Using in‐situ measurements to evaluate the new RapidEye™ satellite series for prediction of wheat nitrogen status

This study assessed whether vegetation indices derived from broadband RapidEye^? data containing the red edge region (690–730 nm) equal those computed from narrow band data in predicting nitrogen (N) status of spring wheat (Triticum aestivum L.). Various single and combined indices were computed from in‐situ spectroradiometer data and simulated RapidEye^? data. A new, combined index derived from the Modified Chlorophyll Absorption Ratio Index (MCARI) and the second Modified Triangular Vegetation Index (MTVI2) in ratio obtained the best regression relationships with chlorophyll meter values (Minolta Soil Plant Analysis Development (SPAD) 502 chlorophyll meter) and flag leaf N. For SPAD, r ² values ranged from 0.45 to 0.69 (p<0.01) for narrow bands and from 0.35 and 0.77 (p<0.01) for broad bands. For leaf N, r ² values ranged from 0.41 to 0.68 (p<0.01) for narrow bands and 0.37 to 0.56 (p<0.01) for broad bands. These results are sufficiently promising to suggest that MCARI/MTVI2 employing broadband RapidEye^? data is useful for predicting wheat N status.     

Predictors of whole-body vibration exposure experienced by highway transport truck operators

Whole-body-vibration (WBV) exposure levels experienced by transport truck operators were investigated to determine whether operator's exposure exceeded the 1997 International Standards Organization (ISO) 2631-1 WBV guidelines. A second purpose of the study was to determine which truck characteristics predicted the levels of WBV exposures experienced. The predictor variables selected based on previous literature and our transportation consultant group included road condition, truck type, driver experience, truck mileage and seat type. Tests were conducted on four major highways with 5 min random samples taken every 30 min of travel at speeds greater than or equal to 80 km/h (i.e. highway driving). Results indicated operators were not on average at increased risk of adverse health effects from daily exposures when compared to the ISO WBV guidelines. Significant regression models predicting the frequency-weighted RMS accelerations for the x (F _(5,97) = 8.63, p < 0.01), y (F _(5,97) = 7.74, p < 0.01), z (F _(5,61) = 9.83, p < 0.01) axes and the vector sum of the orthogonal axes (F _(5,61) = 13.89, p < 0.01) were observed. Road condition was a significant predictor (p < 0.01) of the frequency-weighted RMS accelerations for all three axes and the vector sum of the axes, as was truck type (p < 0.01) for the z-axis and vector sum. Future research should explore the effects of seasonal driving, larger vehicle age differences, greater variety of seating and suspension systems and team driving situations.     

Improving estimates of fractional vegetation cover based on UAV in alpine grassland on the Qinghai–Tibetan Plateau

Fractional vegetation cover (FVC) is an important parameter in studies of ecosystem balance, soil erosion, and climate change. Remote-sensing inversion is a common approach to estimating FVC. However, there is an important gap between ground-based surveys (quadrat level) and remote-sensing imagery (satellite image pixel scale) from satellites. In this study we evaluated that gap with unmanned aerial vehicle (UAV) aerial images of alpine grassland on the Qinghai–Tibetan Plateau (QTP). The results showed that: (1) the most accurate estimations of FVC came from UAV (FVC_UAV) at the satellite image pixel scale, and when FVC was estimated using ground-based surveys (FVC_ground), the accuracy increased as the number of quadrats used increased and was inversely proportional to the heterogeneity of the underlying surface condition; (2) the UAV method was more efficient than conventional ground-based survey methods at the satellite image pixel scale; and (3) the coefficient of determination (R²) between FVC_UAV and vegetation indices (VIs) was significantly greater than that between FVC_ground and VIs (p < 0.05, n = 5). Our results suggest that the use of UAV to estimate FVC at the satellite image pixel scale provides more accurate results and is more efficient than conventional ground-based survey methods.     

