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Open AccessArticle

Integrating Imaging Spectrometer and Synthetic Aperture Radar Data for Estimating Wetland Vegetation Aboveground Biomass in Coastal Louisiana

1
Department of Geography, University of California at Los Angeles, Los Angeles, CA 90095, USA
2
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
3
Department of Oceanography and Coastal Sciences, College of the Coast and Environment, Louisiana State University, Baton Rouge, LA 70803, USA
*
Author to whom correspondence should be addressed.
Present address: Southeast Environmental Research Center, Institute of Water and Environment, Florida International University, Miami, FL 33199, USA.
Remote Sens. 2019, 11(21), 2533; https://doi.org/10.3390/rs11212533
Received: 30 August 2019 / Revised: 14 October 2019 / Accepted: 22 October 2019 / Published: 29 October 2019
Aboveground biomass (AGB) plays a critical functional role in coastal wetland ecosystem stability, with high biomass vegetation contributing to organic matter production, sediment accretion potential, and the surface elevation’s ability to keep pace with relative sea level rise. Many remote sensing studies have employed either imaging spectrometer or synthetic aperture radar (SAR) for AGB estimation in various environments for assessing ecosystem health and carbon storage. This study leverages airborne data from NASA’s Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) to assess their unique capabilities in combination to estimate AGB in coastal deltaic wetlands. Here we develop AGB models for emergent herbaceous and forested wetland vegetation in coastal Louisiana. In addition to horizontally emitted, vertically received (HV) backscatter, SAR parameters are expressed by the Freeman–Durden polarimetric decomposition components representing volume and double-bounce scattering. The imaging spectrometer parameters include normalized difference vegetation index (NDVI), reflectance from 290 visible-shortwave infrared (VSWIR) bands, the first derivatives from those bands, or partial least squares (PLS) x-scores derived from those data. Model metrics and cross-validation indicate that the integrated models using the Freeman-Durden components and PLS x-scores improve AGB estimates for both wetland vegetation types. In our study domain over Louisiana’s Wax Lake Delta (WLD), we estimated a mean herbaceous wetland AGB of 3.58 Megagrams/hectare (Mg/ha) and a total of 3551.31 Mg over 9.92 km2, and a mean forested wetland AGB of 294.78 Mg/ha and a total of 27,499.14 Mg over 0.93 km2. While the addition of SAR-derived values to imaging spectrometer data provides a nominal error decrease for herbaceous wetland AGB, this combination significantly improves forested wetland AGB prediction. This integrative approach is particularly effective in forested wetlands as canopy-level biochemical characteristics are captured by the imaging spectrometer in addition to the variable structural information measured by the SAR. View Full-Text
Keywords: aboveground biomass; deltaic wetlands; coastal Louisiana; imaging spectroscopy; hyperspectral; synthetic aperture radar (SAR); remote sensing; data integration; airborne visible/infrared imaging spectrometer—next generation (AVIRIS-NG); uninhabited aerial vehicle synthetic aperture radar (UAVSAR); blue carbon aboveground biomass; deltaic wetlands; coastal Louisiana; imaging spectroscopy; hyperspectral; synthetic aperture radar (SAR); remote sensing; data integration; airborne visible/infrared imaging spectrometer—next generation (AVIRIS-NG); uninhabited aerial vehicle synthetic aperture radar (UAVSAR); blue carbon
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MDPI and ACS Style

Jensen, D.; Cavanaugh, K.C.; Simard, M.; Okin, G.S.; Castañeda-Moya, E.; McCall, A.; Twilley, R.R. Integrating Imaging Spectrometer and Synthetic Aperture Radar Data for Estimating Wetland Vegetation Aboveground Biomass in Coastal Louisiana. Remote Sens. 2019, 11, 2533.

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