Recent advancements in remote sensing facilitate the mapping of mineral occurrences but lack quantitative estimation of mineral abundances. In the present study, EO-1 Hyperion data are used for mapping and estimating beach placer minerals in the Cuddalore coastal stretch of Tamil Nadu, India, using spectral angle mapper (SAM) algorithm, continuum removed band depth analysis, and random forest (RF) regression. Strategic beach placer minerals are exposed in the image due to their specific spectral reflection/absorption characteristics; these unique settings are used to explore their spatial distribution from associated features. EO-1 Hyperion images are analyzed for (i) atmospheric correction; (ii) selection and transformation of optimum bands; (iii) fixing the input pixels from selected bands; (iv) generating n-D angle—for the preparation of end-members with unique spectra of mineral classes; (v) comparative analysis between true end-member and reference spectra of minerals using SAM, spectral feature fitting, and binary encoding algorithms; and (vi) image classification using SAM. The result of SAM shows the occurrence of placer mineral deposits such as zircon with an overall accuracy of 81.06% and Kappa coefficient of 0.71. The zircon shows strong absorption in spectral geometric parameters of EO-1 Hyperion data, such as band depth and band area at the spectral range of 1075 to 1150 nm. The positive correlation between geometric parameters of mineral spectra in its absorption characteristics and the mineral concentration of in situ samplings is used for developing an RF prediction model for estimating the placer minerals from beach sand deposits. Significantly, the lower RMSE values estimated at 0.082 and 0.156 for reference spectra (in situ) and image spectra respectively proved the ability of EO-1 Hyperion data for quantifying mineral resources.