Airborne SAR monitoring of tree growth in a coniferous plantation

This paper examines three empirically based methods of monitoring forest growth between 1991 and 2000 from airborne synthetic aperture radar (SAR). In the first method, height change and volume change between 1991 and 2000 were estimated from the mean L‐band stand backscatter difference between the two dates. Height change and volume change over the 9‐year period were estimated with an accuracy of 0.23 m and 15 m³ ha^?1, respectively, when the stands were below saturation point for the first date. The accuracy of the results was lower for stands beyond saturation in both data sets. In the second method, the height change is calculated from the estimated stand height in 2000 minus the estimated stand height in 1991. The second method produced poorer results than the first method, but better results than predicted by the error propagation equation. The difference between the observed accuracy and the expected error (based on the error propagation equation) appears to be due to a systematic bias in both the 1991 and 2000 estimates, as the residuals are correlated for stands below 20 years old (r = 0.71 for stand volume residuals). The third experiment investigates the utility of data from two dates to classify the stands into three age classes. The results show that, with two images separated by 9 years, 85% of stands were correctly classified compared with 69% for a single date L‐HV image.     

Mapping tropical forest structure in southeastern Madagascar using remote sensing and artificial neural networks

Tropical forest condition has important implications for biodiversity, climate change and human needs. Structural features of forests can serve as useful indicators of forest condition and have the potential to be assessed with remotely sensed imagery, which can provide quantitative information on forest ecosystems at high temporal and spatial resolutions. Herein, we investigate the utility of remote sensing for assessing, predicting and mapping two important forest structural features, stem density and basal area, in tropical, littoral forests in southeastern Madagascar. We analysed the relationships of basal area and stem density measurements to the Normalised Difference Vegetation Index (NDVI) and radiance measurements in bands 3, 4, 5 and 7 from the Landsat Enhanced Thematic Mapper Plus (ETM+). Strong relationships were identified among all of the individual bands and field based measurements of basal area (p<0.01) while there were weak and insignificant relationships among spectral response and stem density measurements. NDVI was not significantly correlated with basal area but was strongly and significantly correlated with stem density (r=−0.69, p<0.01) when using a subset of the data, which represented extreme values. We used an artificial neural network (ANN) to predict basal area from radiance values in bands 3, 4, 5 and 7 and to produce a predictive map of basal area for the entire forest landscape. The ANNs produced strong and significant relationships between predicted and actual measures of basal area using a jackknife method (r=0.79, p<0.01) and when using a larger data set (r=0.82, p<0.01). The map of predicted basal area produced by the ANN was assessed in relation to a pre-existing map of forest condition derived from a semi-quantitative field assessment. The predictive map of basal area provided finer detail on stand structural heterogeneity, captured known climatic influences on forest structure and displayed trends of basal area associated with degree of human accessibility. These findings demonstrate the utility of ANNs for integrating satellite data from the Landsat ETM+ spectral bands 3, 4, 5 and 7 with limited field survey data to assess patterns in basal area at the landscape scale.     

Effects of spatial and spectral resolution in estimating ecosystem α-diversity by satellite imagery

Remote sensing represents a powerful tool to derive quantitative and qualitative information about ecosystem biodiversity. In particular, since plant species richness is a fundamental indicator of biodiversity at the community and regional scales, attempts were made to predict species richness (spatial heterogeneity) by means of spectral heterogeneity. The possibility of using spectral variance of satellite images for predicting species richness is known as Spectral Variation Hypothesis. However, when using remotely sensed data, researchers are limited to specific scales of investigation. This paper aims to investigate the effects of scale (both as spatial and spectral resolution) when searching for a relation between spectral and spatial (related to plant species richness) heterogeneity, by using satellite data with different spatial and spectral resolution. Species composition was sampled within square plots of 100 m² nested in macroplots of 10,000 m². Spectral heterogeneity of each macroplot was calculated using satellite images with different spatial and spectral resolution: a Quickbird multispectral image (4 bands, spatial resolution of 3 m), an Aster multispectral image (first 9 bands used, spatial resolution of 15 m for bands 1 to 3 and 30 m for bands 4 to 9), an ortho-Landsat ETM+ multispectral image (bands 1 to 5 and band 7 used; spatial resolution, 30 m), a resampled 60 m Landsat ETM+ image.Quickbird image heterogeneity showed a statistically highly significant correlation with species richness (r = 0.69) while coarse resolution images showed contrasting results (r = 0.43, r = 0.67, and r = 0.69 considering the Aster, Landsat ETM+, and the resampled 60 m Landsat ETM+ images respectively). It should be stressed that spectral variability is scene and sensor dependent. Considering coarser spatial resolution images, in such a case even using SWIR Aster bands (i.e. the additional spectral information with respect to Quickbird image) such an image showed a very low power in catching spectral and thus spatial variability with respect to Landsat ETM+ imagery. Obviously coarser resolution data tend to have mixed pixel problems and hence less sensitive to spatial complexity. Thus, one might argue that using a finer pixel dimension should inevitably result in a higher level of detail. On the other hand, the spectral response from different land-cover features (and thus different species) in images with higher spectral resolution should exhibit higher complexity.Spectral Variation Hypothesis could be a basis for improving sampling designs and strategies for species inventory fieldwork. However, researchers must be aware on scale effects when measuring spectral (and thus spatial) heterogeneity and relating it to field data, hence considering the concept of scale not only related to a spatial framework but even to a spectral one.     

