Bio-optical algorithm evaluation for MODIS for western Canada coastal waters: An exploratory approach using in situ reflectance

Biophysical and above-water reflectance measurements collected in 2006 were used to evaluate the OC3M, standard GSM01, and a modified version of the GSM01 algorithms for estimating chlorophyll-a (chl) concentrations in the Strait of Georgia, located off the southwest coast of Canada. The Strait was generally a case 2 water body, transitioning from chromophoric dissolved organic matter (CDOM) dominant in the central region to possibly particulate dominant in Fraser River plume regions. Results showed that the OC3M algorithm was somewhat effective (R² = 0.550) outside the most turbid areas of the Fraser River plume. However, a systematic overestimation of lower chl concentrations was found, which may have been related to the higher CDOM absorption observed throughout the Strait. The standard GSM01 algorithm had moderately good agreement with measured CDOM absorption (R² = 0.593) and total suspended solids (TSS) concentrations (R² = 0.888), but was ineffective at estimating chl concentrations. Localized characterization of the CDOM absorption, through a hyperbolic CDOM model, improved the modified GSM01 results with slightly better agreement with measure CDOM absorption (R² = 0.614) and TSS concentrations (R² = 0.933). When the modified GSM01 algorithm was limited to regions with lower combined CDOM and non-algal particulate absorption (a_dg (443) < 0.7 m^− 1), it was more effective then the OC3M algorithm at estimating chl concentrations. This suggests that a threshold value on the a_dg (443) or b_bp (443) estimated by the GSM01 algorithm may be beneficial for limiting turbidity influence on the algorithm. The further reinterpretation of phytoplankton absorption from the modified GSM01 algorithm with a two-component phytoplankton model resulted in a chl relationship with an R² = 0.677 and a linear slope closer to one.     

Enhancing a leaf radiative transfer model to estimate concentrations and in vivo specific absorption coefficients of total carotenoids and chlorophylls a and b from single-needle reflectance and transmittance

The relative concentrations of different pigments within a leaf have significant physiological and spectral consequences. Photosynthesis, light use efficiency, mass and energy exchange, and stress response are dependent on relationships among an ensemble of pigments. This ensemble also determines the visible characteristics of a leaf, which can be measured remotely and used to quantify leaf biochemistry and structure. But current remote sensing approaches are limited in their ability to resolve individual pigments. This paper focuses on the incorporation of three pigments—chlorophyll a, chlorophyll b, and total carotenoids—into the LIBERTY leaf radiative transfer model to better understand relationships between leaf biochemical, biophysical, and spectral properties.Pinus ponderosa and Pinus jeffreyi needles were collected from three sites in the California Sierra Nevada. Hemispheric single-leaf visible reflectance and transmittance and concentrations of chlorophylls a and b and total carotenoids of fresh needles were measured. These data were input to the enhanced LIBERTY model to estimate optical and biochemical properties of pine needles. The enhanced model successfully estimated reflectance (RMSE = 0.0255, BIAS = 0.00477, RMS%E = 16.7%), had variable success estimating transmittance (RMSE = 0.0442, BIAS = 0.0294, RMS%E = 181%), and generated very good estimates of carotenoid concentrations (RMSE = 2.48 µg/cm², BIAS = 0.143 µg/cm², RMS%E = 20.4%), good estimates of chlorophyll a concentrations (RMSE = 10.7 µg/cm², BIAS = − 0.992 µg/cm², RMS%E = 21.1%), and fair estimates of chlorophyll b concentrations (RMSE = 7.49 µg/cm², BIAS = − 2.12 µg/cm², RMS%E = 43.7%). Overall root mean squared errors of reflectance, transmittance, and pigment concentration estimates were lower for the three-pigment model than for the single-pigment model. The algorithm to estimate three in vivo specific absorption coefficients is robust, although estimated values are distorted by inconsistencies in model biophysics. The capacity to invert the model from single-leaf reflectance and transmittance was added to the model so it could be coupled with vegetation canopy models to estimate canopy biochemistry from remotely sensed data.     

