Coastal wetlands provide a wealth of ecosystem services, including improved water quality, protection from storm surges, and wildlife habitat. Louisiana’s wetlands, however, are threatened by development, pollution, and relative sea level rise (RSLR)—the combination of sea level rise and subsidence rates. Despite widespread wetland loss, areas such as the Wax Lake and Atchafalaya river deltas are in fact growing due to their sediment loads, resulting in a complex of both degradation and aggradation along the Louisiana coast. In order to understand and model how coastal wetlands are responding to RSLR, there is a need for improved vegetation mapping, biomass estimation, and landscape-scale study of accretionary processes. AVIRIS-NG offers high spatial and spectral resolution data that can be integrated with external datasets—including from in situ measurements, monitoring stations, and other remote sensing platforms—to study these distributions and processes. Spectra derived from AVIRIS-NG imagery were used to parameterize Multiple Endmember Spectral Mixture Analysis (MESMA) for mapping vegetation functional types in addition to partial least squares regression (PLSR) models for plant aboveground biomass (AGB). The historical Landsat record complemented this analysis by deriving maps of change in wetland health and sediment availability through time. Each of these remotely sensed parameters were investigated to determine their combined relationship to Louisiana’s coastal accretion rates. In quantifying landscape-scale processes that impact wetland accretion, this research aids the assessment of coastal resiliency in the face of sea level rise. Further, the investigated imaging spectroscopy methods pertaining to vegetation mapping, biomass estimation, and accretionary modeling will inform future studies under the global Surface Biology and Geology mission.