Next Article in Journal
The Integration of Photodiode and Camera for Visible Light Positioning by Using Fixed-Lag Ensemble Kalman Smoother
Next Article in Special Issue
Trends in the Seaward Extent of Saltmarshes across Europe from Long-Term Satellite Data
Previous Article in Journal
A New Empirical Model of NmF2 Based on CHAMP, GRACE, and COSMIC Radio Occultation
Previous Article in Special Issue
Mapping Coastal Wetland Biomass from High Resolution Unmanned Aerial Vehicle (UAV) Imagery
Open AccessArticle

Retrieval of Salt Marsh Above-Ground Biomass from High-Spatial Resolution Hyperspectral Imagery Using PROSAIL

1
Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623–5603, USA
2
Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY 14623–5603, USA
3
Department of Biology, Albright College, Reading, PA 19604, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(11), 1385; https://doi.org/10.3390/rs11111385
Received: 25 April 2019 / Revised: 31 May 2019 / Accepted: 8 June 2019 / Published: 11 June 2019
(This article belongs to the Special Issue Satellite-Based Wetland Observation)
Salt marsh vegetation density varies considerably on short spatial scales, complicating attempts to evaluate plant characteristics using airborne remote sensing approaches. In this study, we used a mast-mounted hyperspectral imaging system to obtain cm-scale imagery of a salt marsh chronosequence on Hog Island, VA, where the morphology and biomass of the dominant plant species, Spartina alterniflora, varies widely. The high-resolution hyperspectral imagery allowed the detailed delineation of variations in above-ground biomass, which we retrieved from the imagery using the PROSAIL radiative transfer model. The retrieved biomass estimates correlated well with contemporaneously collected in situ biomass ground truth data ( R 2 = 0.73 ). In this study, we also rescaled our hyperspectral imagery and retrieved PROSAIL salt marsh biomass to determine the applicability of the method across spatial scales. Histograms of retrieved biomass changed considerably in characteristic marsh regions as the spatial scale of the imagery was progressively degraded. This rescaling revealed a loss of spatial detail and a shift in the mean retrieved biomass. This shift is indicative of the loss of accuracy that may occur when scaling up through a simple averaging approach that does not account for the detail found in the landscape at the natural scale of variation of the salt marsh system. This illustrated the importance of developing methodologies to appropriately scale results from very fine scale resolution up to the more coarse-scale resolutions commonly obtained in airborne and satellite remote sensing. View Full-Text
Keywords: hyperspectral imaging; high-resolution; salt marsh; biomass; Leaf Mass Index (LMA); Leaf Area Index (LAI); PROSAIL; radiative transfer model; Extended Fourier Amplitude Sensitivity Test (EFAST); Virginia Coast Reserve hyperspectral imaging; high-resolution; salt marsh; biomass; Leaf Mass Index (LMA); Leaf Area Index (LAI); PROSAIL; radiative transfer model; Extended Fourier Amplitude Sensitivity Test (EFAST); Virginia Coast Reserve
Show Figures

Graphical abstract

MDPI and ACS Style

Eon, R.S.; Goldsmith, S.; Bachmann, C.M.; Tyler, A.C.; Lapszynski, C.S.; Badura, G.P.; Osgood, D.T.; Brett, R. Retrieval of Salt Marsh Above-Ground Biomass from High-Spatial Resolution Hyperspectral Imagery Using PROSAIL. Remote Sens. 2019, 11, 1385.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Remote Sens., EISSN 2072-4292, Published by MDPI AG
Back to TopTop