Evaluating hyperspectral imaging of wetland vegetation as a tool for detecting estuarine nutrient enrichment

Nutrient enrichment and eutrophication are major concerns in many estuarine and wetland ecosystems, and the need is urgent for fast, efficient, and synoptic ways to detect and monitor nutrients in wetlands and other coastal systems across multiple spatial and temporal scales. We integrated three approaches in a multi-disciplinary evaluation of the potential for using hyperspectral imaging as a tool to assess nutrient enrichment and vegetation responses in tidal wetlands. For hyperspectral imaging to be an effective tool, spectral signatures must vary in ways correlated with water nutrient content either directly, or indirectly via such proxies as vegetation responses to elevated nitrogen. Working in Elkhorn Slough, central California, where intensive farming practices generate considerable runoff of fertilizers and pesticides, we looked first for long- and short-term trends among temporally ephemeral point data for nutrients and other water quality characters collected monthly at 18 water sampling stations since 1988. Second, we assessed responses of the dominant wetland plant, Salicornia virginica (common pickleweed) to two fertilizer regimes in 0.25 m² experimental plots, and measured changes in tissue composition (C, H, N), biomass, and spectral responses at leaf and at canopy scales. Third, we used HyMap hyperspectral imagery (126 bands; 15–19 nm spectral resolution; 2.5 m spatial resolution) for a synoptic assessment of the entire wetland ecosystem of Elkhorn Slough. We mapped monospecific Salicornia patches (～ 56–500 m²) on the ground adjacent to the 18 regular water sampling sites, and then located these patches in the hyperspectral imagery to correlate long-term responses of larger patches to water nutrient regimes. These were used as standards for correlating plant canopy spectral responses with nitrogen variation described by the water sampling program. There were consistent positive relationships between nitrogen levels and plant responses in both the field experiment and the landscape analyses. Two spectral indices, the Photochemical Reflectance Index (PRI) and Derivative Chlorophyll Index (DCI), were correlated significantly with water nutrients. We conclude that hyperspectral imagery can be used to detect nutrient enrichment across three spatial and at least two temporal scales, and suggest that more quantitative information could be extracted with further research and a greater understanding of physiological and physical mechanisms linking water chemistry, plant properties and spectral imaging characteristics.     

Mason: morphological simplification

The traditional rounding and filleting morphological filters are biased. Hence, as r grows, the rounding R_r (S) of S shrinks and the filleting F_r (S) grows. A shape S is r-regular when R_r (S) = F_r (S) = S. The combinations F_r (R_r (S)) and R_r (F_r (S)) produce nearly r-regular shapes, but retain a bias: F_r (R_r (S)) is usually smaller than S and R_r (F_r (S)) is larger. To overcome this bias, we propose a new filter, called Mason. The r-mortar M_r (S) of S is F_r (S)–R_r (S), and the stability of a point P with respect to S is the smallest value of r for which P belongs to M_r (S). Stability provides important information about the shape’s imbedding that cannot be obtained through traditional topological or differential analysis tools. F_r (R_r (S)) and R_r (F_r (S)) only affect space in M_r (S). For each maximally connected component of M_r (S), Mason performs either F_r (R_r (S)) or R_r (F_r (S)), choosing the combination that alters the smallest portion of that component. Hence, Mason acts symmetrically on the shape and on its complement. Its output is guaranteed to have a smaller symmetric difference with the original shape than that of either combination F_r (R_r (S)) or R_r (F_r (S)). Many previously proposed shape simplification algorithms were focused on reducing the combinatorial storage or processing costs of a shape at the expense of the smoothness and regularity or altered the shape in regular portions that did not exhibit any high frequency complexity. Mason is the first shape simplification operator that is independent of the particular representation and offers the advantage of preserving portions of the boundary of S that are regular at the desired scale.     

