DEMO will have a limited diagnostic set for optimization of reactor performance, and limited diagnostic coverage due to challenging reactor conditions. This poses challenges for control, especially for detachment control which is planned to be performed with a limited set of spectroscopic lines -of -sight. To demonstrate mitigation of the coverage problem, we have implemented a sparse sensor placement technique on TCV for the case of spectroscopy. Experimental CIII 2D emissivity profiles from the MANTIS multispectral imaging system at TCV are used to create a synthetic spectroscopy system, with DEMO -relevant lines -of -sight. This synthetic diagnostic is validated through comparison with spectroscopic measurements in TCV. The sparse sensor placement algorithm takes as input the radiance calculated for a large set of lines -of -sight, resolved in time. It provides a method to reconstruct an emission profile along the divertor leg based on measurements from only a few lines -of -sight. We demonstrate that it is feasible to use a calibration based on either experimental data or simulated emissivities from SOLPS-ITER. As a result, for DEMO, the line -of -sight selection and a mathematical basis for reconstruction can be obtained before the reactor is turned on. The sparse sensor placement method can also be applied to estimate other physical quantities from emission measurements, if they have a oneto-one relationship with the shape of the emission profile along the divertor leg. As an example, the peak target current density obtained with Langmuir probes can be reconstructed using spectroscopy measurements. Lastly, the geometry of the lines -of -sight plays an important role in proper emission profile reconstruction. It should be tailor-made to the used magnetic configuration to measure the emission profile accurately, and the technique described here offers a route for performing this optimization.