Variations In Surface Conditions Research Articles

Causal relationship between seasonal variation in surface roughness and dust and sandstorm occurrence in arid and semi-arid Mongolia

In this study, the causal relationship between seasonal variations in surface conditions and DSS generation was investigated through the integrated use of the C-band backscatter coefficient (J 0) of the Sentinel 1 microwave satellite from the optical satellite sensor (Terra/MODIS). Because of the very high reflectance of the background soil in sparsely vegetated bare land, it has been difficult to rely solely on optical satellite data for accurate surface condition assessment in previous studies. Therefore, we used SAR and optical data to represent the spatial variability of backscatter coefficients for different surface conditions in the Gobi Desert and Steppe areas, and employed the C-band backscatter coefficient from the Sentinel-1 microwave satellite as a key parameter. The results show that in the Gobi Desert region, the correlation between the seasonal variation of backscatter coefficients and NDVI is highly significant, with a maximum correlation coefficient in fall (R=0.645, p<0.001) an inverse correlation in summer (R=-0.216, p<0.001), indicating little seasonal variation between NDVI and backscatter coefficients. In conclusion, surface roughness (σ0) is relatively low and stable from winter to the following spring and increases with plant growth in summer. In the Gobi Desert region, surface roughness changes little throughout the year, but in the steppe region, surface roughness increases with vegetation growth during the rainy season, which suppresses the generation of DSS.

Widespread Permafrost Degradation and Thaw Subsidence in Northwest Canada

AbstractLong‐term (1991–2018) thaw tube measurements highlight widespread permafrost thaw and ground surface (GS) subsidence over a large portion of northwest Canada. Statistically significant positive trends in thaw penetration (TP), measured with respect to a fixed datum, were observed at 18 of 28 sites with data that span three decades at a median rate of 0.8 cm a−1. This rate implies thawing of about 22 cm of permafrost over the study period. Similarly significant trends in GS subsidence occurred at 21 of 28 sites, at a median rate of 0.4 cm a−1. In contrast with TP and GS elevation, long‐term trends in active layer thickness (ALT) were less consistent, with 10 of 28 sites having statistically significant trends indicating increasing ALT (median rate: 0.6 cm a−1), and 7 sites having trends indicating decrease in ALT (median: 0.3 cm a−1). The ALT measurements underestimated the thawing of ice‐rich permafrost due to GS subsidence. Sites with high rates of thaw had relatively warm permafrost, deep snow cover, and poor drainage. Masking of ice‐rich permafrost degradation by ALT measurements has important implications for modeling permafrost thaw and climate change reporting. Accurate simulation of ice‐rich permafrost thaw is conceivable for sites where conditions are well‐defined. However, the prediction of subsidence and TP at regional or broader scales is only possible in general terms due to variation in surface conditions and ground ice content. Trends in TP and GS subsidence more accurately characterize ice‐rich permafrost degradation than trends in ALT.

Experimental and Numerical Investigations on the Impact of Surface Conditions on Self-Piercing Riveted Joint Quality

In this study, experimental and numerical investigations were carried out to achieve a comprehensive understanding of the impact of surface conditions on self-piercing riveting (SPR) joint quality. Oil lubrication and sandpaper grinding were employed in experimental tests to change surface conditions at rivet/top sheet, top/bottom sheets and bottom sheet/die interfaces. A finite element (FE) model for the SPR process was also adopted to numerically assess the impact of surface conditions. Variations in surface conditions were modelled by changing friction coefficients at contact interfaces. The results revealed that the friction coefficient between the rivet and top sheet (μ1) imposed significant influences on the interlock (I1) by affecting the deformation of the rivet shank and top sheet. The friction coefficient between the rivet and bottom sheet (μ2) showed a lower influence on the joint quality because of a smaller contact area and shorter interaction time. The friction coefficient between the top and bottom sheets (μ3) led to opposite changing trends of remaining bottom sheet thickness at the joint centre (tc) and under the rivet tip (ttip). The friction coefficient between the bottom sheet and die (μ4) demonstrated crucial influences on the remaining bottom sheet at the joint centre. The riveting force was significantly influenced throughout the whole riveting process by the μ1, but only affected at the end of the joining process by the other three friction coefficients.

