Abstract
In this study, several vegetation indices were examined in order to determine the most sensitive vegetation index for monitoring southern Appalachian wetlands. Three levels of platforms (in situ, airborne, and satellite) for sensors were also examined in conjunction with vegetation indices. Net primary production (NPP) data were gathered to use as a measure of wetland function. Along with the in situ radiometers, National Agricultural Imagery Program (NAIP) data and Landsat 8 Operational Land Imager (OLI) data were gathered in order to calculate vegetation indices at three platforms. At the in situ level, VARI700 was the most sensitive vegetation index in terms of NPP (r2 = 0.65, p 2 = 0.35, p = 0.11). At the satellite level, the DVI appeared to have a positive relationship with NPP. For most indices there was a drop in the coefficient of determination with NPP when the platform altitude increased, with the exception of NDVI when increasing altitude from in situ to airborne. This study provides a novel methodology comparing reflectance and vegetation indices at three platform levels.
Highlights
The use of remote sensing in vegetation-related studies is a rising trend as it allows for the estimation of vegetation characteristics over large areas [1]
Vegetation indices calculated from in situ radiometer data were able to explain a moderate amount of variance in Net primary production (NPP) in southern Appalachian wetlands (Figure 4)
The choice in vegetation index depends on the platform that is being used to examine southern Appalachian wetlands
Summary
The use of remote sensing in vegetation-related studies is a rising trend as it allows for the estimation of vegetation characteristics (chlorophyll content and net primary production, NPP) over large areas [1]. (2016) Assessing Net Primary Production in Montane Wetlands from Proximal, Airborne, and Satellite Remote Sensing. In all of the aforementioned in-situ remote sensing studies, two inter-calibrated hyperspectral radiometers were used. This methodology was employed because the use of two radiometers allows for one to capture incoming radiation while the other captures the ground reflectance simultaneously [3] [4]. Computing radiance is possible during times of inconstant irradiance [4], which might be a difficulty with remote sensing
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