The typical assessment of vegetation condition focuses on the relative proportion of living and dead material, which provides no information on the key element of vegetation structure (i.e., density and orientation). Canopy structure information is critical for monitoring ecosystem status and trends, and is essential in climate, weather, and ecological studies. A three-dimensional description of canopy structure improves water flow estimates, advances optical condition and change mapping, and advances fire burn dynamics and emission projections. Unfortunately, quantitative and robust field techniques for measuring vegetation structure are lacking. One problem is that orientation is typically estimated rather than measured, yielding uncertain error bounds that propagate through the calculated density parameter. If both density and orientation could be calculated solely from common field measurements without the need for user estimates, the information content and direct comparability over time and space for a given species would dramatically increase. Furthermore, independent density and orientation measures would be directly amenable to remote sensing mapping, greatly increasing the effectiveness of monitoring status and trends.
USGS scientists are developing an approach for producing the spatiotemporal estimation of leaf area index (LAI) of a highly heterogeneous coastal marsh without relying on user estimates of marsh leaf-stem orientation. The derived canopy LAI profile used three years of field-measured photosynthetically active radiation (PAR) vertical profiles at seven S. alterniflora (saltmarsh cordgrass) marsh sites. First, an iterative transform of the PAR attenuation profiles produced best-fit light extinction coefficients (KM). KM sun zenith dependency was then removed obtaining, the leaf angle distribution (LAD) representing the average marsh orientation. Finally, the LAD was used to calculate the LAI canopy profile. These derived LAI and LAD reproduced measured PAR profiles with 99 % accuracy and corresponded to field-documented structures. LAI and LAD better reflect marsh structure than visular estimates; results substantiate the need to account for marsh orientation. The structure indexes are directly amenable to remote sensing spatiotemporal mapping and offer a more meaningful representation of wetland grassland systems, promoting biophysical function understanding.
Ramsey III, E., Rangoonwala, A., Jones, C.E., and T. Banister., 2015. Marsh Canopy Leaf Area and Orientation Calculated for Improved Marsh Structure Mapping, Photogramm Eng Rem S, 81(10) 807-816. doi: 10.14358/PERS.81.10.807
(a) Yearly PAR vertical profiles at a single marsh site (397) from 2010 to 2012. (b) Predicted PAR using model-derived LAI and LAD values shown in (c).