Snow process monitoring using time-lapse structure-from-motion photogrammetry with a single camera

Snow-surface processes in high-mountain snow-covered regions can be both complicated and highly variable. It remains a challenge to monitor snow-surface processes due to its tough environment. In this study, a novel One-camera Time-lapse Structure-from-Motion photogrammetry system (O-T-SfM), which is achieved by mounted a camera on a slider to take seven images from different viewing angles, was build-up to monitor snow surface automatically. The novel O-T-SfM was installed next to the August-one ice cap in the Qilian mountains, northwestern China to monitor snow-surface processes by taking oblique digital photographs every three hours from 8:00 to 17:00 from August 24, 2019, to September 7, 2020. Agisoft Photoscan was used to process the images and to derive point clouds and plot 1.5 × 1.5 m scale digital elevation models (DEMs). The O-T-SfM measurements is highly consistent with three different methods such as manual measurement, checkpoints, and manual photogrammetry, which indicates that O-T-SfM photogrammetry can achieve centimeter-scale precision. We found that O-T-SfM photogrammetry was generally successful at monitoring snow surfaces and the performance varies with the variation of surface condition in different season. Best performance was reached with snow-free conditions and O-T-SfM has a good performance when snow bedforms were abundant from October to March. It is hard for O-T-SfM to capture the snow melting processes July to September and the smooth fresh snowfalls from April to June. Alignment achievement was greatest in the morning and declined throughout the day. We found that our digital DEMs could also be used to assess the settling characteristics of the snowpack (snow accumulation and ablation, snow-surface roughness). Our results suggest that remote O-T-SfM photogrammetry can be successfully used to monitor the snow processes.

Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model

Abstract. The contribution of soil heterotrophic respiration to the boreal–Arctic carbon (CO2) cycle and its potential feedback to climate change remains poorly quantified. We developed a remote-sensing-driven permafrost carbon model at intermediate scale (∼1 km) to investigate how environmental factors affect the magnitude and seasonality of soil heterotrophic respiration in Alaska. The permafrost carbon model simulates snow and soil thermal dynamics and accounts for vertical soil carbon transport and decomposition at depths up to 3 m below the surface. Model outputs include soil temperature profiles and carbon fluxes at 1 km resolution spanning the recent satellite era (2001–2017) across Alaska. Comparisons with eddy covariance tower measurements show that the model captures the seasonality of carbon fluxes, with favorable accuracy in simulating net ecosystem CO2 exchange (NEE) for both tundra (R>0.8, root mean square error (RMSE – 0.34 g C m−2 d−1), and boreal forest (R>0.73; RMSE – 0.51 g C m−2 d−1). Benchmark assessments using two regional in situ data sets indicate that the model captures the complex influence of snow insulation on soil temperature and the temperature sensitivity of cold-season soil heterotrophic respiration. Across Alaska, we find that seasonal snow cover imposes strong controls on the contribution from different soil depths to total soil heterotrophic respiration. Earlier snowmelt in spring promotes deeper soil warming and enhances the contribution of deeper soils to total soil heterotrophic respiration during the later growing season, thereby reducing net ecosystem carbon uptake. Early cold-season soil heterotrophic respiration is closely linked to the number of snow-free days after the land surface freezes (R=-0.48, p<0.1), i.e., the delay in snow onset relative to surface freeze onset. Recent trends toward earlier autumn snow onset in northern Alaska promote a longer zero-curtain period and enhanced cold-season respiration. In contrast, southwestern Alaska shows a strong reduction in the number of snow-free days after land surface freeze onset, leading to earlier soil freezing and a large reduction in cold-season soil heterotrophic respiration. Our results also show nonnegligible influences of subgrid variability in surface conditions on the model-simulated CO2 seasonal cycle, especially during the early cold season at 10 km scale. Our results demonstrate the critical role of snow cover affecting the seasonality of soil temperature and respiration and highlight the challenges of incorporating these complex processes into future projections of the boreal–Arctic carbon cycle.

Emergent Simplicity of Continental Evapotranspiration

AbstractEvapotranspiration (ET) is challenging to model because it depends on heterogeneous land surface features—such as soil moisture, land cover type, and plant physiology—resulting in rising model complexity and substantial disagreement between models. We show that the evaporative fraction (ET as a proportion of available energy at the surface) can be estimated accurately across a broad range of conditions using a simple equation with no free parameters and no land surface information; only near‐surface air temperature and specific humidity observations are required. The equation performs well when compared to eddy covariance measurements at 76 inland continental sites, with prediction errors comparable to errors in the eddy covariance measurements themselves, despite substantial variability in surface conditions across sites. This reveals an emergent simplicity to continental ET that has not been previously recognized, in which land‐atmosphere coupling efficiently embeds land surface information in the near‐surface atmospheric state on daily to monthly time scales.