Modelling forest stand volume and tree density using Landsat ETM+ data

Estimation of stand volume and tree density in a large area using remotely sensed data has considerable significance for sustainable management of natural resources. In this paper, we explore likely relationships between forest stand characteristics and Landsat Enhanced Thematic Mapper Plus (ETM+) reflectance values. We used multivariate regression technique to predict stand volume and tree density. The result showed that a linear combination of greenness and difference vegetation index (DVI) were better predictors of stand volume (adjusted R² = 43%; root mean square error (RMSE) = 97.4 m³ ha^?1) than other ETM+ bands and vegetation indices. In addition, the regression model with ETM4 (near infrared band) and ETM5 (first shortwave band) as independent variables was a better predictor of tree density (adjusted R² = 73.4%; RMSE = 170.13 ha^?1) than other combinations of ETM⁺ bands and vegetation indices. Results obtained from this study demonstrate the significant relationship between forest stand characteristics and ETM+ reflectance values and the utility of transformed bands in modelling stand volume and tree density. Based on the results of this study, we conclude that ETM+ data are useful to estimate forest volume and density and to gain insights into its structural characteristics in our study area. Forest managers could use ETM+ data for gaining insights into stand characteristics and generating maps required for developing forest management plans and identifying locations within stands that require treatments and other interventions.     

Resistance training and the enhancement of the gains in material-handling ability and physical fitness of British Army recruits during basic training

The aim was to evaluate the efficacy of a modified British Army basic training that included resistance training in improving material-handling performance and physical fitness, and to compare the modified training directly with the normal basic training. Forty-three males [19.2 (2.6) years of age, 1764 (72) mm in height, 73.0 (10.6) kg in mass] and nine females [19.1 (2.2) years, 1641 (67) mm, 62.0 (7.2) kg] performed the modified basic training. Testing occurred in the week before and in the final week of the 11-week basic training. Improvements with the modified training were observed for all six material-handling tests, including 8–12% for maximal box lifting, 15–19% for repetitive lifting and carrying and 9–17% for loaded marching (all p <0.01), and other established measures of aerobic fitness, strength and kinanthropometric characteristics. Significantly greater improvements were observed for the modified training compared with the normal training in maximal box lift to 1.45 m (12.4 versus 1.7%, p <0.01), 3.2 km loaded march performance with 15 kg (8.9 versus 3.6%, p <0.05), estimated fat-free mass (4.2 versus 1.5%, p <0.001), predicted [Vdot]O_2max (1 min ^-1) (9.3 versus 4.1%, p <0.01) and dynamic lift to 1.45 m (15.5 versus 0.2%, p <0.001). It was concluded that the improvements in material-handling ability and other aspects of physical fitness brought about in recruits by British Army basic training can be enhanced by the use of a physical training programme that includes a carefully designed resistance training element. Of particular note are the improvements shown in performance on material-handling tasks that require muscular strength, as these represent many of the tasks that soldiers encounter in their military careers.     

