Engineering topics

Choudhury, Bhaskar J.

Publications and source records attributed to Choudhury, Bhaskar J..

At least 19 records

NASA NTRS2011

L Band Brightness Temperature Observations Over a Corn Canopy During the Entire Growth Cycle

During a field campaign covering the 2002 corn growing season, a dual polarized tower mounted L-band (1.4 GHz) radiometer (LRAD) provided brightness temperature (T(sub B)) measurements at preset intervals, incidence and azimuth angles. These radiometer measurements were supported by an extensive characterization of land surface variables including soil moisture, soil temperature, vegetation biomass, and surface roughness. During the period from May 22, 2002 to August 30, 2002 a range of vegetation water content (W) of 0.0 to 4.3 kg/square m, ten days of radiometer and ground measurements were available. Using this data set, the effects of corn vegetation on surface emissions are investigated by means of a semi-empirical radiative transfer model. Additionally, the impact of roughness on the surface emission is quantified using T(sub B) measurements over bare soil conditions. Subsequently, the estimated roughness parameters, ground measurements and horizontally (H)-polarized T(sub B) are employed to invert the H-polarized transmissivity (gamma-h) for the monitored corn growing season.

Joseph, Alicia T.↗

NASA NTRS2010

Evaluating the Impact of Vegetation Cover and Atmospheric Characteristics on the Estimation of Snow Water Equivalent from Spaceborne Microwave Radiometry

A radiative transfer model for estimating snow water equivalent (SWE, mm) from satellite-observed brightness temperature (K) at 19 and 37 GHz (respectively, T(sub B(sub, sat,19)) and T(sub B(sub, sat,37)) over partially forested area is presented, as an extension of a previously published model, by considering scattering of radiation within the canopy. For the specific case of dense vegetation covering fractional area f, the model can be written as, SWE = alpha{ A. delta (T(sub B(sub, sat)) + B - C. f}/(l f), where delta T(sub B(sub, sat)), is the difference of T(sub B(sub, sat,19)) and T(sub B(sub, sat,37)), alpha(mm/K) is the slope of SWE vs. brightness temperature difference at 19 and 37 GHz that would be obtained by ignoring the presence of atmosphere, delta(T(sub B)sub g)), for a homogeneous snow cover (which varies with grain size). The parameters A, B, and C, are determined primarily by atmospheric characteristics, and for a likely range of atmospheric conditions appear to be in the range of, respectively, 1.15-1.63, 0.69-2.84 K and 0.59-2.39 K. Ignoring atmospheric correction would introduce bias towards underestimation of SWE (and also, snow cover area and snow depth). Increasing cloud liquid water path (L) has the effect of increasing A, and ignoring this variation of A with L would have the impact of biasing the estimate of SWE (and snow extent). Such biasing is further exacerbated with increasing f, because of the appearance of term (l-f) in the denominator. The impact of ignoring the intercept parameters (B and C) would be noticeable at low values of SWE (appearing as a bias towards underestimation of SWE), which has been determined to be about 6 mm for average environmental conditions. The uncertainty in estimating SWE due to variations in the atmospheric characteristics is likely to be less than 15%, but could be up to 25% for non-vegetated snow-covered areas. Better estimates of SWE (and snow extent) would be obtained by adjusting the parameters of the above model to regional differences in the atmospheric characteristics. The biases in determining SWE arising due to variations in atmospheric conditions and due to changes in fractional forest cover are not independent, since they interact as {A/(l-f)}. The present calculations also show that improvement in determining snow cover area from the microwave data is likely to occur when these data are corrected for atmospheric effects, as demonstrated by a specific case study.

Choudhury, Bhaskar J.↗

NASA NTRS2003

Estimation of Transpiration and Water Use Efficiency Using Satellite and Field Observations

Structure and function of terrestrial plant communities bring about intimate relations between water, energy, and carbon exchange between land surface and atmosphere. Total evaporation, which is the sum of transpiration, soil evaporation and evaporation of intercepted water, couples water and energy balance equations. The rate of transpiration, which is the major fraction of total evaporation over most of the terrestrial land surface, is linked to the rate of carbon accumulation because functioning of stomata is optimized by both of these processes. Thus, quantifying the spatial and temporal variations of the transpiration efficiency (which is defined as the ratio of the rate of carbon accumulation and transpiration), and water use efficiency (defined as the ratio of the rate of carbon accumulation and total evaporation), and evaluation of modeling results against observations, are of significant importance in developing a better understanding of land surface processes. An approach has been developed for quantifying spatial and temporal variations of transpiration, and water-use efficiency based on biophysical process-based models, satellite and field observations. Calculations have been done using concurrent meteorological data derived from satellite observations and four dimensional data assimilation for four consecutive years (1987-1990) over an agricultural area in the Northern Great Plains of the US, and compared with field observations within and outside the study area. The paper provides substantive new information about interannual variation, particularly the effect of drought, on the efficiency values at a regional scale.