Linking physiological responses,chlorophyll fluorescence and hyperspectral imagery to detect salinity stress using the physiological reflectance index in the coastal shrub,Myrica cerifera

Measurements of physiology, chlorophyll fluorescence and hyperspectral reflectance were used to detect salinity stress in the evergreen coastal shrub, Myrica cerifera on Hog Island, Virginia. Two experimental sites were used in our study, the oceanside of a M. cerifera thicket, which is exposed to sea spray, and the protected, leeside of the thicket. Using the physiological reflectance index (PRI), we were able to detect stress at both the canopy and landscape level. Monthly variations in stomatal conductance, photosynthesis, and relative water content indicated a strong summer drought response that was not apparent in chlorophyll fluorescence or in the water band index (WBI) derived from canopy and airborne reflectance measurements. In contrast, there were significant differences in both physiological measurements and tissue chlorides between the two sites used in the study, indicating salinity stress. This was reflected in measurements of PRI. There was a positive relationship between PRI measured at the canopy-level and light-adapted fluorescence (ΔF/F′_m; r² = 0.69). PRI was significantly lower on the oceanside of the Myrica cerifera thicket. PRI was not significantly related to NDVI (r² = 0.01) at the canopy-level and only weakly related (r² = 0.04) at the landscape-level, suggesting that the indices are independent. The chlorophyll index (CI) did not show any significant changes between the two sites. Frequency histograms of pixels sampled from airborne hyperspectral imagery revealed that the distribution of PRI was shifted to the right on the backside of the thicket relative to the oceanside and there was a significant difference between sites. These results suggest that PRI may be used for early identification of salt-stress and to identify areas across the landscape where community structure may change due to sea-level rise.     

Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content,leaf mass per area,leaf area index and leaf canopy biomass

This article aims at finding efficient hyperspectral indices for the estimation of forest sun leaf chlorophyll content (CHL, µg cm_leaf^? 2), sun leaf mass per area (LMA, g_{dry matter} m_leaf^? 2), canopy leaf area index (LAI, m²_leaf m_soil^? 2) and leaf canopy biomass (B_leaf, g_{dry matter} m_soil^? 2). These parameters are useful inputs for forest ecosystem simulations at landscape scale. The method is based on the determination of the best vegetation indices (index form and wavelengths) using the radiative transfer model PROSAIL (formed by the newly-calibrated leaf reflectance model PROSPECT coupled with the multi-layer version of the canopy radiative transfer model SAIL). The results are tested on experimental measurements at both leaf and canopy scales. At the leaf scale, it is possible to estimate CHL with high precision using a two wavelength vegetation index after a simulation based calibration. At the leaf scale, the LMA is more difficult to estimate with indices. At the canopy scale, efficient indices were determined on a generic simulated database to estimate CHL, LMA, LAI and Bleaf in a general way. These indices were then applied to two Hyperion images (50 plots) on the Fontainebleau and Fougères forests and portable spectroradiometer measurements. They showed good results with an RMSE of 8.2 µg cm^? 2 for CHL, 9.1 g m^? 2 for LMA, 1.7 m² m^? 2 for LAI and 50.6 g m^? 2 for Bleaf. However, at the canopy scale, even if the wavelengths of the calibrated indices were accurately determined with the simulated database, the regressions between the indices and the biophysical characteristics still had to be calibrated on measurements. At the canopy scale, the best indices were: for leaf chlorophyll content: ND_chl = (ρ₉₂₅ ? ρ₇₁₀)/(ρ₉₂₅ + ρ₇₁₀), for leaf mass per area: ND_LMA = (ρ₂₂₆₀ ? ρ₁₄₉₀)/(ρ₂₂₆₀ + ρ₁₄₉₀), for leaf area index: D_LAI = ρ₁₇₂₅ ? ρ₉₇₀, and for canopy leaf biomass: ND_Bleaf = (ρ₂₁₆₀ ? ρ₁₅₄₀)/(ρ₂₁₆₀ + ρ₁₅₄₀).     

Identifying plant species using mid-wave infrared (2.5–6 μm) and thermal infrared (8–14 μm) emissivity spectra

Plant species discrimination using remote sensing is generally limited by the similarity of their reflectance spectra in the visible, NIR and SWIR domains. Laboratory measured emissivity spectra in the mid infrared (MIR; 2.5 μm–6 μm) and the thermal infrared (TIR; 8 μm–14 μm) domain of different plant species, however, reveal significant differences. It is anticipated that with the advances in airborne and space borne hyperspectral thermal sensors, differentiation between plant species may improve. The laboratory emissivity spectra of thirteen common broad leaved species, comprising 3024 spectral bands in the MIR and TIR, were analyzed. For each wavelength the differences between the species were tested for significance using the one way analysis of variance (ANOVA) with the post-hoc Tukey HSD test. The emissivity spectra of the analyzed species were found to be statistically different at various wavebands. Subsequently, six spectral bands were selected (based on the histogram of separable pairs of species for each waveband) to quantify the separability between each species pair based on the Jefferies Matusita (JM) distance. Out of 78 combinations, 76 pairs had a significantly different JM distance. This means that careful selection of hyperspectral bands in the MIR and TIR (2.5 μm–14 μm) results in reliable species discrimination.     

