Remote Sensing Using Canopy and Leaf Reflectance for Estimating Nitrogen Status in Red-blush Pears

Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance

Farmers must balance the competing goals of supplying contributions of background reflectance, while spectral vegetation indices that combined reflectances of near-infrared adequate N for their crops while minimizing N losses to the environment. To characterize the spatial variability of N and other visible bands (MCARI and NIR/Green) were responsive to both leaf chlorophyll concentrations and ...

Hyperspectral remote sensing of sagebrush canopy nitrogen

Plant canopy nitrogen (N) is associated with ecosystem processes such as photosynthetic and aboveground net primary production, particularly in forested ecosystems. Sagebrush N is directly relatable to wildlife nutritional status and contributes to assessments of habitat quality, productivity, plant / soil water dynamics and controls on canopy photosynthesis. Hyperspectral remote sensing studie...

Remote sensing of sagebrush canopy nitrogen

Estimating canopy water content using hyperspectral remote sensing data

Hyperspectral remote sensing has demonstrated great potential for accurate retrieval of canopy water content (CWC). This CWC is defined by the product of the leaf equivalent water thickness (EWT) and the leaf area index (LAI). In this paper, in particular the spectral information provided by the canopy water absorption feature at 970 nm for estimating and predicting CWC was studied using a mode...

Estimating Leaf Water Status from Vis-nir Reflectance and Transmittance

Remotely sensing the water status of plant canopies remains a long term goal of remote sensing research. Established approaches involve measurements in the thermal infrared and the 900-2000nm reflective infrared. Less popular UVvisible-NIR techniques presumably deserve research attention, because photochemical changes linked to plant water status manifest spectral light scattering and absorptio...