High-resolution soil moisture (SM) plays an important role in hydrological processes and agricultural and climatic dynamics. Therefore, this study attempts to enhance the spatial resolution of Soil Moisture Active Passive (SMAP) SM data product from 9 km to 1 km using the Triangle method. The Triangle method employs the normalized Land Surface Temperature (LST*) and normalized vegetation indices (VIs*) in a polynomial regression relation for the computation of SM. In this study, four VIs-Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index (MSAVI), Soil Adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI) were evaluated in the Triangle method with various orders of polynomial relation for downscaling of SMAP SM. The polynomial relation was used with first and second order of LST* and VI*, and the order of variables has been shown as 1 and 2 in the manuscript. The methodology was validated in the Varanasi region, India, using in situ soil moisture measurements collected on twelve dates. The assessed results indicate that the 1-1 order of LST* and NDVI* (linear in both LST* and VI*) provided the highest accuracy among all the combinations of different orders, with a Root Mean Square Error (RMSE) of 0.032 m3/m3 and a correlation coefficient (R) of 0.76. Among Vis, NDVI and MSAVI showed better results in comparison to EVI due to its sensitivity to soil background and atmospheric conditions in semi-arid regions. Spatial analysis in the form of SM maps showed that the SM map generated using NDVI and MSAVI in the Triangle method effectively captured local hydrological variability, such as agricultural fields and riparian features. Overall, this study demonstrated the potential of the Triangle method for the downscaling of SM through the integration of thermal and optical remote sensing and highlights the importance of selecting a suitable VI and model configuration for improving the downscaling accuracy of the Triangle method. (c) 2026 Published by Elsevier B.V. on behalf of COSPAR.