Parallel algorithms for rounding exact evaluation of sums of products

We propose two parallel algorithms for the rounding exact evaluation of sums of products. The first method transforms products to sums and applies one of the known methods for rounding exact summation in time complexity O(n²) with n processors (n denoting the “length” of the expression). The second method approximates the products as well as the sum and has average time complexity O(ld(n)) for n/2 processors and has average time complexity O(n) viewed as a sequential algorithm.     

Synthesis and characterisation of nanosized TiO2-ZrO2 binary system prepared by an aqueous sol-gel process: Physical and sensing properties

Nanostructured TiO₂-ZrO₂ thin films and powders were prepared by a straightforward aqueous particulate sol-gel route. Titanium (IV) isopropoxide and zirconium (IV) acetate hydrate were used as precursors, and hydroxypropyl cellulose was used as a polymeric fugitive agent in order to increase the specific surface area. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy revealed that the powder were crystallised at the low temperature of 500 °C, containing anatase-TiO₂ and tetragonal-ZrO₂ phases. Furthermore, it was found that ZrO₂ retarded the anatase-to-rutile transformation up to 900 °C. The activation energies for crystallite growth of TiO₂ and ZrO₂ components in the binary system were calculated 10.16 and 3.12 kJ/mol, respectively. Transmission electron microscope (TEM) image showed that one of the smallest crystallite sizes was obtained for TiO₂-ZrO₂ binary mixed oxide, being 5 nm at 500 °C. Field emission scanning electron microscope (FESEM) analysis revealed that the deposited thin films had nanostructured morphology with the average grain size of 20 nm at 500 °C and 36 nm at 900 °C. Thin films produced under optimised conditions showed excellent microstructural properties for gas sensing applications. They exhibited a remarkable response towards low concentrations of CO and NO₂ gases at low operating temperature of 150 °C, resulted in an increase of thermal stability of sensing films as well as a decrease in the power consumption. Furthermore, calibration curves revealed that TiO₂-ZrO₂ sensor follows the power law, S = A[gas]^B (where S is sensor response, coefficients A and B are constants and [gas] is gas concentration) for the two types of gases, and it has excellent capability for the detection of low gas concentrations.     

Potentiometric urea biosensor based on urease immobilized by an electrosynthesized poly(o-phenylenediamine) film with buffering capability

A simple and novel potentiometric biosensor for urea detection was prepared by employing an electrosynthesized polymer with buffering capability. It was obtained by deposition of a weighed amount of urease (Ur) at a glassy carbon (GC) electrode followed by immobilization by an electrosynthesized poly-o-phenylenediamine (PPD) film. An unconventional “upside-down” (UD) geometry was employed for the electrochemical cell. The response of GC/Ur/PPD sensor is linear with urea concentration in the range 10 μM to 1 mM (15 mV/mM, R² = 0.9999) due to buffering capability of PPD film, which represents a novel role of electrosynthesized polymers in their application to biosensors. At higher concentrations, the more common Nernstian response (28 mV/decade, R² = 0.9987) is observed. The sensor exhibits a sufficient sensitivity for practical determinations, rapid response and long term stability.     

Estimation of instantaneous net surface longwave radiation from MODIS cloud-free data

