A Comparison of Hyperspectral Chlorophyll Indices for Wheat Crop Chlorophyll Content Estimation Using Laboratory Reflectance Measurements

The objective of this paper is to investigate the relationship between a wide range of hyperspectral chlorophyll indices and wheat crop chlorophyll content using laboratory measurements. These measurements included the GER-3700 spectroradiometric data, leaf chlorophyll content using the Soil-Plant Analyses Development (SPAD)-502 meter and leaf chlorophyll content estimated from chemical laboratory analysis. The SPAD-502 readings were correlated with leaf chlorophyll content extracted in the laboratory to establish calibration equations for the computation of chlorophyll-ab (Chl-ab) and chlorophyll-a (Chl-a) content. This resulted in a coefficient of determination (R2) of 0.72 for the Chl-ab content and 0.69 for the Chl-a content and a root mean square error (RMSE) of 3.53 and 1.94 mug/cm², respectively. These estimates were used to establish relationships against hyperspectral chlorophyll indices calculated from the GER-3700 data. From the investigated indices, the NPCI showed the best results with R2 of 0.84 and RMSE of 11.0. The other indices, such as GNDVI, OSAVI, PSSR_a, PSND_a, CAI, HNDVI, and MTCI did not perform satisfactorily. The better ones, but still showing a relatively week relationship with leaf chlorophyll content, are the indices NDPI, SIPI, PRI and SRPI with R^2's of 0.56, 0.62, 0.54, and 0.57, respectively and RMSEs of 11.06, 10.27, 11.32, and 10.96 mug/cm², respectively.     

Three-dimensional mathematical modeling of dispersed two-phase flow using class method of population balance in bubble columns

Computational fluid dynamics (CFD) simulations of bubble columns have received recently much attention and several multiphase models have been developed, tested, and validated through comparison with experimental data. In this work, we propose a model for two-phase flows at high phase fractions. The inter-phase forces (drag, lift and virtual mass) with different closure terms are used and coupled with a classes method (CM) for population balance. This in order to predict bubble’s size distribution in the column which results of break-up and coalescence of bubbles. Since these mechanisms result greatly of turbulence, a dispersed k– turbulent model is used.The results are compared to experimental data available from the literature using a mean bubble diameter approach and CM approach and the appropriate formulations for inter-phase forces in order to predict the flow are highlighted.The above models are implemented using the open source package OpenFoam.     

Estimating and mapping crop residues cover on agricultural lands using hyperspectral and IKONOS data

Crop residues left on agricultural lands after harvest play an important role in controlling and protecting soil against water and wind erosion. One challenge of remote sensing is to differentiate crop residues from bare soil and crop cover, especially when the residues have been weathered and/or when the crop cover phenology is more advanced. Several techniques for mapping and estimating crop residues exist in the literature. However, these methods are time consuming and not suited for quantitative evaluation. They have the disadvantage of being less rigorous and accurate because they do not consider the spectral mixture of different materials in the same pixel. In this study, the potential of hyperspectral (Probe-1) and multispectral high spatial resolution (IKONOS) data were compared for estimating and mapping crop residues on agricultural lands using the constrained linear spectral mixture analysis approach. Image data were spectrally and radiometrically calibrated, atmospherically corrected, as well as geometrically rectified. Pure spectral signatures of residues, bare soil and crop cover were manually extracted from image data based on prior knowledge of the fields. Percent (fraction) cover for each sampling point was extracted using unmixing and validated against ground reference measurements. The best results were achieved for the crop cover (index of agreement (D) = 0.92 and root mean square error (RMSE) = 0.09) adjusted for the impurity of the endmembers canola, pea and wheat, followed by the wheat residues (D = 0.76 and RMSE = 0.12). Considering only the wheat residues in fields with a canola crop, D increases to 0.86. The soil fractions were generally underestimated with D = 0.72, and no significant improvements could be made after adjusting for the shadow effect. The estimations from the IKONOS data were poorer for the same cover types (residues: D = 0.40 and RMSE = 0.24; crop: D = 0.51 and RMSE = 0.38; soil: D = 0.58 and RMSE = 0.29). Relative to the IKONOS data, the better performance of the hyperspectral data is mainly due to the improved spectral band characteristics, especially in the SWIR, which is sensitive to the residues (lignin and cellulose absorption features), soil and crop cover.     

