Microbial biofilm communities are composed of fungi, bacteria, and phytoplankton taxonomic groups (e.g., cyanobacteria, diatoms, and chlorophytes), which inhabit the surface of intertidal mudflats. Such biofilms have critical roles in shorebird diets, mudflat stabilization, primary productivity, and carbon storage. These raster datasets represent the nutritional quality, quantity and pigment characteristics of biofilms located on the mudflats of South San Francisco Bay in Spring 2021, during peak shorebird migration. To produce these datasets, we used a multi-scalar remote sensing approach that coupled in-situ data with data from an ASD field spectrometer, a HySpex VNIR/SWIR imaging spectrometer (5 mm), and the AVIRIS-Next Generation (NG) airborne imaging spectrometer (3.7 m). We used these data to develop and scale algorithms of chlorophyll-a (chl-a; indicator of biomass), lipids, total organic carbon (TOC), carbohydrates and pigments (indicators of taxonomic groups). Using multiple and single response partial least squares regression, we modeled the nutritional quality components (chl-a, lipids, TOC, carbohydrates) with field spectra and scaled models to the South Bay using an AVIRIS-NG image collected on April 15, 2021. Pigments (chl-b, fucoxanthin, diadioxanthin, zeaxanthin) were likewise modeled and scaled to the South Bay. Results indicated high biomass and nutritional quality component concentrations within a tidal marsh restoration site and some creek outflows. Maps created using hyperspectral remote sensing data will support managers’ need to visualize shorebird habitat quality and research on drivers of biofilm quality and quantity.