This paper develops a statistical regression method to estimate the instantaneous Downwelling Surface Longwave Radiation (DSLR) for cloud-free skies using only the satellite-based radiances measured at the Top Of the Atmosphere (TOA), and subsequently combines the DSLR with the MODIS land surface temperature/emissivity products (MOD11_L2) to estimate the instantaneous Net Surface Longwave Radiation (NSLR). The proposed method relates the DSLR directly to the TOA radiances in the MODIS Thermal InfraRed (TIR) channels provided that the terrain altitude and the satellite Viewing Zenith Angle (VZA) are known. The simulation analysis shows that the instantaneous DSLR could be estimated by the proposed method with the Root Mean Square Error (RMSE) of 12.4 W/m² for VZA = 0 and terrain altitude z = 0 km. Similar results are obtained for the other VZAs and altitudes. Considering the MODIS instrumental errors of 0.25 K for the TOA brightness temperatures in channels 28, 33 and 34, and of 0.05 K for channels 29 and 31, and of 0.35 K for channel 36, the overall retrieval accuracy in terms of the RMSE is decreased to 13.1 W/m² for the instantaneous DSLR. Moreover, a comparison of MODIS derived DSLR and NSLR are done with the field measurements made at six sites of the Surface Radiation Budget Network (SURFRAD) in the United States for days with cloud-free conditions at the moment of MODIS overpass in 2006. The results show that the bias, RMSE and the square of the correlation coefficient (R²) between the MODIS derived DSLR with the proposed method and the field measured DSLR are 20.3 W/m², 30.1 W/m² and 0.91 respectively, and bias = 11.7 W/m², RMSE = 26.1 W/m² and R² = 0.94 for NSLR. In addition, the scheme proposed by Bisht et al. [Bisht, G., Venturini, V., Islam, S., & Jiang, L. (2005). Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear-sky days. Remote Sensing of Environment, 97, 52-67], which requires the MODIS atmospheric profile product (MOD07) and also the MODIS land surface temperature/emissivity products (MOD11_L2) as inputs, is used to estimate the instantaneous DSLR and NSLR for comparison with the field measurements as well as the MODIS derived DSLR and NSLR using our proposed method. The results of the comparisons show that, at least for our cases, our proposed method for estimating DSLR from the MODIS radiances at the TOA and the resultant NSLR gives results comparable to those estimated with Bisht et al.'s scheme [Bisht, G., Venturini, V., Islam, S., & Jiang, L. (2005). Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear-sky days. Remote Sensing of Environment, 97, 52-67].     

Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically active pigments,chlorophyll a and phycocyanin

Nuisance blue-green algal blooms contribute to aesthetic degradation of water resources by means of accelerated eutrophication, taste and odor problems, and the production of toxins that can have serious adverse human health effects. Current field-based methods for detecting blooms are costly and time consuming, delaying management decisions. Methods have been developed for estimating phycocyanin concentration, the accessory pigment unique to freshwater blue-green algae, in productive inland water. By employing the known optical properties of phycocyanin, researchers have evaluated the utility of field-collected spectral response patterns for determining concentrations of phycocyanin pigments and ultimately blue-green algal abundance. The purpose of this research was to evaluate field spectroscopy as a rapid cyanobacteria bloom assessment method. In-situ field reflectance spectra were collected at 54 sampling sites on two turbid reservoirs on September 6th and 7th in Indianapolis, Indiana using ASD Fieldspec (UV/VNIR) spectroradiometers. Surface water samples were analyzed for in-vitro pigment concentrations and other physical and chemical water quality parameters. Semi-empirical algorithms by Simis et al. [Simis, S., Peters, S., Gons, H. (2005). Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water. American Society of Limnology and Oceanography 50(11): 237–245] were applied to the field spectra to predict chlorophyll a and phycocyanin absorption at 665 nm and 620 nm, respectively. For estimation of phycocyanin concentration, a specific absorption coefficient of 0.0070 m² mg PC^-1 for phycocyanin at 620 nm, a_PC^?(620), was employed, yielding an r² value of 0.85 (n = 48, p < 0.0001), mean relative residual value of 0.51 (σ = 1.41) and root mean square error (RMSE) of 19.54 ppb. Results suggest this algorithm could be a robust model for estimating phycocyanin. Error is highest in water with phycocyanin concentrations of less than 10 ppb and where phycocyanin abundance is low relative to chlorophyll a. A strong correlation between measured phycocyanin concentrations and biovolume measurements of cyanobacteria was also observed (r = 0.89), while a weaker relationship (r = 0.66) resulted between chlorophyll a concentration and cyanobacterial biovolume.     

Pharmacokinetics of insulin lispro in type 2 diabetes during closed-loop insulin delivery

