The Photochemical Reflectance Index (PRI) provides insight remote sensing into plant physiological processes occurring at leaf to canopy scales. We have found that PRI displays greater sensitivity to these processes if redefined to exclude the leaf surface reflectance. Here we suggest our published method for estimating leaf surface reflectance using linear polarizers underestimates the actual leaf surface reflectance. We suggest part of the leaf volume reflectance obtained using our published method represents light diffusely scattered by the leaf surface. We propose here a modification to our published method in order to obtain estimates of vPRI that are presumably more sensitive to leaf photochemistry.
Remotely sensing plant canopy water status remains a long term goal of remote sensing research.
Established approaches to estimating canopy water status — the Crop Water Stress Index, the Water
Deficit Index and the Equivalent Water Thickness — involve measurements in the thermal or reflective
infrared. Here we report plant water status estimates based upon analysis of polarized visible imagery of a
cotton canopy measured by ground Multi-Spectral Polarization Imager (MSPI). Such estimators potentially
provide access to the plant hydrological photochemistry that manifests scattering and absorption effects in
the visible spectral region.
In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside leaves in a plant stand. Developed by1,2, PRI evolved from laboratory reflectance measurements of individual leaves. Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves.
We compared values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. Our results show the polarized leaf surface reflection should be removed when calculating PRI and that the leaf physiology information is in leaf interior reflectance, not leaf transmittance.
The light scattered by plant canopies depends in part on the light scattering/absorbing properties of the leaves and is
key to understanding the remote sensing process in the optical domain. Here we specifically looked for evidence of
fine spectral detail in the polarized portion of the light reflected from the individual leaves of five species of plants
measured at Brewsters angle over the wavelength range 450 to 2300nm. Our results show no strong, unambiguous
evidence of narrow band spectral variation of the polarized portion of the reflectance factor.
A better understanding of the information contained in the spectral, polarized bidirectional reflectance and transmittance
of leaves may lead to improved techniques for identifying plant species in remotely sensed imagery as well as better
estimates of plant moisture and nutritional status.
Here we report an investigation of the optical polarizing properties of several leaves of one species, Cannabis sativa,
represented by a 3x3 Mueller matrix measured over the wavelength region 400-2,400 nm. Our results support the
hypothesis that the leaf surface alters the polarization of incident light - polarizing off nadir, unpolarized incident light,
for example - while the leaf volume tends to depolarized incident polarized light.
Precision agriculture requires high spectral and spatial resolution imagery for advanced analyses of crop and soil
conditions to increase environmental protection and producers' sustainability. GIS models that anticipate crop responses
to nutrients, water, and pesticides require high spatial detail to generate application prescription maps. While the added
precision of geo-spatial interpolation to field scouting generates improved zone maps and are an improvement over
field-wide applications, it is limited in detail due to expense, and lacks the high precision required for pixel level
applications. Multi-spectral imagery gives the spatial detail required, but broad band indexes are not sensitive to many
variables in the crop and soil environment. Hyperspectral imagery provides both the spatial detail of airborne imagery
and spectral resolution for spectroscopic and narrow band analysis techniques developed over recent decades in the laboratory that will advance precise determination of water and bio-physical properties of crops and soils.
For several years, we have conducted remote sensing investigations to improve cotton production through field
spectrometer measurements, and plant and soil samples in commercial fields and crop trials. We have developed
spectral analyses techniques for plant and soil conditions through determination of crop water status, effectiveness of
pre-harvest defoliant applications, and soil characterizations. We present the most promising of these spectroscopic
absorption and narrow band index techniques, and their application to airborne hyperspectral imagery in mapping the
variability in crops and soils.
Representing the areal extent of circumpolar wetlands is a critical step to quantifying the emission of methane, an important greenhouse gas. Present estimates of the areal extent of these wetlands differ nearly seven fold, implying large uncertainties exist in the prediction of circumpolar methane emission rates. Our objective is to use multi- directional and polarization measurement provided by the French POLDER sensor to improve this estimate. The results show that wetlands can be detected, classified and their area quantified using the unique, highly polarized angular signature of the sunglint measured over their water surfaces.