 The objective of this paper was to compare the accuracy of two advanced blending algorithms, Spatial and Temporal Adaptive Reflectance Fusion Model, a CRFM, and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model, a STARF, when downscaling Modi's indices to the Spatial Resolution of Landsat. Two approaches were tested, index then blend, IB, and blend then index, BI. Nine indices, commonly used for vegetation studies, environmental moisture assessment, and standing water identification were simulated on 45 dates from three sites. The outputs were then compared with indices calculated from observed Landsat data and pixel-to-pixel accuracy was assessed by calculating the Ike, BIOS, II, R2, and III, Root Mean Square Deviation, RMSD. The IB approach produced higher accuracies than the BI approach for both blending algorithms for all nine indices at all three sites. Additionally, we found that the relative performance of the STRFM and ASTARF algorithms depended on the Spatial and Temporal variances of the Landsat Modi's input indices. This article was authored by Abdullah Iyari-Hani, Timmer McVicker, Thomas G. Van Neel, and others. We are article.tv, links in the description below.