Insulin pharmacokinetics is not well understood during continuous subcutaneous insulin infusion in type 2 diabetes (T2D). We analyzed data collected in 11 subjects with T2D [6 male, 9 white European and two of Indian ethnicity; age 59.7(12.1) years, BMI 30.1(3.9) kg/m², fasting C-peptide 1002.2(365.8) pmol/l, fasting plasma glucose 9.6(2.2) mmol/l, diabetes duration 8.0(6.2) years and HbA1c 8.3(0.8)%; mean(SD)] who underwent a 24-h study investigating closed-loop insulin delivery at the Wellcome Trust Clinical Research Facility, Cambridge, UK. Subcutaneous delivery of insulin lispro was modulated every 15 min according to a model predictive control algorithm. Two complementary insulin assays facilitated discrimination between exogenous (lispro) and endogenous plasma insulin concentrations measured every 15–60 min. Lispro pharmacokinetics was represented by a linear two-compartment model whilst parameters were estimated using a Bayesian approach applying a closed-form model solution. The time-to-peak of lispro absorption (t_max) was 109.6 (75.5–120.5) min [median (interquartile range)] and the metabolic clearance rate (MCR_I) 1.26 (0.87–1.56) × 10⁻² l/kg/min. MCR_I was negatively correlated with fasting C-peptide (r_s = −0.84; P = .001) and with fasting plasma insulin concentration (r_s = −0.79; P = .004). In conclusion, compartmental modelling adequately represents lispro kinetics during continuous subcutaneous insulin infusion in T2D. Fasting plasma C-peptide or fasting insulin may be predictive of lispro metabolic clearance rate in T2D but further investigations are warranted.     

Programs for generating Clebsch-Gordan coefficients of SU(3) in SU(2) and SO(3) bases

Computer codes are developed to calculate Clebsch-Gordan coefficients of SU(3) in both SU(2)- and SO(3)-coupled bases. The efficiency of this code derives from the use of vector coherent state theory to evaluate the required coefficients directly without recursion relations. The approach extends to other compact semi-simple Lie groups. The codes are given in subroutine form so that users can incorporate the codes into other programs.

Program summary

Title of program: SU3CGVCSCatalogue identifier: ADTNProgram summary URL:http://cpc.cs.qub.ac.uk/summaries/ADTNProgram obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: Persons requesting the program must sign the standard CPC non-profit use licenseComputers for which the program is designed and others on which it is operable: SGI Origin 2000, HP Apollo 9000, Sun, IBM SP, PentiumOperating systems under which the program has been tested: IRIX 6.5, HP UX 10.01, SunOS, AIX, LinuxProgramming language used: FORTRAN 77Memory required to execute with typical data: On the HP system, it requires about 732 KBytes.Disk space used for output: 2100+2460 bytesNo. of bits in a word: 32 bit integer and 64 bit floating point numbers.No. of processors used: 1Has the code been vectorized: NoNo. of bytes in distributed program, including test data, etc.: 26 309No. of lines in distributed program, including test data, etc.: 3969Distribution format: tar gzip fileNature of physical problem: The group SU(3) and its Lie algebra have important applications, for example, in elementary particle physics, nuclear physics, and quantum optics [1-3]. The code presented is particularly relevant for the last two fields. Clebsch-Gordan (CG) coefficients are required whenever the symmetries of many-body systems are used for the evaluation of matrix elements of tensor operators. Moreover, the construction of CG coefficients for SU(3) serves as a nontrivial prototype for larger compact semi-simple Lie algebras and even for non semi-simple Lie algebras. It is the simplest Lie algebra to have multiplicity in its outer products and a non-canonical subalgebra, i.e., SO(3).Method of solution: Vector coherent state theory is first used to construct bases for the products of two irreducible representations (irreps) [4]. The bases are SU(2)-coupled so that SU(2)-reduced CG (or isoscalar factors) can be constructed naturally. The CG coefficients in the SO(3) bases are constructed subsequently from the overlaps between the SU(2) and SO(3) bases.Restriction on the complexity of the problem: The programs are limited by computer memory and the maximum size of variable arrays. As dimension overflow conditions are possible, they are flagged and can be fixed by following the directions given as part of the error message.Typical running time: The calculation time for a single SU(3) CG coefficient is very different for SU(2) and SO(3) bases. It varies between 7.3-54.1 ns in SGI Origin 2000, 0.81-5.48 ms in HP Apollo 9000, or 0.055-0.373 ms in Intel Pentium 4 for SU(2) bases while it is between 0.027-0.255 s in Intel Pentium 4 for SO(3) bases.Unusual features of the program: Intrinsic bit functions: and, or, and shift, called iand, ior, and ishft, respectively, in FORTRAN, are used for packing and unpacking the labels for the irreps. Intrinsic logical btest is used to test the bit for the phase factor.References:[1] Y. Ne'eman, Nucl. Phys. 26 (1961) 222;  M. Gell-Man, Y. Ne'eman, The Eightfold Way, Benjamin, New York, 1964.[2] J.P. Elliott, Proc. Roy. Soc. A 245 (1958) 128, 562.[3] M. Reck, A. Zeilinger, H.J. Bernstein, P. Bertani, Phys. Rev. Lett. 73 (1994) 58;  B.C. Sanders, H. de Guise, D.J. Rowe, A. Mann, J. Phys. A 32 (1999) 7111.[4] D.J. Rowe, C. Bahri, J. Math. Phys. 41 (2000) 6544.     