Remote sensing of photosynthetic light-use efficiency across two forested biomes: Spatial scaling

Eddy covariance (EC) measurements have greatly advanced our knowledge of carbon exchange in terrestrial ecosystems. However, appropriate techniques are required to upscale these spatially discrete findings globally. Satellite remote sensing provides unique opportunities in this respect, but remote sensing of the photosynthetic light-use efficiency (ε), one of the key components of Gross Primary Production, is challenging. Some progress has been made in recent years using the photochemical reflectance index, a narrow waveband index centered at 531 and 570 nm. The high sensitivity of this index to various extraneous effects such as canopy structure, and the view observer geometry has so far prevented its use at landscape and global scales. One critical aspect of upscaling PRI is the development of generic algorithms to account for structural differences in vegetation. Building on previous work, this study compares the differences in the PRI: ? relationship between a coastal Douglas-fir forest located on Vancouver Island, British Columbia, and a mature Aspen stand located in central Saskatchewan, Canada. Using continuous, tower-based observations acquired from an automated multi-angular spectro-radiometer (AMSPEC II) installed at each site, we demonstrate that PRI can be used to measure ? throughout the vegetation season at the DF-49 stand (r² = 0.91, p < 0.00) as well as the deciduous site (r² = 0.88, p < 0.00). It is further shown that this PRI signal can be also observed from space at both sites using daily observations from the Moderate Resolution Imaging Spectro-radiometer (MODIS) and a multi-angular implementation of atmospheric correction (MAIAC) (r² = 0.54 DF-49; r² = 0.63 SOA; p < 0.00). By implementing a simple hillshade model derived from airborne light detection and ranging (LiDAR) to approximate canopy shadow fractions (α_s), it is further demonstrated that the differences observed in the relationship between PRI and ε at DF-49 and SOA can be attributed largely to differences in α_s. The findings of this study suggest that algorithms used to separate physiological from extraneous effects in PRI reflectance may be more broadly applicable and portable across these two climatically and structurally different biome types, when the differences in canopy structure are known.     

Assessment of QuickBird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation

High spatial resolution remotely sensed data has the potential to complement existing forest health programs for both strategic planning over large areas, as well as for detailed and precise identification of tree crowns subject to stress and infestation. The area impacted by the current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia, Canada, has increased 40-fold over the previous 5 years, with approximately 8.5 million ha of forest infested in 2005. As a result of the spatial extent and intensity of the outbreak, new technologies are being assessed to help detect, map, and monitor the damage caused by the beetle, and to inform mitigation of future beetle outbreaks. In this paper, we evaluate the capacity of high spatial resolution QuickBird multi-spectral imagery to detect mountain pine beetle red attack damage. ANOVA testing of individual spectral bands, as well as the Normalized Difference Vegetation Index (NDVI) and a ratio of red to green reflectance (Red-Green Index or RGI), indicated that the RGI was the most successful (p < 0.001) at separating non-attack crowns from red attack crowns. Based on this result, the RGI was subsequently used to develop a binary classification of red attack and non-attack pixels. The total number of QuickBird pixels classified as having red attack damage within a 50 m buffer of a known forest health survey point were compared to the number of red attack trees recorded at the time of the forest health survey. The relationship between the number of red attack pixels and observed red attack crowns was assessed using independent validation data and was found to be significant (r² = 0.48, p < 0.001, standard error = 2.8 crowns). A comparison of the number of QuickBird pixels classified as red attack, and a broader scale index of mountain pine beetle red attack damage (Enhanced Wetness Difference Index, calculated from a time series of Landsat imagery), was significant (r² = 0.61, p < 0.001, standard error = 1.3 crowns). These results suggest that high spatial resolution imagery, in particular QuickBird satellite imagery, has a valuable role to play in identifying tree crowns with red attack damage. This information could subsequently be used to augment existing detailed forest health surveys, calibrate synoptic estimates of red attack damage generated from overview surveys and/or coarse scale remotely sensed data, and facilitate the generation of value-added information products, such as estimates of timber volume impacts at the forest stand level.     