Discrete return lidar-based prediction of leaf area index in two conifer forests

Leaf area index (LAI) is a key forest structural characteristic that serves as a primary control for exchanges of mass and energy within a vegetated ecosystem. Most previous attempts to estimate LAI from remotely sensed data have relied on empirical relationships between field-measured observations and various spectral vegetation indices (SVIs) derived from optical imagery or the inversion of canopy radiative transfer models. However, as biomass within an ecosystem increases, accurate LAI estimates are difficult to quantify. Here we use lidar data in conjunction with SPOT5-derived spectral vegetation indices (SVIs) to examine the extent to which integration of both lidar and spectral datasets can estimate specific LAI quantities over a broad range of conifer forest stands in the northern Rocky Mountains. Our results show that SPOT5-derived SVIs performed poorly across our study areas, explaining less than 50% of variation in observed LAI, while lidar-only models account for a significant amount of variation across the two study areas located in northern Idaho; the St. Joe Woodlands (R² = 0.86; RMSE = 0.76) and the Nez Perce Reservation (R² = 0.69; RMSE = 0.61). Further, we found that LAI models derived from lidar metrics were only incrementally improved with the inclusion of SPOT 5-derived SVIs; increases in R² ranged from 0.02–0.04, though model RMSE values decreased for most models (0–11.76% decrease). Significant lidar-only models tended to utilize a common set of predictor variables such as canopy percentile heights and percentile height differences, percent canopy cover metrics, and covariates that described lidar height distributional parameters. All integrated lidar-SPOT 5 models included textural measures of the visible wavelengths (e.g. green and red reflectance). Due to the limited amount of LAI model improvement when adding SPOT 5 metrics to lidar data, we conclude that lidar data alone can provide superior estimates of LAI for our study areas.     

A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation

Accurate assessment of phytoplankton chlorophyll-a (chla) concentrations in turbid waters by means of remote sensing is challenging due to the optical complexity of case 2 waters. We have applied a recently developed model of the form [R_rs^? 1(λ₁) ? R_rs^? 1(λ₂)] × R_rs(λ₃) where R_rs(λ_i) is the remote-sensing reflectance at the wavelength λ_i, for the estimation of chla concentrations in turbid waters. The objectives of this paper are (a) to validate the three-band model as well as its special case, the two-band model R_rs^? 1(λ₁) × R_rs(λ₃), using datasets collected over a considerable range of optical properties, trophic status, and geographical locations in turbid lakes, reservoirs, estuaries, and coastal waters, and (b) to evaluate the extent to which the three-band model could be applied to the Medium Resolution Imaging Spectrometer (MERIS) and two-band model could be applied to the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate chla in turbid waters.The three-band model was calibrated and validated using three MERIS spectral bands (660–670 nm, 703.75–713.75 nm, and 750?757.5 nm), and the 2-band model was tested using two MODIS spectral bands (λ₁ = 662–672, λ₃ = 743–753 nm). We assessed the accuracy of chla prediction in four independent datasets without re-parameterization (adjustment of the coefficients) after initial calibration elsewhere. Although the validation data set contained widely variable chla (1.2 to 236 mg m^? 3), Secchi disk depth (0.18 to 4.1 m), and turbidity (1.3 to 78 NTU), chla predicted by the three-band algorithm was strongly correlated with observed chla (r² > 0.96), with a precision of 32% and average bias across data sets of ? 4.9% to 11%. Chla predicted by the two-band algorithm was also closely correlated with observed chla (r² > 0.92); however, the precision declined to 57%, and average bias across the data sets was 18% to 50.3%. These findings imply that, provided that an atmospheric correction scheme for the red and NIR bands is available, the extensive database of MERIS and MODIS imagery could be used for quantitative monitoring of chla in turbid waters.     