Estimation of cyanobacterial pigments in a freshwater lake using OCM satellite data

Cyanobacteria represent a major harmful algal group in fresh to brackish water environments. Lac des Allemands, a freshwater lake of 49 km² southwest of New Orleans, Louisiana on the upper end of the Barataria Estuary, provides a natural laboratory for remote characterization of cyanobacterial blooms because of their seasonal occurrence. The Oceansat-1 satellite Ocean Colour Monitor (OCM) provides measurements similar to SeaWiFS but with higher spatial resolution, and this work is the first attempt to use OCM measurements to quantify cyanobacterial pigments. The satellite signal was first vicariously calibrated using SeaWiFS as a reference, and then corrected to remove the atmospheric effects using a customized atmospheric correction procedure. Then, empirical inversion algorithms were developed to convert the OCM remote sensing reflectance (R_rs) at bands 4 and 5 (centered at 510.6 and 556.4 nm, respectively) to concentrations of phycocyanin (PC), the primary cyanobacterial pigment. A holistic approach was used to minimize the influence of other optically active constituents on the PC algorithm. Similarly, empirical algorithms to estimate chlorophyll a (Chl a) concentrations were developed using OCM bands 5 and 6 (centered at 556.4 and 669 nm, respectively). The best PC algorithm (R² = 0.7450, p < 0.0001, n = 72) yielded a root mean square error (RMSE) of 36.92 μg/L with a relative RMSE of 10.27% (PC from 2.75 to 363.50 μg/L, n = 48). The best algorithm for Chl a (R² = 0.7510, p < 0.0001, n = 72) produced an RMSE of 31.19 μg/L with a relative RMSE of 16.56% (Chl a from 9.46 to 212.76 μg/L, n = 48). While more field data are required to further validate the long-term performance of these algorithms, currently they represent the best protocol for establishing a long time-series of cyanobacterial blooms in the Lac des Allemands using OCM data.     

A remote sensing/GIS-based physical template to understand the biogeochemistry of the Ji-Paraná river basin (Western Amazônia)

Amazônia is one of the most important ecosystems of the planet, containing the largest extent of contiguous tropical rain forest on earth, over 5 million square kilometers. While most of the region remains forested, rapid development has led, over the past two decades, to the destruction of over 589,000 km² of forests in Brazil alone. Forest clearing can alter the transport of sediments, organic matter and associated nutrients to the rivers. In this article, we present the results of an integrated analysis of the landscape characteristics, including soil properties, river network, topography, and land use/cover of a tropical meso-scale river. This physical template was developed as a comprehensive tool, based on Remote Sensing and GIS, to support the understanding of the biogeochemistry of surface waters of the Ji-Paraná river basin, State of Rondônia, Western Amazônia. Our primary objective was to demonstrate how this tool can help the understanding of complex environmental questions, such as the effects of land-use changes in the biogeochemistry of riverine systems. River sites and basin characteristics were calculated using the data sets compiled as layers in Arc-Info GIS. A land-use/cover map for 1999 was produced from a digital classification of Landsat 7-ETM⁺ images. To test the effects of the landscape characteristics on river water chemistry, we performed a multiple linear regression analysis. Average slope, river network density, effective cation exchange capacity (ECEC), and proportion of pasture were treated as independent variables. River water electrical conductivity (EC) and Na⁺, Ca²⁺, Mg²⁺, K⁺, Cl⁻ and PO₄³⁻ concentrations were the dependent variables. Spatially, higher values of all ions were associated with areas dominated by pasture, with the highest concentrations found in the central part of the basin, where pasture areas are at a maximum. As the river enters the lower reaches, forests dominate the landscape, and the concentrations drop. The percentage of the basin area covered by pasture was consistently the best predictor of EC (r²=0.872), PO₄³⁻ (r²=0.794), Na⁺ (r²=0.754), Cl⁻ (r²=0.692) and K⁺ (r²=0.626). For Ca²⁺, both ECEC (r²=0.538) and pasture (r²=0.502) explained most of the observed variability. The same pattern was found for Mg²⁺ (r²=0.498 and 0.502, respectively).     

Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes

The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of reflectance at 710 and 670 nm (R² = 0.832; RMSE = 29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R² = 0.984; RMSE = 3.98 mg m⁻³). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R² = 0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R² = 0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales.     

Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain

The aim of this study is to derive parameters from spectral variations associated with heavy metals in soil and to explore the possibility of extending the use of these parameters to hyperspectral images and to map the distribution of areas affected by heavy metals on HyMAP data. Variations in the spectral absorption features of lattice OH and oxygen on the mineral surface due to the combination of different heavy metals were linked to actual concentrations of heavy metals. The ratio of 610 to 500 nm (R_610,500 nm) in the visible and near-infrared (VNIR) range, absorption area at 2200 nm (Area_2200 nm), and asymmetry of the absorption feature at 2200 nm (Asym_2200 nm) showed significant correlations with concentrations of Pb, Zn, and As, respectively. The resulting spectral gradient maps showed similar spatial patterns to geochemical gradient maps. The ground-derived spectral parameters showed a reliable quantitative relationship with heavy metal levels based on multiple linear regression. To examine the feasibility to applying these parameters to a HyMAP image, image-derived spectral parameters were compared with ground-derived parameters in terms of R², one-way ANOVA, and spatial patterns in the gradient map. The R_1344,778 nm and Area_2200 nm parameters showed a weak relationship between the two datasets (R² > 0.5), and populations of spectral parameter values, Depth_500 nm, R_1344,778 nm, and Area_2200 nm derived from the image pixels were comparable with those of ground-derived spectral parameters along a section of the stream channel. The pixels classified in the rule image of Depth_500 nm, R_1344,778 nm, and Area_2200 nm derived from a HyMAP image showed similar spatial patterns to the gradient maps of ground-derived spectral parameters. The results indicate the potential applicability of the parameters derived from spectral absorption features in screening and mapping the distribution of heavy metals. Correcting for differences in spectral and spatial resolution between ground and image spectra should be considered for quantitative mapping and the retrieval of heavy metal concentrations from HyMAP images.     

Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties - the sill and the mean length scale metric - provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R² = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R² = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.     

A new parallel algorithm for lagrange interpolation on a hypercube

We present a new parallel algorithm for computing N point lagrange interpolation on an n-dimensional hypercube with total number of nodes p = 2ⁿ. Initially, we consider the case when N = p. The algorithm is extended to the case when only p (p fixed) processors are available, p < N. We assume that N is exactly divisible by p. By dividing the hypercube into subcubes of dimension two, we compute the products and sums appearing in Lagrange's formula in a novel way such that wasteful repetitions of forming products are avoided. The speed up and efficiency of our algorithm is calculated both theoretically and by simulating it over a network of PCs.     

Mechanism and kinetic study of 3-fluoropropene with hydroxyl radical reaction

Potential energy surface for the reaction of hydroxyl radical (OH) with 3-fluoropropene (CH₂CHCH₂F) has been studied to evaluate the reaction mechanisms, possible products and rate constants. It has been shown that the CH₂CHCH₂F with OH reaction takes place via a barrierless addition/elimination and hydrogen abstraction mechanism. It is revealed for the first time that the initial step for the barrierless additional process involves a pre-reactive loosely bound complex (CR1) that is 1.60 kcal/mol below the energy of the reactants. Subsequently, the reaction bifurcates into two different pathways to form IM1 (CH₂CHOHCH₂F) and IM2 (CH₂OHCHCH₂F), which can decompose or isomerize to various products via complicated mechanisms. Variational transition state model and multichannel RRKM theory are employed to calculate the temperature-, pressure-dependent rate constants and branching ratios. At atmospheric pressure with He as bath gas, IM1 formed by collisional stabilization is dominated at T ≤ 600 K; whereas the direct hydrogen abstraction leading to CH₂CHCHF and H₂O are the major products at temperatures between 600 and 3000 K, with estimated contribution of 72.9% at 1000 K. Furthermore, the predicted rate constants are in good agreement with the available experimental values.     

