We develop a self-adaptive algebraic tomography algorithm (SAATA) to investigate the simultaneous reconstruction of concentration and temperature distributions in larger temperature range from two views. The simplified optical arrangement with fewer projections is realized by extension of spectral information at multiple wavelengths, resulting in great potential in applications of practical combustion diagnosis. The results show SAATA can perform much better reconstructions in 300–3000 K temperature range than genetic simulated annealing algorithm and least-square orthogonal-triangular decomposition method with two-wavelength scheme. More phantoms are created to demonstrate the capability of SAATA to capture the peaks and adapt for both flat and sharp temperature distributions. Meanwhile, the advantage of high stability ensures better reconstruction performance at noise levels from 0.1% to 10% in projections.