Remote sensing of canopy light use efficiency in temperate and boreal forests of North America using MODIS imagery

Light use efficiency (LUE) is an important variable characterizing plant eco-physiological functions and refers to the efficiency at which absorbed solar radiation is converted into photosynthates. The estimation of LUE at regional to global scales would be a significant advantage for global carbon cycle research. Traditional methods for canopy level LUE determination require meteorological inputs which cannot be easily obtained by remote sensing. Here we propose a new algorithm that incorporates the enhanced vegetation index (EVI) and a modified form of land surface temperature (T_m) for the estimation of monthly forest LUE based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Results demonstrate that a model based on EVI × T_m parameterized from ten forest sites can provide reasonable estimates of monthly LUE for temperate and boreal forest ecosystems in North America with an R² of 0.51 (p < 0.001) for the overall dataset. The regression coefficients (a, b) of the LUE–EVI × T_m correlation for these ten sites have been found to be closely correlated with the average EVI (EVI_ave, R² = 0.68, p = 0.003) and the minimum land surface temperature (LST_min, R² = 0.81, p = 0.009), providing a possible approach for model calibration. The calibrated model shows comparably good estimates of LUE for another ten independent forest ecosystems with an overall root mean square error (RMSE) of 0.055 g C per mol photosynthetically active radiation. These results are especially important for the evergreen species due to their limited variability in canopy greenness. The usefulness of this new LUE algorithm is further validated for the estimation of gross primary production (GPP) at these sites with an RMSE of 37.6 g C m^? 2 month^? 1 for all observations, which reflects a 28% improvement over the standard MODIS GPP products. These analyses should be helpful in the further development of ecosystem remote sensing methods and improving our understanding of the responses of various ecosystems to climate change.     

Using QuickBird imagery and a production efficiency model to improve crop yield estimation in the semi-arid hilly Loess Plateau,China

Crop yield is a key element in rural development and an indicator of national food security. A method that could estimate crop yield over large hilly areas would be highly desirable. Methods including high spatial resolution satellite imagery have the potential to achieve this objective. This paper describes a method of integrating QuickBird imagery with a production efficiency model (PEM) to estimate crop yield in Zhonglianchuan, a hilly area on Loess Plateau, China. In the PEM model, crop yield is a function of the photosynthetic active radiation (PAR), fraction of absorbed photosynthetically active radiation (f_APAR) and light-use efficiency (LUE). Based on the high spatial resolution QuickBird imagery, a land cover classification is used to attribute a class-specific LUE. The f_APAR is related to spectral vegetation indices (SVI), which can be derived from the satellite images. The LUE, f_APAR and incident PAR data were combined to estimate the crop yield. Farmer-reported crop yield data in 80 representative plots were used to validate the model output. The results indicated QuickBird imagery can improve the accuracy of predicted results relative to the Landsat TM image. The predicted yield approximated well with the data reported by the farmers (r² = 0.86; n = 80). The spatial distributions of crop yield derived here also offers valuable information to manage agricultural production and understand ecosystem functioning.     

Fabrication and characterization of a thermal switch

The development of a thermal switch based on arrays of liquid–metal micro-droplets is presented. Prototype thermal switches are assembled from a silicon substrate on which is deposited an array of 1600 30-μm liquid–metal micro-droplets. The liquid–metal micro-droplet array makes and breaks contact with a second bare silicon substrate. A gap between the two silicon substrates is filled with either air at 760 Torr, air at of 0.5 Torr or xenon at 760 Torr. Heat transfer and thermal resistance across the thermal switches are measured for “on” (make contact) and “off” (break contact) conditions using guard-heated calorimetry. The figure of merit for a thermal switch, the ratio of “off” state thermal resistance over “on” state thermal resistance, R_off/R_on, is 129 ± 43 for a xenon-filled thermal switch that opens 100 μm and 60 ± 17 for an 0.5 Torr air-filled thermal switch that opens 25 μm. These thermal resistance ratios are shown to be markedly higher than values of R_off/R_on for a thermal switch based on contact between polished silicon surfaces. Transient temperature measurements for the liquid–metal micro-droplet switches indicate thermal switching times of less than 100 ms. Switch lifetimes are found to exceed one-million cycles.     

