Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture

Extracting Red Edge Position Parameters from Ground- and Space-Based Hyperspectral Data for Estimation of Canopy Leaf Nitrogen Concentration in Rice

“…Since plant chlorophyll concentration is highly correlated with nitrogen status (Hansen & Schjoerring, 2003;Haboudane et al, 2004), REP has also been used for evaluating plant nitrogen status (Lamb et al, 2002;Jongschaap & Booij, 2004). However, as most often encountered, REP is not adequate to track the variations in chlorophyll concentration due to its doublepeak feature (Clevers et al, 2004;Cho and Skidmore, 2006).…”

Remote sensing in food production and #8211; a review

“…However, even if the influences of external factors could be completely removed, the type of VIs that use reflectance data from red and NIR bands would still have intrinsic limitations because they are not a single measure of a specific plant biophysical parameter but rather of many vegetation parameters (Govaerts et al, 1999;Haboudane et al, 2004). In fact, a major problem in the use of these VIs arises from the fact that canopy reflectance, in the visible and near infrared, strongly depends on both structural (LAI, leaf orientation, canopy architecture) and biochemical properties (e.g., photosynthetic pigments content) (Asner, 1998;Gao et al, 2000;Haboudane et al, 2004).…”

“…In fact, a major problem in the use of these VIs arises from the fact that canopy reflectance, in the visible and near infrared, strongly depends on both structural (LAI, leaf orientation, canopy architecture) and biochemical properties (e.g., photosynthetic pigments content) (Asner, 1998;Gao et al, 2000;Haboudane et al, 2004). It is difficult to uncouple the combined effect of the two influences (red and NIR spectral regions) and, consequently, to develop a "unique" VI exclusively sensitive to a single vegetation property, as Agapiou et al (2012) point out.…”

Evaluation and Normalization of Cloud Obscuration Related BRDF Effects in Field Spectroscopy

“…Alternatively broader spectral regions around the atmospheric water absorption regions or even the entire 1,800-2,500 nm region may need to be excluded from analysis. This analysis indicates that DFOV time series can be established even with low illumination conditions for the monitoring of chlorosis-related stresses such as nitrogen deficiencies that show up in the VIS spectrum [34] and canopy structure changes that are most pronounced in the near-infrared (NIR) [35]. Monitoring of changes that appear in the short-wave infrared (SWIR) may on the other hand be restricted.…”