The moisture content (MC) of wood affects its industrial performance, but it is difficult to monitor spatial variations in MC. Here, a multivariate regression was developed to estimate the MC from near infrared (NIR) spectra and was used to monitor the spatial variation in the MC of wood during air- and oven-drying. The spectra and mass of wood pieces were measured at five stages during drying (at each 20% loss of initial water mass). Wood pieces were dried naturally and oven-dried at 60 °C. Initially, 25 spectra were recorded at equidistant points covering the entire longitudinal × radial surface of the sample. Then, a planing machine was used to access the inside of the wood, and NIR spectra were measured for each new surface, at a total of 100 points spatially distributed within the wood pieces. The wood pieces were analyzed in their original state, and when they had lost 20, 40, 60, and 80% of their initial water mass. An NIR-based regression (R 2 p = 0.90 and RMSEP = 10.51%) was applied to estimate the MC, and its spatial gradient during drying was then mapped. These analyses revealed the spatial variation in MC within wood pieces during drying.