Evaluation of a non-point source pollution model,AnnAGNPS, in a tropical watershed

Impaired water quality caused by human activity and the spread of invasive plant and animal species has been identified as a major factor of degradation of coastal ecosystems in the tropics. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized Non-Point Source Pollution Model), in simulating runoff and soil erosion in a 48 km² watershed located on the Island of Kauai, Hawaii. The model was calibrated and validated using 2 years of observed stream flow and sediment load data. Alternative scenarios of spatial rainfall distribution and canopy interception were evaluated. Monthly runoff volumes predicted by AnnAGNPS compared well with the measured data (R² = 0.90, P < 0.05); however, up to 60% difference between the actual and simulated runoff were observed during the driest months (May and July). Prediction of daily runoff was less accurate (R² = 0.55, P < 0.05). Predicted and observed sediment yield on a daily basis was poorly correlated (R² = 0.5, P < 0.05). For the events of small magnitude, the model generally overestimated sediment yield, while the opposite was true for larger events. Total monthly sediment yield varied within 50% of the observed values, except for May 2004. Among the input parameters the model was most sensitive to the values of ground residue cover and canopy cover. It was found that approximately one third of the watershed area had low sediment yield (0–1 t ha⁻¹ y⁻¹), and presented limited erosion threat. However, 5% of the area had sediment yields in excess of 5 t ha⁻¹ y⁻¹. Overall, the model performed reasonably well, and it can be used as a management tool on tropical watersheds to estimate and compare sediment loads, and identify “hot spots” on the landscape.     

Factors responsible for the aggregation behavior of hydrophobic polyelectrolyte PEA in aqueous solution studied by molecular dynamics simulations

Self-association (i.e. interchain aggregation) behavior of atactic poly(ethacrylic acid) PEA in dilute aqueous solution as function of degree-of-neutralization by Na⁺ counter-ions (i.e. charge fraction f) was investigated by molecular dynamics simulations. Aggregation is found to occur in the range 0 ≤ f ≤0.7 in agreement with experimental results compared at specified polymer concentration C_p = 0.36 mol/l in dilute solution. The macromolecular solution was characterized and analysed for radius-of-gyration, torsion angle distribution, inter and intra-molecular hydrogen bonds, radial distribution functions of intermolecular and inter-atomic pairs, inter-chain contacts and solvation enthalpy. The PEA chains form aggregate through attractive inter-chain interaction via hydrogen bonding, in the range f < 0.7, in agreement with experimental observation. The numbers of inter-chain contacts decreases with f. A critical structural transition occurs at f = 0.7, observed via simulations for the first time, in R_g as well as inter-chain H-bonds. The inter-chain distance increases with f due to repulsive interactions between COO− groups on the chains. PEA-PEA electrostatic interactions dominant solvation enthalpy. The PEA solvation enthalpy becomes increasingly favorable with increase in f. The transition enthalpy change, in going from uncharged (acid) state to fully charged state (f = 1) is unfavorable towards aggregate formation.     

Evaluation of the absolute affinity of neuraminidase inhibitor using steered molecular dynamics simulations

The absolute free energy difference of binding (ΔG) between neuraminidase and its inhibitor was evaluated using fast pulling of ligand (FPL) method over steered molecular dynamics (SMD) simulations. The metric was computed through linear interaction approximation. Binding nature was described by free energy differences of electrostatic and van der Waals (vdW) interactions. The finding indicates that vdW metric is dominant over electrostatics in binding process. The computed values are in good agreement with experimental data with a correlation coefficient of R = 0.82 and error of σΔG_exp = 2.2 kcal/mol. The results were observed using Amber99SB-ILDN force field in comparison with CHARMM27 and GROMOS96 43a1 force fields. Obtained results may stimulate the search for an Influenza therapy.     

Design of high speed gate driver employing IZO TFTs

This paper presents a new bi-side gate driver integrated by indium-zinc-oxide thin film transistors (IZO TFTs). Our optimized operate method can achieve high speed performance by employing a lower duty ratio (25%) CK2 with its pulse located in the middle of the pulse of CK2L to fully use the bootstrapped high voltage of node Q. In addition, the size of devices is optimized by calculation and simulation, and the function of the proposed gate driver is predicted by the circuit simulation. Furthermore, the proposed gate driver with 20 stages is fabricated by the IZO TFTs process. It is shown that a 2.6 μs width pulse with good noise-suppressed characteristic can be successfully output at the condition of R_load = 6 kΩ and C_load = 150 pF. The power consumption of the proposed gate driver with 20 stages is measured as 1 mW. Hence, the proposed gate driver may be applied to the display of 4K resolution (4096 × 2160) at a frame rate of 120 Hz. Moreover, there is a good stability for the proposed gate driver under 48 h operation.     

