Relations Between Red Edge Characteristics and Agronomic Parameters of Crops

The hyperspectral reflectance of the canopy and the leaves on the main stemfor six varieties, two each of rice corn, and cotton crops, were measured at different growth stageswith an ASD FieldSpec Pro FR^(TM) to analyze red edge characteristics forleaf area indices (LAI),aboveground biomass, as well as the chlorophyll, carotenoid, and nitrogen content, emphasizingcomparative differences on the red edge parameters. The results showed a 'double peak' phenomenonfor the red edge of the canopy spectra but not for the leaves. There were 'increase' and 'decrease'change rules for the red edge position, lambda_r, the red edge slope, D lambda_r, and the red edgearea, S_r, of the canopy spectra for all 3 crops with a 'blue shift' for lambda_r of the leafspectra for all 3 crops as the development stages progressed. For rice, corn, and cotton the LAI andfresh leaf mass had highly significant correlations (P < 0.01) to the red edge parameters lambda_r,D lambda_r, and S_r of their canopy spectra. Additionally, for all crops the chlorophyll-a,chlorophyll-b, total chlorophyll, and carotenoid content of the leaves all had highly significant (P< 0.01) correlations to their lambda_r. For rice, the nitrogen content of the leaves in g kg^(-1)and phytomassfor a unit area of land in g m^(-2) also had a highly significant (P < 0.01)correlation to lambda_r, D lambda_r lambda_r, and S_r of the canopy spectra.

The Red Edge Parameters of Different Wheat Varieties Under Different Fertilization and Irrigation Treatments

The dynamics of red edge parameters at different growth stages of wheat canopy was studied. The red edge position moved to the longer wavelength from erecting stage to heading stage, and returned to the original wavelength direction from grain-filling stage to maturity stage. The leaf total nitrogen content (LTN) is positively related to red edge amplitude (d λ red) and NIR platform amplitude (d λNIRP) and the correlation coefficient improved as growth stage extended. The chlorophyll content (TChl) is negatively related to d λ red from erecting stage to the elongation stage, and positively related to d λ red from heading stage to milky maturity stage. TChl is also positively related to d λNIRP. The leaf area index (LAI) is positively related to d λ red and d λNIRP, and the correlation coefficient improved as growth stage extended. It was concluded that d λ red and d λNIRP can be used as the indicators of winter wheat growth state, and guide the fertilization and irrigation decision making. The λNIRF is suitable for derivation of LTN, the d λ red for TChl, and the d λ red or d λNIRP for LAI.

Estimating Leaf Chlorophyll Content Using Red Edge Parameters

Hyperspectral remote sensing makes it possible to non-destructively monitor leaf chlorophyll content （LCC）. This study characterized the geometric patterns of the first derivative reflectance spectra in the red edge region of rapeseed （Brassica napus L.） and wheat （Triticum aestivum L.） crops. The ratio of the red edge area less than 718 nm to the entire red edge area was negatively correlated with LCC. This finding allowed the construction of a new red edge param- eter, defined as red edge symmetry （RES）. Compared to the commonly used red edge parameters （red edge position, red edge amplitude, and red edge area）, RES was a better predictor of LCC. Furthermore, RES was easily calculated using the reflectance of red edge boundary wavebands at 675 and 755 nm （R675 and R755） and reflectance of red edge center wavelength at 718 nm （R718）, with the equation RES = （R71s - R675）/（R755 - R675）. In addition, RES was simulated effectively with wide wavebands from the airborne hyperspectral sensor AVIRIS and satellite hyperspectral sensor Hyperion. The close relationships between the simulated RES and LCC indicated a high feasibility of estimating LCC with simulated RES from AVIRIS and Hyperion data. This made RES readily applicable to common airborne and satellite hyperspectral data derived from AVIRIS and Hyperion sources, as well as ground-based spectral reflectance data.

Red-shift law of intense laser-induced electro-absorption in solids

A theoretical study on the red-shift of laser-induced electro-absorption is presented. It is found that laser-induced red-shift scales with the cube root of the pump laser intensity in the optical tunneling regime and has an obvious deviation from this scale in the multi-photon regime. Our results show that in the optical tunneling regime, the laser-induced red shift has the same law as that in the direct current （DC） approximation. Though the scales are the same in the optical tunneling regime, the physical pictures in the two cases are quite different. The electro-absorption in the DC case is a tunneling-assisted transition process, while the laser-induced electro-absorption is a mixed multi-photon process.

An entirely new approach based on remote sensing data to calculate the nitrogen nutrition index of winter wheat

The nitrogen nutrition index(NNI)is a reliable indicator for diagnosing crop nitrogen(N)status.However,there is currently no specific vegetation index for the NNI inversion across multiple growth periods.To overcome the limitations of the traditional direct NNI inversion method(NNI_(T1))of the vegetation index and traditional indirect NNI inversion method(NNI_(T2))by inverting intermediate variables including the aboveground dry biomass(AGB)and plant N concentration(PNC),this study proposed a new NNI remote sensing index(NNI_(RS)).A remote-sensing-based critical N dilution curve(Nc_(_RS))was set up directly from two vegetation indices and then used to calculate NNI_(RS).Field data including AGB,PNC,and canopy hyperspectral data were collected over four growing seasons(2012–2013(Exp.1),2013–2014(Exp.2),2014–2015(Exp.3),2015–2016(Exp.4))in Beijing,China.All experimental datasets were cross-validated to each of the NNI models(NNI_(T1),NNI_(T2)and NNI_(RS)).The results showed that:(1)the NNI_(RS)models were represented by the standardized leaf area index determining index(sLAIDI)and the red-edge chlorophyll index(CI_(red edge))in the form of NNI_(RS)=CI_(red edge)/(a×sLAIDI~b),where"a"equals 2.06,2.10,2.08 and 2.02 and"b"equals 0.66,0.73,0.67 and 0.62 when the modeling set data came from Exp.1/2/4,Exp.1/2/3,Exp.1/3/4,and Exp.2/3/4,respectively;(2)the NNI_(RS)models achieved better performance than the other two NNI revised methods,and the ranges of R2 and RMSE were 0.50–0.82 and 0.12–0.14,respectively;(3)when the remaining data were used for verification,the NNI_(RS)models also showed good stability,with RMSE values of 0.09,0.18,0.13 and 0.10,respectively.Therefore,it is concluded that the NNI_(RS)method is promising for the remote assessment of crop N status.