Development of a national model of Pinus radiata stand volume from lidar metrics for New Zealand

Light detection and ranging (lidar) has been successfully used to describe a wide range of forest metrics at local scales. However, little research has tested the general applicability of this technology to describe commercially important stand dimensions, such as total stem volume (V), at national levels across broad environmental gradients.

Using an extensive national data set covering the spatial extent of Pinus radiata plantation forests in New Zealand, the key objectives of this study were to (1) develop regression models to best describe V for P. radiata from lidar metrics and (2) investigate whether these relationships could be improved using coincident environmental and stand-level information. Development of relationships between lidar metrics and forest volume are of particular importance for P. radiata, as this species constitutes approximately 90% of the 1.8 Mha plantation resource.

Using lidar mean height and the percentage of lidar ground returns, the initial model (model 1) accounted for 85% of the variance in V. Addition of stand stocking (number of stems ha^?1), measured within the plots, to the model (model 2) significantly (p < 0.001) improved predictions, with R ² increasing to 0.86 and the root mean square error declining from 80.1 m³ ha^?1 to 71.6 m³ ha^?1. For both models, partial responses show V to be most sensitive to lidar mean height, which was included in the model as a second-order polynomial.

Although environmental variables are established determinants for V, their inclusion did not significantly improve either model 1 or 2. Residual values for both models showed little apparent bias when plotted against stand-level information or a wide array of environmental variables, supporting the general applicability of these relationships.     

Sub-pixel evaluation of sea ice roughness using AMSR-E data

The rapidly changing sea ice regime in the Arctic has necessitated an evaluation of sea ice roughness at smaller scales than those provided by satellites. In this article, we evaluate sub-pixel (<5.4 km) sea ice roughness using AMSR-E brightness temperature (T_b) 89 GHz data and in situ physical roughness data acquired using a helicopter-based laser system in the southern Beaufort Sea during April–June of 2008. The analysis shows a statistically significant correlation (r² = 0.61, P-value < 0.05, regression line slope = –79.93) of T_b at horizontal polarization (H-pol) decreasing with increasing root mean square (RMS) heights. These results suggest that 89 H-pol is more sensitive (than vertical polarization (V-pol)) to the changes in physical roughness. The temporal evolution in AMSR-E T_b values at 89 H-pol and 89 V-pol shows a decrease from April to June. We conclude that solely the AMSR-E T_b at 5.4 km is insufficient to fully account for the changes occurring in the dielectric properties and surface roughness of sea ice at sub-pixel level of 1–4 km during April–June.     

Global and regional evaluation of the SeaWiFS chlorophyll data set

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll data set was compared to comprehensive archives of in situ chlorophyll data from NASA and NOAA. The global comparison indicated a root mean square (RMS) log error of 31%, with a coefficient of determination (r²) of 0.76, using 4168 data points where in situ and SeaWiFS data were coincident and collocated. RMS log error for open ocean (defined as bottom depth>200 m) was 27.7% with r²=0.72, compared to 33% RMS log error and r²=0.60 on the coasts, indicating a deterioration of quality of the SeaWiFS data set in coastal regions. All of the Pacific oceanographic basins generally showed very good agreement with SeaWiFS, as did the South Atlantic basin. However, poorer agreement was found in the Mediterranean/Black Seas, Equatorial Atlantic, and the Antarctic. Optical complexity arising from riverine inputs, Saharan dust, and anomalous oceanic constituents contributed to the differences observed in the Atlantic, where an overestimation by SeaWiFS occurred. The Antarctic indicated a pronounced negative bias, indicating an underestimation, especially for chlorophyll concentrations greater than about 0.15 mg m⁻³. The results provide a comprehensive global and geographic analysis of the SeaWiFS data set, which will assist data users and policy makers in assessing the uncertainty of estimates of global and regional ocean chlorophyll and primary production.     