High spatial density ground thermal measurements in a warming permafrost region, Beiluhe Basin, Qinghai-Tibet Plateau

Air, ground surface, and permafrost surface temperatures are important components of the permafrost thermal regime. However, ground temperatures from one or two boreholes are commonly considered representative of site conditions in permafrost studies despite significant variations in local surface conditions. This makes the evaluation of site-scale temperature variations important for improving the accuracy of permafrost modelling efforts. In this study we analyzed the variability in near-surface ground temperatures in a warming permafrost region using high spatial density borehole measurements to capture variations in surface conditions. Ground temperatures were collected from 72 boreholes drilled to 5 m depth at 8 sites in Beiluhe Basin, Qinghai-Tibet Plateau. Six sites straddled an alpine meadow ecotone between well- and sparsely-vegetated ground, and two sites were located on slopes with opposing aspects. Air temperatures at the 8 sites were similar with annual mean values ranging from −2.6 to −3.0 °C in 2016–18. In contrast, annual mean surface temperatures exhibited greater variation between sites, so that surface offsets were also variable. Ground surface temperatures were highest at a sloping sunny site, and lowest at a north-facing shady site. The results indicated that surface temperatures were strongly controlled by slope aspect. In contrast, the expected effect of vegetation cover shading was not distinguishable because of variations in soil moisture content between sites. Deeper temperatures at the permafrost surface and at 5 m depth exhibited a similar trend among sites except in an unusual warm transitional area where eolian erosion disturbed the surface vegetation cover. The detailed ground temperature records characterizing within- and between-site variations could be used in future to support the calibration and validation of numerical models of permafrost distribution.

Making time-lapse seismic work in a complex desert environment for CO2 EOR monitoring — Design and acquisition

Onshore seismic monitoring for CO2 injection in carbonate reservoirs in the Middle East is a major challenge for many reasons. The 4D signal is generally much smaller than that of clastic or chalk reservoirs due to the high bulk moduli of the rocks and the relatively small fluid effect. In addition, seismic data are characterized by low signal-to-noise ratio (S/N) due to poor signal penetration below high-contrast near-surface layers, poorly consolidated materials at the surface, conversion of source energy into surface waves and trapped modes, and scattering from near-surface complexities. Seasonal variations in surface conditions combined with low S/N make acquisition and processing of 4D seismic data some of the greatest challenges in geophysics today. We show results from feasibility and field pilot seismic programs for enhanced oil recovery (EOR) monitoring that resulted in successful imaging of CO2 injection in such a challenging onshore environment and achieved 4D metrics comparable with offshore seismic monitoring. The final acquisition choice included a hybrid surface source/buried receiver system with point sensors and sources based on cost and effectiveness of the various technologies tested. Acquisition included continuous monitoring with a full 3D survey acquired once every four weeks for a period of several years. Burying sparser receivers with dense source coverage minimized 4D noise to acceptable levels (< 5% normalized root mean square) and allowed fluid saturation changes from CO2 EOR to be observed.

Stacked convolutional auto-encoders for surface recognition based on 3d point cloud data

This paper addresses the problem of feature extraction for 3d point cloud data using a deep-structured auto-encoder. As one of the most focused research areas in human---robot interaction (HRI), the vision-based object recognition is very important. To recognize object using the most common geometry feature, surface condition that can be obtained from 3d point cloud data could decrease the error during the HRI. In this research, the surface normal vectors are used to convert 3D point cloud data to a surface-condition-feature map, and a sub-route stacked convolution auto-encoder (sCAE) is designed to classify the difference between the surfaces. The result of the trained filters and the classification of sCAE shows the surface-condition-feature and the specified sCAE are very effective in the variation of surface condition.

