Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data

Fires in boreal and temperate forests play a significant role in the global carbon cycle. While forest fires in North America (NA) have been surveyed extensively by U.S. and Canadian forest services, most fire records are limited to seasonal statistics without information on temporal evolution and spatial expansion. Such dynamic information is crucial for modeling fire emissions. Using the daily Advanced Very High Resolution Radiometer (AVHRR) data archived from 1989 to 2000, an extensive and consistent fire product was developed across the entire NA forest regions on a daily basis at 1-km resolution. The product was generated following data calibration, geo-referencing, and the application of an active fire detection algorithm and a burned area mapping algorithm. The spatial-temporal variation of forest fire in NA is analyzed in terms of (1) annual and monthly patterns of fire occurrences in different eco-domains, (2) the influence of topographic factors (elevation zones, aspect classes, and slope classes), and (3) major forest types and eco-regions in NA. It was found that 1) among the 12 years analyzed, 1989 and 1995 were the most severe fire years in NA; 2) the majority of burning occurred during June-July and in low elevation zones (< 500 m) with gentle slopes (< 10°), except in the dry eco-domain where more fires occurred in higher elevation zones (> 2000 m); 3) most fires occurred in the polar eco-domain, sub-arctic eco-division, and in the taiga ( boreal forests), forest-tundras and open woodlands eco-provinces in the boreal forests of Canada. The tendency for multiple burns to occur increases with elevation and slope until about 2500 m elevation and 24° slope, and decreases therefore. In comparison with ground observations, the omission and commission errors are on the order of 20%.     

On simultaneous on-line state and parameter estimation in non-linear state-space models

On-line estimation plays an important role in process control and monitoring. Obtaining a theoretical solution to the simultaneous state-parameter estimation problem for non-linear stochastic systems involves solving complex multi-dimensional integrals that are not amenable to analytical solution. While basic sequential Monte-Carlo (SMC) or particle filtering (PF) algorithms for simultaneous estimation exist, it is well recognized that there is a need for making these on-line algorithms non-degenerate, fast and applicable to processes with missing measurements. To overcome the deficiencies in traditional algorithms, this work proposes a Bayesian approach to on-line state and parameter estimation. Its extension to handle missing data in real-time is also provided. The simultaneous estimation is performed by filtering an extended vector of states and parameters using an adaptive sequential-importance-resampling (SIR) filter with a kernel density estimation method. The approach uses an on-line optimization algorithm based on Kullback–Leibler (KL) divergence to allow adaptation of the SIR filter for combined state-parameter estimation. An optimal tuning rule to control the width of the kernel and the variance of the artificial noise added to the parameters is also proposed. The approach is illustrated through numerical examples.     

SPOT VEGETATION for characterizing boreal forest fires

The potential of the recent SPOT VEGETATION (VGT) sensor for characterizing boreal forest fires was investigated. Its capability for hotspot detection and burned area mapping was assessed by analysing a series of VGT, NOAA/AVHRR, and Landsat TM images over a 1541 km²     

A biophysically based and objective satellite seasonality observation method for applications over the Arctic

Despite wide applications of remote-sensing data with high temporal resolution for monitoring phenology, two persistent problems have prevented the realization of their full potential. The first is the subjectivity in defining thresholds for a phenological event (e.g. the start or end of growing season ? SOS or EOS). The second is the use of various arbitrarily selected filtering and smoothing algorithms for constructing vegetation index seasonal profiles in order to reduce the noise caused by residue cloud contamination and aerosol variations. In this study, we addressed both problems by developing a biophysically based and objective satellite seasonality observation method (BLOSSOM) for application over Canada’s Arctic. Application of the BLOSSOM method to three northern Canadian national parks (Ivvavik, Wapusk, and Sirmilik) proved that the method is operational. Using the uncertainties in the vegetation index and its threshold, we estimated the overall mean uncertainties as being ?5.3 to 3.4 days, ?4.2 to 5.2 days, and ?6.2 to 8.4 days, respectively, for SOS, EOS, and growing season length (GSL). Further independent tests against SOS, determined using records of snow cover at nearby climate stations (as ‘truth’), indicate that the mean absolute error is less than 3.6 ± 0.2 days.     

Analysis for TNF-alpha using solid-phase affinity capture with radiolabel and MALDI-MS detection.