Efficient parallel algorithms forr-dominating set andp-center problems on trees

We develop efficient parallel algorithms for ther-dominating set and thep-center problems on trees. On a concurrent-read exclusive-write PRAM, our algorithm for ther-dominating set problem runs inO(logn log logn) time withn processors. The algorithm for thep-center problem runs inO(log² n log logn) time withn processors.Xin He was supported in part by an Ohio State University Presidential Fellowship, and by the Office of Research and Graduate Studies of Ohio State University. Yaacov Yesha was supported in part by the National Science Foundation under Grant No. DCR-8606366.     

Dynamic control and conventional strength ratios of the quadriceps and hamstrings in subjects with anterior cruciate ligament deficiency

The hamstrings:quadriceps muscle strength ratio has been used as an indicator of normal balance between the knee flexors and extensors. A more functional approach to this strength ratio would be to compare opposite muscle actions of antagonistic muscle groups. The dynamic strength control ratio (DSCR) should give a more appropriate measure relating to knee function. There is a lack of normative data relating to DSCR for anterior cruciate ligament (ACL) deficient subjects. EVects of ACL deficiency on isokinetic peak torque for eccentric and concentric muscle actions of the quadriceps and hamstrings, in conjunction with isometric peak torque, were examined in 10 patients awaiting reconstructive surgery (male= 8, female= 2; age= 32.8 ± 8.3 years; height= 1.77 ± 0.08 m; mass= 72.1 ± 12.5 kg). These variables were assessed using an isokinetic dynamometer. The results were considered in terms of the conventional ratio and DSCR. Anterior tibial drawer was measured using a knee ligament arthrometer to confirm clinical diagnosis of ACL rupture. The isokinetic peak torque data analysed were for angular velocities of 1.05 rad s^?1 (60° s^?1). Significant strength deficits were apparent between normal and injured sides for: concentric isokinetic quadriceps action (p < 0.05); isometric quadriceps action at 70° of knee flexion (p < 0.05); isometric quadriceps action at 40° of knee flexion (p < 0.01); eccentric isokinetic hamstrings action (p < 0.05). With bilateral comparison, the conventional strength ratios showed no significant difference, as did the DSCR. The bilateral comparison of isometric strength ratios revealed significant losses in quadriceps strength for the injured side (p < 0.05) but no significant losses in hamstring strength (p > 0.05). Thus, differences can be seen in conventional ratios and DSCR for ACL-deficient subjects. This is an area of clinical interest with the increasing frequency of ACL reconstruction using hamstrings tendons.     

Effect of backpack fit on lung function

Carrying loads close to the trunk with a backpack causes a restrictive type of change in lung function in which Forced Vital Capacity (FVC) and Forced Expiratory Volume in 1?s (FEV₁) are reduced without a corresponding decrement in the FEV₁.FVC^???1 %. It is not known whether this is due to the weight of the load acting on the chest or to the tightness of fit of the shoulder and chest straps and waist belt of the pack harness. This study examined FVC, FEV₁, FEV₁.FVC^???1 %, peak expiratory flow (PEF), forced expiratory flow between 0.2 and 1.2?s (FEF_0.2?–?1.2) after the start of expiration and between 25 and 75% of each FVC (FEF_25?–?75%) in 12 healthy males wearing a 15?kg backpack in which the shoulder and chest straps and hip belt were loosened by 3?cm from a ‘comfort fit’ to achieve a ‘loose pack’ fit (LPF) and tightened by 3?cm from CF to achieve a ‘tight pack’ fit (TPF). In comparison with the control condition of no pack, a loose pack fit significantly reduced FVC (by 3.6%, p?<?0.01), FEV₁ (by 4.3%, p?<?0.01) and FEF_25?–?75% (by 8.4%, p?<?0.01). A tight pack fit significantly reduced FVC (by 8.1%, p?<?0.01) and FEV₁ (by 9.1%, p?<?0.001). It also significantly reduced FEF_0.2?–?1.2 (by 7.3%, p?<?0.05) and FEF_25?–?75% (by 21%, p?<?0.01). In comparison with a loose pack fit, the tight pack fit was associated with a significantly lower FVC (by 4.6%, p?<?0.01), FEV₁ (by 5.0%, p?<?0.01), FEF_25?–?75% (by 13.8%, p?<?0.01) and a fall in FEF_0.2?–?1.2 (by 5.5%). The latter was approaching significance (p?=?0.077). There were no significant changes in FEV₁.FVC^???1% and PEF. It is concluded that tightening the fit of a backpack significantly affects lung function in a manner that is typical of a restrictive change in lung function and is very similar in pattern to that of wearing a loosely fitted loaded backpack. The effect of tightness of fit is additional to that due to the weight of the load alone and may also reduce expiratory flow at low lung volumes.     