Statistical properties of soil moisture images derived from Radarsat-1 SAR data

In this article, we report on the assessment of the spatial variability of soil moisture using synthetic aperture radar (SAR) data. The imagery was acquired during five different periods over the Roseau River watershed in southern Manitoba, Canada. For validation purposes, ground measurements were carried out at 62 locations simultaneous with the satellite data acquisitions. The first step in this analysis was to assess the performance of the Integral Equation Model (IEM) in simulating backscatter coefficients for selected bare soils. In order to reduce the surface roughness effect on radar backscatter, a semi-empirical calibration technique was implemented. This calibrated model was then implemented in a simplex inversion routine in order to estimate and map soil moisture. Derived spatial patterns of near-surface moisture content were then examined using scale analyses. It has been confirmed that the variance of radar-based soil moisture images follows power law decay versus the observation scale. Also, more explicit analysis of the same soil moisture maps shows a ln–ln linear spatial scale with statistical moments. Concave shape dependency of the corresponding slopes with the moment order was observed during all radar acquisition periods. The latter indicates the presence of multifractal effects.     

Mass transfer and shear in an airlift bioreactor: Using a mathematical model to improve reactor design and performance

Several studies have shown a strong relationship between morphology and agitation ( [Cui et al., 1997] and [Berzins et al., 2001] ). The shear stress distribution and mass transfer are the important parameters which can improve the performance of bioreactor. In this work, a mathematical model using computational fluid dynamics (CFD) techniques is used to study the gas–liquid dispersion in an airlift reactor. Multiple rotating frame (MRF) technique is used to approximate the movement of the impeller in the stationary reactor. Population balance modeling (PBM) is used to describe the dynamics of the time and space variation of bubble sizes in the reactor. The PBM equation is solved using an approximate method known as the class method (CM) and the bubble sizes are approximated through a discrete number of size ‘bins’, including transport, and different bubble phenomena. These equations of the CM are then written as scalar transport equations and added to the multiphase fluid mechanical equations describing the dynamics of the flow. All these equations are solved using control volume formulation through the use of an open-source CFD package OpenFOAM. The model is used to analyze an existing geometry of an airlift bioreactor and validate the modification on the initial design. The new design of airlift gives a clear performance by the increase of the global and local mass transfer and the decrease of the shear stress.     

Instrument and technique for the in vitro screening of platelet activation from whole blood samples

The measurement of platelet activation is very difficult to accomplish clinically as platelets are readily activated by in vitro manipulations. Although techniques such as platelet aggregation and flow cytometry exist to estimate platelet function, important limitations prevent these techniques to be widely accepted. In this study, low-fouling surfaces used to limit ex vivo platelet activation were locally bioactivated to rapidly detect platelet activation from whole blood through the selective local adhesion and aggregation of artificially activated platelets. To achieve this result, a fabrication method was developed to create arrays of anti-CD62 and anti-CD61 proteins covalently immobilized on substrates covered by low-fouling graft layers. Moreover, to further limit ex vivo platelet activation and to obtain reproducible results, a custom-made flow chamber was designed and fabricated with the help of computer-assisted mathematical modeling to create defined shear environments. This diagnostic instrument has the potential to allow the rapid estimation of platelet activation levels in whole blood.     

Potential of Getis statistics to characterize the radiometric uniformity and stability of test sites used for the calibration of Earth observation sensors

The calibration of airborne and satellite remote sensing sensors is a fundamental step for the rigorous validation of products derived from satellite data. Because of the inaccessibility of Earth Observation Satellites on orbit, the direct calibration method based on a test site with ground reference data is often considered necessary. However, the problem of radiometric spatial uniformity and temporal stability of test sites constitutes an important issue in the accuracy achieved in calibration operations and the long-term characterization of satellite sensor radiometry. Generally, the coefficient of variation and semivariograms are the most widely used tools for evaluating the radiometric uniformity and stability of a calibration site. In this study, we analyze for the first time the potential of Getis statistics compared to the coefficient of variation for the study of the radiometric spatial uniformity and temporal stability of the Lunar Lake Playa, Nevada (LLPN) test site. The results obtained show the potential and the importance of the synergy generated by these two methods for analyzing the radiometric temporal stability of the LLPN site. Getis statistics provide an excellent spatial analysis of the site while the coefficient of variation provides complementary information on the temporal evolution of the site.