Application of optimization methods to solid phase analysis of combustion gases desulphurization products

The variations in calcium and sulphur concentrations measured along cross-sections of limestone-lime sulphated particles in scanning electron microscope (EDS microanalysis) and the computation of the sum of oxides CaO+SO₃, (s) and the molar ratio CaO/SO₃, (r) are essential to identifying the compounds which could appear.A method of estimating the phase of sulphation limestone/lime products is presented in this paper. The aim of this method is to find such component proportions which minimize the differences between the measured and the calculated values of s and r. The method is developed using the software package CAMOS and enables one to calculate automatically the component proportions for the given system. In the paper the CaS–CaSO₄–CaO–CaCO₃ and CaS–CaSO₄–CaO–Ca(OH)₂ systems are considered. Some experimental examples are also shown.     

Evaluation of satellite based primary production modelling in the semi-arid Sahel

The MODIS (Moderate Resolution Imaging Spectroradiometer) primary productivity products are evaluated against observed Above-ground Net Primary Production (AGNPP) in the semi-arid Senegal 2001. MODIS net primary productivity (NPP) modelling is a light use efficiency (LUE) based approach incorporating constraints on vegetation productivity arising from simulated radiation, water demand and temperature data from NASA's Data Assimilation Office (DAO). Annually integrated MODIS PSN (MOD17A2 net photosynthesis, Collection 4) explains more of the observed biomass variation (r² = 0.77) than MODIS fAPAR (fraction Absorbed Photosynthetically Active Radiation, Collection 4) (r² = 0.72), indicating the effect of including the canopy stress scalar (ε_s) based on DAO data combined with modelled maintenance respiration costs (of leaf and fine roots). Annual MODIS NPP (MOD17A3, Collection 4 (C4) and Collection 4.5 (C4.5)) including growth respiration and live wood maintenance respiration costs and modified DAO input (C4.5) however increases the residual unexplained observed AGNPP variance (C4 NPP; r² = 0.49) (C4.5 NPP; r² = 0.37). The overall quality of the annual NPP MODIS C4 and C4.5 products are moderate for the semi-arid Senegal because of the annual respiration cost modelling and a change in C4.5 biome-specific parameters stored in a Biome Properties Look-Up Table (BPLUT) is the main contributor to the observed discrepancy between C4 and C4.5 NPP. The dynamic range of the values of all MOD17 products was too low when compared to observed AGNPP. An estimate of canopy water stress (SIWSI; Shortwave Infrared Water Stress Index) derived from MODIS channels 2 and 6 and photosynthetically active radiation (PAR) irradiance derived from geostationary METEOSAT data were tested for primary production modelling using a stepwise linear regression analysis. PAR irradiance was combined with MODIS fAPAR into APAR (Absorbed Photosynthetically Active Radiation) explaining 79% of the observed AGNPP variation. Introducing SIWSI significantly increased the explained variance of observed AGNPP (r² = 0.89). MODIS-derived percentage tree cover was tested as a predictor based on the hypothesis that tree cover provides information on differences in respiratory costs between trees and grasses thereby accounting for variations in the LUE conversion efficiency ε. No significant reduction in residual unexplained AGNPP variance was found. Earth observation based derivation of PAR and canopy water stress from SIWSI suggest potential improvements to primary production models in semi-arid biomes that can be implemented in general NPP modelling LUE methodology.     

