A study was conducted on comprehensive analysis of soil properties across three micro- watersheds where the soils are derived from distinct parent materials: Amtur-3 MWS (WeatheredSchist),LakkundiMWS(WeatheredBasalt) andHanbarhatti-1MWS(Weathered sandstone) during 2022-24. The research involved characterization of soils; encompassing morphological, physical, chemical and exchangeable properties, along with elemental composition in soil primary particles. Additionally, quantitative evaluation of soil properties was performed using multispectral remote sensing data.WorldView-2 data were procured from REWARD project, UAS, Dharwad forselected sampling sites covering all the three parent materials. Multiple linear regression (MLR)modelsweredevelopedbyincorporatingfourextractedbandsfromWorldView-2data andtenspectralindices (NDVI, GNDVI,SAVI, GRVI, SAVI, TVI, EVI, BI,CIand MSAVI) as independent variables and total elemental composition as dependent variables. Surface soil sampling (0-20 cm depth) was done during March-April 2023 in all the three micro- watersheds representing schist, basalt and sandstone parent materials.
The physical analysis revealed high sand content in schistose soils, high clay contentin basaltic soils, while sandstone soils exhibited sandy clay texture. Physico-chemicalanalyses indicated neutral pH in schistose soils and slightly alkaline pH levels in basalt and sandstone soils, with low EC (<1 dS m-1) across all soil types. Basaltic soils exhibited the highest CEC and exchangeable cations, particularly Ca and Mg. The organic carbon content was moderate across all soil types. Available nutrient status revealed consistently low available N content across all soils. Basalt derived soils had highest K2O, while schistose and sandstone soils showed higher available P2O5 and Mn levels. Levels of available Zn, Cu and Fe content varied across soil types based on soil pH and OC content.The total elemental composition analysis demonstrated significant enrichment and similarity in major and trace elemental contents across surface soil and parent material, with unique mobility patterns across soil types. Correlation analysis showed strong associations between total elemental contents and spectral indices viz; SAVI, MSAVI, RI and GNDVI. Elements viz; Si, K, Pb and Crwerenegativelycorrelated while, Al, Fe, Ca, Mg, P, S, Mn, Ti, Zn, Cu, V, Co, Rb and As were positively correlated, validating high predictive accuracy of indices (R² = 0.90–0.96). Soil properties like sand, clay, bulk density and maximum water- holding capacity were correlated with elemental content. Sand content was positively linkedto Si and negatively to Al, Fe and Ca, while clay content displayed the opposite trend. Chemical properties and nutrient availability, particularly for N, K, Ca and micronutrients, were accuratelypredicted based on total elemental content, particularlyK and Ca (R² = 0.76– 0.89), reinforcing these elements reliability for predicting various soil properties and nutrient dynamics.RegressionmodelsdevelopedusingWorldView-2 spectral indicesproved valuablefor predicting both major and trace elemental contents, while models developed based on elemental content showed precise predictability for specific soil parameters. This study highlighted the potential utility of WorldView-2 data in predicting elemental distribution in unsampled fields for precision agriculture and our data can be used as benchmark for major and trace elemental contents to assess elemental enrichment from soil-forming and pedological processes along with some anthropogenic activities.