Exceptional ocean surface conditions on the SE Greenland shelf during the Medieval Climate Anomaly

Diatom inferred 2900 year long records of August sea surface temperature (aSST) and April sea ice concentration (aSIC) are generated from a marine sediment core from the SE Greenland shelf with a special focus on the interval ca. 870–1910 Common Era (C.E.) reconstructed in subdecadal temporal resolution. The Medieval Climate Anomaly (MCA) between 1000 and 1200 C.E. represents the warmest ocean surface conditions of the SE Greenland shelf over the late Holocene (880 B.C.E.(before the Common Era) to 1910 C.E.). It was characterized by abrupt, decadal to multidecadal changes, such as an abrupt warming of ~2.4°C in 55 years around 1000 C.E. Temperature changes of these magnitudes are rare on the North Atlantic proxy data. Compared to regional air temperature reconstructions, our results indicate a lag of about 50 years in ocean surface warming either due to increased freshwater discharge from the Greenland ice sheet or intensified sea ice export from the Arctic as a response to atmospheric warming at the beginning of the MCA. A cool phase, from 1200–1890 C.E., associated with the Little Ice Age, ends with the rapid warming of aSST and diminished aSIC in the early twentieth century. The results show that the periods of warm aSST and aSIC minima are coupled with solar minima suggesting that solar forcing possibly amplified by atmospheric forcing have been behind the variability of surface conditions on the SE Greenland over the last millennium. The results indicate that the SE Greenland shelf is a climatologically sensitive area where extremely rapid changes are possible and highlights the importance of the area under the present warming conditions.

Gate-induced transition between metal-type and thermally activated transport in self-catalyzed MBE-grown InAs nanowires

Electronic transport properties of InAs nanowires are studied systematically. The nanowires are grown by molecular beam epitaxy on a SiOx-covered GaAs wafer, without using foreign catalyst particles. Room-temperature measurements revealed relatively high resistivity and low carrier concentration values, which correlate with the low background doping obtained by our growth method. Transport parameters, such as resistivity, mobility, and carrier concentration, show a relatively large spread that is attributed to variations in surface conditions. For some nanowires the conductivity has a metal-type dependence on temperature, i.e. decreasing with decreasing temperature, while other nanowires show the opposite temperature behavior, i.e. temperature-activated characteristics. An applied gate voltage in a field-effect transistor configuration can switch between the two types of behavior. The effect is explained by the presence of barriers formed by potential fluctuations.

Examination of Errors in Near-Surface Temperature and Wind from WRF Numerical Simulations in Regions of Complex Terrain

Abstract The performance of an advanced research version of the Weather Research and Forecasting Model (WRF) in predicting near-surface atmospheric temperature and wind conditions under various terrain and weather regimes is examined. Verification of 2-m temperature and 10-m wind speed and direction against surface Mesonet observations is conducted. Three individual events under strong synoptic forcings (i.e., a frontal system, a low-level jet, and a persistent inversion) are first evaluated. It is found that the WRF model is able to reproduce these weather phenomena reasonably well. Forecasts of near-surface variables in flat terrain generally agree well with observations, but errors also occur, depending on the predictability of the lower-atmospheric boundary layer. In complex terrain, forecasts not only suffer from the model's inability to reproduce accurate atmospheric conditions in the lower atmosphere but also struggle with representative issues due to mismatches between the model and the actual terrain. In addition, surface forecasts at finer resolutions do not always outperform those at coarser resolutions. Increasing the vertical resolution may not help predict the near-surface variables, although it does improve the forecasts of the structure of mesoscale weather phenomena. A statistical analysis is also performed for 120 forecasts during a 1-month period to further investigate forecast error characteristics in complex terrain. Results illustrate that forecast errors in near-surface variables depend strongly on the diurnal variation in surface conditions, especially when synoptic forcing is weak. Under strong synoptic forcing, the diurnal patterns in the errors break down, while the flow-dependent errors are clearly shown.

Thermal history of Mars inferred from orbital geochemistry of volcanic provinces

Reconstruction of the geological history of Mars has been the focus of considerable attention over the past four decades, with important discoveries being made about variations in surface conditions. However, despite a significant increase in the amount of data related to the morphology, mineralogy and chemistry of the martian surface, there is no clear global picture of how magmatism has evolved over time and how these changes relate to the internal workings and thermal evolution of the planet. Here we present geochemical data derived from the Gamma Ray Spectrometer on board NASA's Mars Odyssey spacecraft, focusing on twelve major volcanic provinces of variable age. Our analysis reveals clear trends in composition that are found to be consistent with varying degrees of melting of the martian mantle. There is evidence for thickening of the lithosphere (17-25 km Gyr(-1)) associated with a decrease in mantle potential temperature over time (30-40 K Gyr(-1)). Our inferred thermal history of Mars, unlike that of the Earth, is consistent with simple models of mantle convection.