Remote sensing assessment of sediment re-suspension during Hurricane Frances in Apalachicola Bay, USA

Assessments of hurricane-induced environmental impacts are important to coastal management and risk analysis of ecosystems. In this study, a previously-developed remote sensing model for non-hurricane conditions by Wang et al. [Wang, H. Q., Hladik, C. M., Milla, K., Huang, W. R., Edmiston, L., Harwell, M. A., & Schalles, J. F. (in press). Detecting and mapping water quality indicators in Apalachicola Bay, Florida using MODIS Terra 250-m imagery. International Journal of Remote Sensing] has been substantially enhanced to investigate the impact of Hurricane Frances on total suspended solid (TSS) concentrations in Apalachicola Bay, Florida, USA. The remote sensing model uses 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) to map TSS concentrations in the Bay. Eleven additional satellite imageries of MODIS were used in the model improvement and calibration. TSS concentration computation in the present model has been substantially improved by using a two-step process: firstly producing atmospheric correction intercept by an approach of in-water reflectance regression, and then building the regression model (R² = 0.8534, n = 25) between 250-m MODIS reflectance and observed TSS concentrations, which includes an extreme high TSS concentration data of 208 mg/L for severe storm or hurricane condition. Also, we carried out the validation of model (RMSE = 5.5 mg/L, n = 21). MODIS-derived TSS maps show substantial increases of TSS concentrations in the Bay during the passage of Hurricane Frances (the average TSS and maximum concentration about 54.3 mg/L and 165 mg/L in the Bay respectively) compared to under no-storm or -hurricane condition ( the average TSS and maximum concentration were approximately 24-27 mg/L and 58-64 mg/L). In comparison to those before and 5-days after the passage of the hurricane, the average TSS concentration in the Bay was twice higher while the maximum TSS concentration increased almost three times during the hurricane. This indicates that strong winds during the hurricane have caused strong sediment re-suspension. The spatial variations of TSS concentrations were analyzed by applying the hydrodynamic characteristics of wind-induced flow and tidal currents as described by Huang [Huang, W., Jones, K., & Wu, T. (2002). Modeling surface wind effects on subtidal salinity in Apalachicola Bay. Estuarine, Coastal and Shelf Science, 55(1), 33−46; Huang, W., Sun, H., Nnaji, S., & Jones, K. (2002). Tidal hydrodynamics in a multiple inlet estuary: Apalachicola Bay. International Journal of Coastal Research, 18(4), 674−684], which show westward currents in the Bay under westward wind condition. Therefore, the southwestward wind (about 50° from the north) during the hurricane induced southwestward currents and transport that resulted in the high TSS concentrations near West Pass in the Bay and the Gulf. Within the Bay, TSS concentrations were generally higher in the southern portion of the Bay, which was due mainly to transport by the combination of southwestward wind and southward residual flow from the Apalachicola River.     

Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters

Model-data fusion offers considerable promise in remote sensing for improved state and parameter estimation particularly when applied to multi-sensor image products. This paper demonstrates the application of a ‘multiple constraints’ model-data fusion (MCMDF) scheme to integrating AMSR-E soil moisture content (SMC) and MODIS land surface temperature (LST) data products with a coupled biophysical model of surface moisture and energy budgets for savannas of northern Australia. The focus in this paper is on the methods, difficulties and error sources encountered in developing an MCMDF scheme and enhancements for future schemes. An important aspect of the MCMDF approach emphasized here is the identification of inconsistencies between model and data, and among data sets.The MCMDF scheme was able to identify that an inconsistency existed between AMSR-E SMC and LST data when combined with the coupled SEB-MRT model. For the example presented, an optimal fit to both remote sensing data sets together resulted in an 84% increase in predicted SMC and 0.06% increase for LST relative to the fit to each data set separately. That is the model predicted on average cooler LST's (∼ 1.7 K) and wetter SMC values (∼ 0.04 g cm^− 3) than the satellite image products. In this instance we found that the AMSR-E SMC data on their own were poor constraints on the model. Incorporating LST data via the MCMDF scheme ameliorated deficiencies in the SMC data and resulted in enhanced characterization of the land surface soil moisture and energy balance based on comparison with the MODIS evapotranspiration (ET) product of Mu et al. [Mu, Q., Heinsch, F.A, Zhao, M. and Running, S.W. (in press), Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sensing of Environment.]. Canopy conductance, g_C, and latent heat flux, λE, from the MODIS ET product were in good agreement with RMSEs for g_C = 0.5 mm s^− 1 and for λE = 18 W m^− 2, respectively. Differences were attributable to a greater canopy-to-air vapor pressure gradient in the MCMDF approach obtained from a more realistic partitioning of soil surface and canopy temperatures.