= Raman band-area map
{c}
{title2=$A(x,y)$}
A <Raman band-area map> assigns each spatial position an integrated, usually background-corrected spectral intensity over a stated <Raman shift> range. If $I(x,y,\widetilde\nu)$ is the spectrum and $B$ is its estimated baseline,
$$
A(x,y)=\int_{\widetilde\nu_1}^{\widetilde\nu_2}[I(x,y,\widetilde\nu)-B(x,y,\widetilde\nu)]\,d\widetilde\nu.
$$
This is one way to summarize the spectra collected in <Raman mapping>. It is useful for following a band's spatial distribution while preserving a different interpretation from a <Raman peak-position map>.<What Raman images can reveal by Renishaw>[“How do we collect Raman images?” and “How can I analyse Raman images?”, spectral datasets and band parameters]{ref}
Peak height alone does not determine area. For an isolated <Gaussian function> band of height $H$ and width parameter $s$, integrating the complete band gives
$$
A_{\rm full}=Hs\sqrt{2\pi}.
$$
Two hypothetical bands of equal height10 intensity units and $s=2$ or4cm⁻¹ have full areas about50.13 and100.27 intensity-units·cm⁻¹. Thus an area map can change while a height map stays constant. A finite integration window captures only part of the complete band, so the actual window must accompany the value.
<Raman integration-window bias> arises if shifting or broadening moves part of the chosen band outside that fixed range. Neighboring bands and an incorrectly subtracted background can also change the result. For a sampled spectrum, a quadrature uses the actual channel spacing, for example $A\approx\sum_i(I_i-B_i)\Delta\widetilde\nu_i$. A bare sum without the spacing factor has a different numerical convention when sampling changes.
Comparing areas across positions also requires consistent exposure, illumination and focus, or an appropriate normalization and <measurement calibration>. A larger area is therefore not automatically a larger concentration of one material. The manufacturer's discussion of spectral analysis explicitly cautions that broad background can contaminate simple intensity-based images.<What Raman images can reveal by Renishaw>[“How can I analyse Raman images?”, single-frequency intensity and background warning]{ref}
Back to article page
