Diffuse and specular characteristics of leaf reflectance

Zhou

European Journal of Remote Sensing

et al. 2014

The objectives of this study were to establish quantitative models for monitoring the leaf ion and water content under saline conditions. The best spectral indices for estimating leaf ion content and leaf water content were found to be normalized difference spectral indices (NDSI (R 1340 , R 2306 )), ratio spectral indices (RSI (R 2306 , R 1347 )) for K 2-and NDSI (R 1222 , R 2264 ), RSI (R 2264 , R 1321 ) for RWC, respectively. The regression models based on the above spectral indices were formulated with R 2 greater than 0.46. The high fit between the measured and estimated values indicate that the present models based on RSI could be used to estimate leaf ion and water content feasibly under saline conditions.

Section: Discussionmentioning

confidence: 99%

Monitoring cotton (Gossypium hirsutum L.) leaf ion content and leaf water content in saline soil with hyperspectral reflectance

Zhou

European Journal of Remote Sensing

et al. 2014

“…Most of these studies have shown that canopy reflectance within the red (600-710 nm) and near infra-red (750-900 nm) wavelengths were correlated with disease severity estimates. In the visible range reflectance is considered to be influenced by leaf pigments such as chlorophyll and in the near-infrared range reflectance is affected by changes in the anatomical structure of leaves [40,41].…”

Section: Discussionmentioning

confidence: 99%

Identification of powdery mildew (Erysiphe graminis sp. tritici) and take-all disease (Gaeumannomyces graminis sp. tritici) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements

2006

Identification of powdery mildew (Erysiphe graminis sp. tritici ) and take-all disease (Gaeumannomyces graminis sp. tritici ) in wheat (Triticum aestivum L.) by means of leaf reflectance measurements Abstract: The ability to identify diseases in an early infection stage and to accurately quantify the severity of infection is crucial in plant disease assessment and management. A greenhouse study was conducted to assess changes in leaf spectral reflectance of wheat plants during infection by powdery mildew and take-all disease to evaluate leaf reflectance measurements as a tool to identify and quantify disease severity and to discriminate between different diseases. Wheat plants were inoculated under controlled conditions in different intensities either with powdery mildew or take-all. Leaf reflectance was measured with a digital imager (Leica S1 Pro, Leica, Germany) under controlled light conditions in various wavelength ranges covering the visible and the near-infrared spectra (380 -1300 nm). Leaf scans were evaluated by means of L*a*b*-color system. Visual estimates of disease severity were made for each of the epidemics daily from the onset of visible symptoms to maximum disease severity. Reflectance within the ranges of 490 780 nm (r 2 = 0.69), 510 780 nm (r 2 = 0.74), 516 1300 nm (r 2 = 0.62) and 540 1300 nm (r 2 = 0.60) exhibited the strongest relationship with infection levels of both powdery mildew and take-all disease. Among the evaluated spectra the range of 490 780 nm showed most sensitive response to damage caused by powdery mildew and take-all infestation. The results of this study indicated that disease detection and discrimination by means of reflectance measurements may be realized by the use of specific wavelength ranges. Further studies have to be carried out, to discriminate powdery mildew and take-all infection from other plant stress factors in order to develop suitable decision support systems for site-specific fungicide application.

“…We hypothesize that this is caused by needle wax [40]. In the visible wavelengths where leaf pigments are highly absorbing, leaf scattering is dominated by specular reflectance at the surface [41]. Specular reflectance, directed mostly in backward directions, increases strongly with decreasing wavelength in the visible spectral region.…”

Section: Discussionmentioning

confidence: 98%

Spectral Similarity and PRI Variations for a Boreal Forest Stand Using Multi-angular Airborne Imagery

2017

Abstract:The photochemical reflectance index (PRI) is a proxy for light use efficiency (LUE), and is used in remote sensing to measure plant stress and photosynthetic downregulation in plant canopies. It is known to depend on local light conditions within a canopy indicating non-photosynthetic quenching of incident radiation. Additionally, when measured from a distance, canopy PRI depends on shadow fraction-the fraction of shaded foliage in the instantaneous field of view of the sensor-due to observation geometry. Our aim is to quantify the extent to which sunlit fraction alone can describe variations in PRI so that it would be possible to correct for its variation and identify other possible factors affecting the PRI-sunlit fraction relationship. We used a high spatial and spectral resolution Aisa Eagle airborne imaging spectrometer above a boreal Scots pine site in Finland (Hyytiälä forest research station, 61 • 50 N, 24 • 17 E), with the sensor looking in nadir and tilted (off-nadir) directions. The spectral resolution of the data was 4.6 nm, and the spatial resolution was 0.6 m. We compared the PRI for three different scatter angles (β = 19 • , 55 • and 76 • , defined as the angle between sensor and solar directions) at the forest stand level, and observed a small (0.006) but statistically significant (p < 0.01) difference in stand PRI. We found that stand mean PRI was not a direct function of sunlit fraction. However, for each scatter angle separately, we found a clear non-linear relationship between PRI and sunlit fraction. The relationship was systematic and had a similar shape for all of the scatter angles. As the PRI-sunlit fraction curves for the different scatter angles were shifted with respect to each other, no universal curve could be found causing the observed independence of canopy PRI from the average sunlit fraction of each view direction. We found the shifts of the curves to be related to a leaf structural effect on canopy scattering: the ratio of needle spectral reflectance to transmittance. We demonstrate that modeling PRI-sunlit fraction relationships using high spatial resolution imaging spectroscopy data is suitable and needed in order to quantify PRI variations over forest canopies.