain applications, Sentinel-2 images were used for the indices derivation. The generated mineral maps can support the digital soil mapping of the soil attributes at different spatial scales.
Keywords: Parent materials/mineralogy, SCORPAN factors, sentinel -2A, spectral indices