Identification of Contamination Information of Vegetation in Coal Mines Based on Hyperspectral Remote Sensing Data

The development and application of the hyper-spectral remote sensing (HRS) in the environment investiga-tion and evaluation of coal mines have been discussed in detail. By using Hyperion HRS technology and field spectrummeasuring and integrating traditional geological method as well as laboratory chemical measurement, the absorptionspectrum features and the spectral variation rules of vegetation caused by coal mine waste piles were studied. Based onthe spectral modeling methods and Vegetation Red Edge Parameter (VREP), the diagnose spectra information andspectral variation parameter were extracted, and the mapping methods of VREP were researched. The spatial distribu-tions of contaminative vegetation have been quickly found out.This study has provided technical supports for the envi-ronment investigation and pollution management of coal mines.

Quantitative estimation of photosynthetic pigments using new spectral indices

Foliar chlorophylls are the most important pigments related to the physiological function of plants. Quantitative estimation of photosynthetic pigments can provide important information about relationships between plants and their environmental conditions. In this study, new spectral indices were designed to enhance spectral resistance to noise, using the area of the spectral curve and axis. The specific area was around the red edge （Rdaa）, instead of the sum of the first derivative of the spectrum, specifically the area of red edge （Rda）. Meanwhile, three reference indices were also introduced as non-sensitive bands of chlorophylls. The results show that by dividing spectral references, a kind of re-projection, the spectral indices can be calibrated to allow direct and reasonable comparisons of the results. The sensitivity of these reference indices to chlorophylls was also evaluated in this study. The regression results show that Rdaa and its derivates are highly related to chlorophylls and resistant to noise.

Integrating volunteered smartphone data with multispectral remote sensing to estimate forest fuels

Volunteered data sources are readily available due to advances in electronic communications technology.For example,smartphones provide tools to collect ground-based observations over broad areas from a diverse set of data collectors,including people with,and without,extensive training.In this study,volunteers used a smartphone application to collect ground-based observations.Forest structural components were then estimated over a broader area using high spatial resolution RapidEye remote sensing imagery(5 spectral bands 440–850 nm,5 m spatial resolution)and a digital elevation model following a three nearest neighbor approach(K-NN).Participants with professional forestry experience on average chose highpriority fuel load locations near buildings,while nonprofessional participants chose a broader range of conditions over a larger extent.When used together,the professional and nonprofessional observations provided a more complete assessment of forest conditions.A generalized framework is presented that utilizes K-NN imputation tools for estimating the distribution of forest fuels using remote sensing and topography variables,ensuring spatial representation,checking attribute accuracy,and evaluating predictor variables.Frameworks to integrate volunteered data from smartphone platforms with remote sensing may contribute toward more complete Earth observation for Digital Earth.

Wavelet-based threshold denoising for imaging hyperspectral data

Imaging spectroradiometer is highly susceptible to noise.Accurately quantitative processing with higher quality is obligatory before any derivative analysis,especially for precision agricultural application.Using the self-developed Pushbroom Imaging Spectrometer(PIS),a wavelet-based threshold(WT)denoising method was proposed for the PIS imaging hyperspectral data.The WT with PIS was evaluated by comparing with other popular denoising methods in pixel scale and in regional scale.Furthermore,WT was validated by chlorophyll concentration retrieval based on red-edge position extraction.The result indicated that the determination coefficient R2 of the chlorophyll concentration inversion model of winter wheat leaves was improved from 0.586 to 0.811.It showed that the developed denoising method allowed effective denoising while maintaining image quality,and presented significant advantages over conventional methods.

Influence of Metal Cations and Cholesterol on Lipid-amphotericin Membrane

Amphotericin B（AmB） has been widely used in antifungal therapy. AraB molecules combine with cholesterol to form pores that can be toxic to human cells, thus greatly limiting its clinical application. The interaction between Arab and the cell membrane may be influenced by potassimn, sodium and calcium ions. Lq this study, the bilayer in large unilamellar lipid-drug liposomes with or without cholesterol was employed as a model membrane. N-（7-Nitrobenz-2-oxa-1,3-diazol-4-yl）-1,2-dipalmitoyl-sn-glycero-3-phosphoetheanolamine（N-BD-PE） and 1-palmi-toyl-2-[6（7-nitrobenz-2-oxa-1,3-diazol-4-yl）aminodoclecanoyl]-sn-glysero-3-phosphocholine（6-NBD-PC） are two kinds of fluorescent lipid probes, and the NBD group is attached to the polar lipid headgroup in the former, but to the sn-2 fatty acyl chain in the latter. The effect of these metal cations on the lipid-drug membrane was monitored by red edge excitation shift（REES）, fluorescence polarization, and the fluorescence lifetime of lipid probes in hydrophilic and hydrophobic areas of the membrane. These ions have different effects on the lipid-AraB membrane. Cholesterol can strengthen the packing ability of the membrane, which is influenced differently by potassium, sodium and calcium ions. Moreover, the influence of these ions on the membrane may be relative to the method of ion transportation through the membrane. This study is significant to understand the reduction of AraB＇s cellular toxicity.