Curves of Genus 2 with (N,N) Decomposable Jacobians

Let C be a curve of genus 2 and ψ₁: C  −  → E ₁  a map of degree n, from C to an elliptic curveE₁ , both curves defined over C. This map induces a degree n map φ₁:P¹  −  → P ¹  which we call a Frey–Kani covering. We determine all possible ramifications for φ₁. If ψ₁:C  −  → E ₁  is maximal then there exists a maximal map ψ₂: C  −  → E ₂  , of degree n, to some elliptic curveE₂ such that there is an isogeny of degree n²from the JacobianJ_C to E₁ × E₂. We say thatJ_C is (n, n)-decomposable. If the degree n is odd the pair (ψ₂, E₂) is canonically determined. For n =  3, 5, and 7, we give arithmetic examples of curves whose Jacobians are (n, n)-decomposable.     

Assessment of grape yield and composition using the reflectance based Water Index in Mediterranean rainfed vineyards

In rainfed vineyards water deficits play a major role in determining berry yield and composition. Therefore, reliable indicators of vine water status might be of great value for the optimization of grape yield and quality. In the present study the feasibility of using hyperspectral reflectance indices related to plant biophysical properties at predicting berry yield and quality attributes in rainfed vineyards is assessed. The study was conducted on Vitis vinifera cv. Chardonnay in commercial vineyards in the D.O. Penedès region (Catalonia, Spain) over two consecutive years (2007–2008). Field measurements of fractional intercepted Photosynthetic Active Radiation (fIPAR), canopy reflectance, predawn water potential (Ψ_p) and the canopy to air temperature difference at midday (ΔT_midday) were conducted at the stage of veraison. Yield, Total Soluble Solids (TSS), Titratable Acidity (TA) and the ratio TSS/TA (maturation index, IMAD) were determined at harvest. Contrasted water availability among vineyards prompted considerable variation in berry yield and quality attributes. Across years, higher yield was accompanied by higher TA (r = 0.59, p < 0.01) and lower IMAD (r = ? 0.63, p < 0.01) while no significant relationship was observed between yield and TSS. Yield was related to canopy vigor (fIPAR) in a variable extend: in 2007, yield was positively related to fIPAR (r = 0.71, p < 0.05) while yield was found to decrease along with increasing fIPAR in 2008 (r = ? 0.62, p < 0.05). Contrastingly, NDVI provided consistent estimates of yield across years (r = 0.57, p < 0.05). These results suggest that NDVI might be more appropriate to characterize the effects of varying water availability on yield than fIPAR. In addition, yield was found to be related to ΔT_midday (r = ? 0.63 and r = ? 0.66, in 2007 and 2008, respectively). Accordingly, the Water Index (WI), an indicator of vine water status, provided robust estimates of yield across years (r = 0.61, p < 0.01). The strength of the correlation between NDVI and WI vs. yield suggests that yield was influenced by changes in both leaf area (intercepted light) and photosynthesis (stomatal aperture) in a variable extent according to the timing and severity of water deficits in the years of study. Berry quality attributes did not show significant relationships against fIPAR but were related to ΔT_midday. Accordingly, NDVI did not show significant correlation with berry quality attributes, while WI was found to be consistently related to TA (r = 0.70, p < 0.01) and IMAD (r = ? 0.71, p < 0.01) across years. The results obtained suggest that the WI might provide reliable estimates of berry quality attributes in vineyards experiencing moderate to severe water deficits with potential application in precision viticulture activities such as selective harvesting according to grape quality attributes as well as for ripening assessment.     

Performance analysis of networks of queues under active queue management scheme

Analysis of networks of queues under repetitive service blocking mechanism has been presented in this paper. Nodes are connected according to an arbitrary configuration and each node in the networks employs an active queue management (AQM) based queueing policy to guarantee certain quality of service for multiple class external traffic. This buffer management scheme has been implemented using queue thresholds. The use of queue thresholds is a well known technique for network traffic congestion control. The analysis is based on a queue-by-queue decomposition technique where each queue is modelled as a GE/GE/1/N queue with single server, R (R ⩾ 2) distinct traffic classes and {N = N₁, N₂, … , N_R} buffer threshold values per class under first-come-first-serve (FCFS) service rule. The external traffic is modelled using the generalised exponential (GE) distribution which can capture the bursty property of network traffic. The analytical solution is obtained using the maximum entropy (ME) principle. The forms of the state and blocking probabilities are analytically established at equilibrium via appropriate mean value constraints. The initial numerical results demonstrate the credibility of the proposed analytical solution.