Process Studies on Laser Welding of Copper with Brilliant Green and Infrared Lasers

Copper materials are classified as difficult to weld with state-of-the-art lasers. High thermal conductivity in combination with low absorption at room temperature require high intensities for reaching a deep penetration welding process. The low absorption also causes high sensitivity to variations in surface conditions. Green laser radiation shows a considerable higher absorption at room temperature. This reduces the threshold intensity for deep penetration welding significantly. The influence of the green wavelength on energy coupling during heat conduction welding and deep penetration welding as well as the influence on the weld shape has been investigated.

Spatio-temporal variations in surface characteristics over the North American Monsoon region

In this paper we summarize the surface characteristics for six locations in western Mexico and southwestern USA (from a subhumid climate in Jalisco, Mexico to the Sonoran Desert climate in Arizona, USA), that lie along a meridional transect within the North American Monsoon (NAM) core region using available MODerate Resolution Imaging Radiometer (MODIS) satellite data and supplementary surface instrumental data for two of these sites in Sonora, Mexico. The climate analysis for each site is carried out for the period 2000–2008, that includes all available MODIS data. A comparison of seasonal and annual variability in surface conditions for the enhanced vegetation index (EVI), albedo and land surface temperature (LST) at each site is presented. With the help of available surface data from field observations, a more detailed analysis of Rayón and Rosario de Tesopaco sites is presented. The qualitative behavior and climate response of three types of vegetation: desert shrub, subtropical shrub, and tropical deciduous forest ecosystems are analyzed under the influence of the NAM summer wet season. The onset of the NAM warm wet season in early summer, is one of the main precursors of generalized EVI growth in all the NAM region. At all the sites, it is observed that the mean daytime LST cools several degrees as the NAM fully develops. During the warm wet season, in the case of open and sparse vegetation regions such as desert shrub and subtropical shrub, albedo values fall slightly during the NAM season, while in closed and dense tropical deciduous forest regions albedo shows a slight increase. Differences in soil reflectivity at these sites are probably responsible for this rather unexpected behavior. Additionally it is found that, desert shrub and subtropical shrub regions in northern latitudes show large LST and small EVI/albedo seasonal variability, whilst tropical deciduous forests in lower latitudes show much larger EVI/albedo and smaller LST seasonal variability. Thus MODIS data proves to be a valuable tool for assessing the dynamics of seasonal and interannual surface characteristics helpful in determining climate patterns.

The Effect of Surface Conditions on Friction by Tip Test

In the present investigation, a tip test based on upsetting and backward extrusion was utilized to characterize the effect of surface roughness of the billet and forming tools, and the type of lubricants on friction. For the test, cylindrical specimens made of aluminum alloys of 6061-O and 2024-O, and single punch and two die sets with different surface topologies, were used with four lubricants such as VG32, VG100, corn oil, and grease. The load levels and tip distances were measured for both materials, and compared with each other to determine shear friction factors at the punch and counter punch interfaces separately, depending on the variation in surface topologies and lubrications using finite element simulations. As a result, a linear relationship among the dimensionless load, tip distance, and shear friction factors at the punch and counter punch interfaces was derived for the experimental conditions investigated. The slope change of this linear relationship from negative to positive clearly depends on the variation in surface conditions at the billet/punch and billet/counter punch interfaces. Also, it was demonstrated that the dimensionless tip distance for the frictionless case can be extrapolated from the experimental data. This value can be used for characterizing the relative effect on friction due to surface conditions at the punch and counter punch, and lubrication quality of the lubricant for the given processing conditions.

Transient power variation in surface conditions in heat conduction for plates

Transient temperature solutions in plates are derived for heating conditions varying as time to an integer power at a surface. The powers include 0, 1, 2 and 3; the last of which is useful for cubic splines. Boundary conditions of the first, second and third kinds are treated at both surfaces with the non-homogeneity at x = 0. As the power increases by one, an additional quasi-steady summation term appears in the analytical solution. Algebraic forms for these summations are derived in a systematic way. Extensive tables are given along with an example.