Screening of mutant mice for subtle phenotypes requires sensitive, high-throughput analyses of sentinel proteins in functional pathways. The cytokine TNF-alpha is upregulated during inflammatory reactions associated with autoimmune diseases. We have developed a method to monitor the concentration of TNF-alpha under physiological conditions. TNF-alpha is captured, purified, and concentrated using monoclonal antibody-coated microbeads. The capture is efficient (> 80%) and can be used in the concentration range < 100 pg/mL to > 50 ng/mL, as determined by detection of 125I-labeled TNF-alpha. The bead capture of TNF-alpha can be combined with direct detection by MALDI-MS for sample concentrations of > 10 ng/mL. TNF-alpha can be captured and detected from diluted mouse serum, with minimal interferences observed in the MALDI spectrum. This method is adaptable to high-throughput sample handling with microfluidic devices and automated mass spectrometric analysis.     

The Cognitive Interview: A meta-analytic review and study space analysis of the past 25 years.

The Cognitive Interview (CI) is a well-established protocol for interviewing witnesses. The current article presents a study space analysis of laboratory studies of the CI together with an empirical meta-analysis summarizing the past 25 years of research. The study space comprises 57 published articles (65 experiments) on the CI, providing an assessment of the boundary conditions underlying the analysis and application of this interview protocol. The current meta-analysis includes 46 published articles, including 20 articles published since the last meta-analysis conducted a decade earlier (K?hnken, Milne, Memon, & Bull, 1999). Reassuringly for practitioners, the findings of the original meta-analysis were replicated with a large and significant increase in correct details and a small increase in errors. In addition we found that there were no differences in the rate at which details are confabulated. Importantly, the effect sizes were unaffected by the inclusion of recent studies using modified versions of the CI. The CI appeared to benefit older adult witnesses even more than younger adults. We highlight trends and gaps in research and discuss how our findings can inform policy and training decisions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Second-sphere Coordination of [Pt(bipy)(NH3)2]2+ by Dibenzo-crown Ethers. Solution Spectroscopic Studies and the Crystal and Molecular Structures of [Pt(bipy)(NH3)2.dibenzo-30-crown-10] [PF6]2.0.6 H2O and [Pt(bipy)(NH3)2.dibenzo-24-crown-8] [PF6]2

In addition to hydrogen bonding and Coulombic forces, charge transfer interactions stabilise the 1:1 adducts formed between [Pt(bipy)(NH₃)₂] ²⁺ and a series of dibenzo-3n-crown-n (n = 6–12) ethers as evidenced by ¹H NMR and UV-visible spectra in solution and by X-ray crystal structures (for n = 8 and 10) in the solid state. Mutual diamagnetic (ring current) shielding by the aromatic systems of host and guest results in dramatic upfield shifts of certain aromatic proton resonances on adduct formation, especially when n = 10 or 11. A broad charge-transfer absorption band at 350 nm attains its maximum intensity at n = 11 though stability constant measurements indicate optimum binding when n = 10. X-ray diffraction studies reveal that, when n = 8, only one of the crown ether benzo-rings interacts with the bipyridyl ligand in a charge-transfer sense. However, when n = 10, the macrocycle is sufficiently large and flexible to allow both benzo-rings to enter into stabilising interactions with the bipyridyl ligand such that the platinum complex is encapsulated by the host in a U-shaped cavity.     

Gate bias polarity dependence of charge trapping and time-dependentdielectric breakdown in nitrided and reoxidized nitrided oxides

The gate bias polarity dependence of charge trapping and time-dependent dielectric breakdown (TDDB) in nitrided and reoxidized nitrided silicon dioxides prepared by rapid thermal processing (RTP) is reported. Charge trapping during high-field injection can be reduced by rapid thermal nitridation for both substrate and gate injection. While reoxidation of nitrided oxides shows further reduction in charge trapping for substrate injection, degradation is observed for gate injection. Similar effects are observed for TDDB: reoxidized nitrided oxides show charge-to-breakdown in excess of 300 C/cm² for substrate injection, but less than 30 C/cm² for gate injection. These effects are related to the nitrogen and hydrogen profiles in the oxides. By tailoring the process conditions, a symmetric behavior of NO and RONO films with low charge trappings and Q _BD in excess of 50 C/cm² is possible, making them attractive as long-lifetime dielectrics from EEPROM (electrically erasable programmable ROM) and flash EEPROM technologies