Leveraging the Historical Landsat Catalog for a Remote Sensing Model of Wetland Accretion in Coastal Louisiana

Abstract

A wetland's ability to vertically accrete—capturing sediment and biological matter for soil accumulation—is key for maintaining elevation to counter soil subsidence and sea level rise. Wetland soil accretion is comprised of organic and inorganic components largely governed by net primary productivity and sedimentation. Sea level, land elevation, primary productivity, and sediment accretion are all changing across Louisiana's coastline, destabilizing much of its wetland ecosystems. In coastal Louisiana, analysis from 1984 to 2020 shows an estimated 1940.858 km2 of total loss at an average rate of 53.913 km2/year. Here we hypothesize that remote sensing timeseries data can provide suitable proxies for organic and inorganic accretionary components to estimate local accretion rates. The Landsat catalog offers decades of imagery applicable to tracking land extent changes across coastal Louisiana. This dataset's expansiveness allows it to be combined with the Coastwide Reference Monitoring System's point‐based accretion data. We exported normalized difference vegetation index (NDVI) and red‐band surface reflectance data for every available Landsat 4–8 scene across the coast using Google Earth Engine. Water pixels from the red‐band were transformed into estimates of total suspended solids to represent sediment deposition—the inorganic accretionary component. NDVI values over land pixels were used to estimate bioproductivity—representing accretion's organic component. We then developed a Random Forest regression model that predicts wetland accretion rates (R2 = 0.586, MAE = 0.333 cm/year). This model can inform wetland vulnerability assessments and loss predictions, and is to our knowledge the first remote sensing‐based model that directly estimates accretion rates in coastal wetlands.

Using Normalize Difference Vegetation Index to Infer Wetlands Salinity and Organic Contribution to Vertical Accretion Rates

“…Recently, Jensen et al. (2022) derived accretion rates along coastal Louisiana using NDVI and estimated suspended sediment concentration from Landsat time‐series as proxies for mineral and organic inputs respectively. Yet, no explicit relationship between NDVI and organic accretion was tested.…”

“…However, an analysis of the relationship between remotely sensed measurements and organic deposition from vegetation has never been proposed. Recently, Jensen et al (2022) derived accretion rates along coastal Louisiana using NDVI and estimated suspended sediment concentration from Landsat time-series as proxies for mineral and organic inputs respectively. Yet, no explicit relationship between NDVI and organic accretion was tested.…”

Spatial Variability in Salt Marsh Drainage Controlled by Small Scale Topography

“…To determine the influence of water depth and friction on WLC, we make use of (a) high‐spatial resolution topographic data (Figure 2a) (Christensen et al., 2023); and (b) two high‐spatial resolution maps of herbaceous aboveground biomass (AGB) obtained using AVIRIS‐NG hyperspectral imager (see Figure 2b for the AGB distribution during spring) (Jensen et al., 2022). Note that we employ two AGB maps because the UAVSAR campaigns occurred in two different seasons (i.e., spring and fall, see how vegetation structure changes with seasons in Table 1 (Castañeda & Solohin, 2021)).…”

“…We utilize two maps of herbaceous aboveground biomass (AGB), derived from Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) data, developed by Jensen et al (2022), D. , and D. J. for the spring and fall seasons. AVIRIS-NG is an imaging spectrometer that measures radiance at 5 nm sampling across 425 bands in the Visible to Short-Wave Infrared (VSWIR) spectral range (380-2,500 nm).…”

Climate and Human Impacts on Hydrological Processes and Flood Risk in Southern Louisiana

“…Inland radar altimetry data is made available through the Global Water Monitor portal (https://blueice.gsfc.nasa.gov/gwm/river/Index) and ocean radar altimetry is derived from the Copernicus Marine Service (Copernicus Marine Service, 2023a, 2023b) (https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_MY_008_047/description and https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_NRT_OBSERVATIONS_008_046/description). Delta‐X annual land change data over coastal Louisiana (Jensen et al., 2022) is available on Getirana (2023). LIS and LDT are freely available through https://github.com/NASA-LIS/LISF.…”