Corrosion of Steel Bars in Concrete with Various Steel Surface Conditions

Marine concrete structures are prone to deterioration by the corrosion of the internal steel reinforcing bars. This article reports on a study carried out to investigate the corrosion of steel bars and steel-concrete interface in concrete comparing various surface conditions of steel bars, such as mill-scaled (M), polished (P), brown-rusted (BR), black-rusted (BL), and pre-passivated (PP). Other variables were considered as possible ways to improve the steel-concrete interface, including PP, revibration of the concrete after casting, and insertion of steel bars in concrete after casting. The specimens were exposed to an artificially created accelerated marine exposure and tested for the corrosion of steel bars and chloride ingress into concrete at a regular interval. Steel-concrete interfaces were examined by a scanning electron microscope (SEM) to check the nature of the steel-concrete interface with the variation of surface condition and casting method. Results showed that application of a cement paste coat over the steel bar created a remarkably dense steel-concrete interface compared to the other types investigated, and therefore significantly improved the chloride threshold level. M bars produced the most corrosion compared to the other bars investigated. Revibration causes a slight improvement of mechanical properties of concrete; however, it causes relatively earlier corrosion over the steel bars due to the formation of micro-crevices at the steel-concrete interface.

Measurement and data analysis methods for field‐scale wind erosion studies and model validation

AbstractAccurate and reliable methods of measuring windblown sediment are needed to confirm, validate, and improve erosion models, assess the intensity of aeolian processes and related damage, determine the source of pollutants, and for other applications. This paper outlines important principles to consider in conducting field‐scale wind erosion studies and proposes strategies of field data collection for use in model validation and development. Detailed discussions include consideration of field characteristics, sediment sampling, and meteorological stations. The field shape used in field‐scale wind erosion research is generally a matter of preference and in many studies may not have practical significance. Maintaining a clear non‐erodible boundary is necessary to accurately determine erosion fetch distance. A field length of about 300 m may be needed in many situations to approach transport capacity for saltation flux in bare agricultural fields. Field surface conditions affect the wind profile and other processes such as sediment emission, transport, and deposition and soil erodibility. Knowledge of the temporal variation in surface conditions is necessary to understand aeolian processes. Temporal soil properties that impact aeolian processes include surface roughness, dry aggregate size distribution, dry aggregate stability, and crust characteristics. Use of a portable 2 tall anemometer tower should be considered to quantify variability of friction velocity and aerodynamic roughness caused by surface conditions in field‐scale studies. The types of samplers used for sampling aeolian sediment will vary depending upon the type of sediment to be measured. The Big Spring Number Eight (BSNE) and Modified Wilson and Cooke (MWAC) samplers appear to be the most popular for field studies of saltation. Suspension flux may be measured with commercially available instruments after modifications are made to ensure isokinetic conditions at high wind speeds. Meteorological measurements should include wind speed and direction, air temperature, solar radiation, relative humidity, rain amount, soil temperature and moisture. Careful consideration of the climatic, sediment, and soil surface characteristics observed in future field‐scale wind erosion studies will ensure maximum use of the data collected. Copyright © 2003 John Wiley & Sons, Ltd.

Estimating forest structure in wetlands using multitemporal SAR

Data from 202 forest plots on the Roanoke River floodplain, North Carolina were used to assess the capabilities of multitemporal radar imagery for estimating biophysical characteristics of forested wetlands. The research was designed to determine the potential for using widely available data from the current set of satellite-borne synthetic aperture radar (SAR) sensors to study forests over broad geographic areas and complex environmental gradients. The SAR data set included 11 Radarsat scenes, 2 ERS-1 images, and 1 JERS-1 scene. Empirical analyses were stratified by flood status such that sites were compared only if they exhibited common flooding characteristics. In general, the results indicate that forest properties are more accurately estimated using data from flooded areas, probably because variations in surface conditions are minimized where there is a continuous surface of standing water. Estimations yielded root mean square errors (RMSEs) for validation data around 10 m 2/ha for basal area (BA), and less than 3 m for canopy height. The r 2 values generally exceeded .65 for BA, with the best predictions coming from sample sites for which both nonflooded and flooded SAR scenes were available. The addition of early spring normalized difference vegetation index (NDVI) values from Landsat Thematic Mapper (Landsat TM) improved model predictions for BA in forests where BA levels were <55 m 2/ha. Further analyses indicated a very limited sensitivity of the individual SAR scenes to differences in forest composition, although soil properties in nonflooded areas exerted a weak but nevertheless important influence on backscatter.