Discrimination of conifer height,age and crown closure classes using Landsat-5 TM imagery in the Canadian Northwest Territories

Empirical relationships between forest stand attributes and Landsat-5 Thematic Mapper spectral response were developed in order to assess its informational value in support of forest inventory operations in the Northwest Territories. An existing large-area classification procedure, based on a supervised methodology, has been able to generate classes of white spruce and jack pine. Within individual forest species groups, spectral variability related to differences in crown closure, height and age is of interest to forest managers in the region. The objective of this study was to determine the accuracy with which stands within the white spruce and jack pine classes could be further separated into two stand height classes (< 15 m and S 15 m), two age classes (< 100 years and S 100 years) and two crown closure classes (< 30% and S 30%) with a single (summer) Landsat-5 Thematic Mapper (TM) image. Discrimination generally improved with the addition of spectral texture measures where independently assessed accuracies ranged from 60 to 90%. A look-up table was devised for conifer-dominated areas (> 80% dominant species) which could subsequently be assigned for height, age and crown closure class values based on Landsat TM spectral response patterns.     

Resource allocation efficiency as an indicator of boredom,work performance and absence

Boredom has been implicated in a range of unfortunate behaviours from absenteeism to substance abuse. Here resource allocation efficiency is proposed as a proximal indicator of both boredom and work behaviour. Clerical volunteers (N = 89) completed a series of computer-based tasks in which puzzle-solving speed was taken as an indicator of resource allocation efficiency. Individual variability in puzzle-solving speed correlated, as predicted, with accuracy of work (r =-0.35, p< 0.01) and days absence (r = + 0.26, p< 0.05) as recorded in annual staff appraisals. Both these behaviours are considered boredom sensitive. These experiments suggest a direct way of predicting the consistency of key work-related behaviours.     

Sub-Constant Error Probabilistically Checkable Proof of Almost-Linear Size

We show a construction of a PCP with both sub-constant error and almost-linear size. Specifically, for some constant 0 < α < 1, we construct a PCP verifier for checking satisfiability of Boolean formulas that on input of size n uses log n+O((log n)^1-a)\log\, n+O((\log\, n)^{1-\alpha}) random bits to make 7 queries to a proof of size n·2^{O((log n)1-a)}n·2^{O((\log\, n)^{1-\alpha})}, where each query is answered by O((log n)^1-a)O((\log\, n)^{1-\alpha}) bit long string, and the verifier has perfect completeness and error 2^{-W((log n)a)}2^{-\Omega((\log\, n)^{\alpha})}.     

Global robust stabilization of nonlinear systems subject to input constraints

Our main purpose in this paper is to further address the global stabilization problem for affine systems by means of bounded feedback control functions, taking into account a large class of control value sets: p, r ‐weighted balls ??^m _r (p), with 1<p?∞, defined via p, r ‐weighted gauge functions. Observe that p=∞ is allowed, so that m‐dimensional r ‐hyperboxes ??^m _r (∞)?[?r₁^?,r₁⁺]×???×[?r_m^?,r_m⁺], r_j^±>0 are also considered. Working along the line of Artstein–Sontag's approach, we construct an explicit formula for a one‐parameterized family of continuous feedback controls taking values in ?? _r ^m(p) that globally asymptotically stabilize an affine system, provided an appropriate control Lyapunov function is known. The designed family of controls is suboptimal with respect to the robust stability margin for uncertain systems. The problem of achieving disturbance attenuation for persistent disturbances is also considered. Copyright © 2002 John Wiley & Sons, Ltd.