Choudhury, Bhaskar J.↗

NASA NTRS2002

Estimating Net Primary Productivity Using Satellite and Ancillary Data

The net primary productivity (C) or the annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of gross photosynthesis (A(sub g)) and respiration (R) per unit ground area. Available field observations show that R is a large and variable fraction of A(sub g), although it is generally recognized that there are considerable difficulties in determining these fluxes, and thus pose challenge in assessing the accuracy. Further uncertainties arise in extrapolating field measurements (which are acquired over a hectare or so area) to regional scale. Here, an approach is presented for determining these fluxes using satellite and ancillary data to be representative of regional scale and allow assessment of interannual variation. A, has been expressed as the product of radiation use efficiency for gross photosynthesis by an unstressed canopy and intercepted photosynthetically active radiation, which is then adjusted for stresses due to soil water shortage and temperature away from optimum. R has been calculated as the sum of growth and maintenance components (respectively, R(sub g) and R(sub m)).The R(sub m) has been determined from nitrogen content of plant tissue per unit ground area, while R(sub g) has been obtained as a fraction of the difference of A(sub g) and R(sub m). Results for five consecutive years (1986-1990) are presented for the Amazon-Tocontins, Mississippi, and Ob River basins.

Choudhury, Bhaskar J.↗

NASA NTRS2001

Implementing a Nitrogen-Based Model for Autotrophic Respiration Using Satellite and Field Observations

The rate of carbon accumulation by terrestrial plant communities in a process-level, mechanistic modeling is the difference of the rate of gross photosynthesis by a canopy (A(sub g)) and autotrophic respiration (R) of the stand. Observations for different biomes often show that R to be a large and variable fraction of A(sub g), ca. 35% to 75%, although other studies suggest the ratio of R and A(sub g) to be less variable. Here, R has been calculated according to the two compartment model as being the sum of maintenance and growth components. The maintenance respiration of foliage and living fine roots for different biomes has been determined objectively from observed nitrogen content of these organs. The sapwood maintenance respiration is based on pipe theory, and checked against an independently derived equation considering sapwood biomass and its maintenance coefficient. The growth respiration has been calculated from the difference of A(sub g) and maintenance respiration. The A(sub g) is obtained as the product of biome-specific radiation use efficiency for gross photosynthesis under unstressed conditions and intercepted photosynthetically active radiation, and adjusted for stress. Calculations have been done using satellite and ground observations for 36 consecutive months (1987-1989) over large contiguous areas (ca. 10(exp 5) sq km) of boreal forests, crop land, temperate deciduous forest, temperate grassland, tropical deciduous forest, tropical evergreen forest, tropical savanna, and tundra. The ratio of annual respiration and gross photosynthesis, (R/A(sub g)), is found to be 0.5-0.6 for temperate and cold adopted biome areas, but somewhat higher for tropical biome areas (0.6-0.7). Interannual variation of the fluxes is found to be generally less than 15%. Calculated fluxes are compared with observations and several previous estimates. Results of sensitivity analysis are presented for uncertainties in parameterization and input data. It is found that uncertainty in determining maintenance respiration for tropical biomes is such that R/A(sub g) for these biomes could be similar to that for temperate biomes.

Choudhury, Bhaskar J.↗

NASA NTRS1999

Seasonal and Interannual Variations of Evaporation and their Relations with Precipitation, Net Radiation, and Net Carbon Accumulation for the Gediz Basin Area

A model combining the rate of carbon assimilation with water and energy balance equations has been run using satellite and ancillary data for a period of 60 months (January 1986 to December 1990). Calculations for the Gediz basin area give mean annual evaporation as 395 mm, which is composed of 45% transpiration, 42% soil evaporation and 13% interception. The coefficient of interannual variation of evaporation is found to be 6%, while that for precipitation and net radiation are, respectively, 16% and 2%, illustrating that net radiation has an important effect in modulating interannual variation of evaporation. The mean annual water use efficiency (i.e., the ratio of net carbon accumulation and total evaporation) is ca. 1 g/sq m/mm, and has a coefficient of interannual variation of 5%. A comparison of the mean water use efficiency with field observations suggests that evaporation over the area is utilized well for biomass production. The reference crop evaporation for irrigated areas has annual mean and coefficient of variation as, respectively, 1176 mm and 3%. The total evaporation during three summer months of peak evaporation (June-August) is estimated to be about 575 mm for irrigated crops like maize and cotton. Seasonal variations of the fluxes are presented.

Choudhury, Bhaskar J.↗

NASA NTRS1999

Further Evaluation of an Emperical Equation for Annual Total Evaporation

An empirical equation for annual total evaporation based on annual precipitation and net radiation was found to provide evaporation within 10% of the observed values at seven locations within temperate and tropical regions, but it overestimated evaporation by 90% at one location within the tundra region. A synthesis of observations at two other locations within the tundra region gives overestimates of about 65%. A general analysis of observed precipitation, net radiation, and runoff within the tundra region shows that the empirical equation is generally biased to overestimate annual evaporation within the tundra region. A theoretical analysis is being done to understand the reason behind this bias.

Choudhury, Bhaskar J.↗

NASA NTRS1997

Global Pattern of Potential Evaporation Calculated from the Penman-Monteith Equation Using Satellite and Assimilated Data

Potential evaporation (E(0)) has been found to be useful in many practical applications and in research for setting a reference level for actual evaporation. All previous estimates of regional or global E(0) are based upon empirical formulae using climatologic meteorologic measurements at isolated stations (i.e., point data). However, the Penman-Monteith equation provides a physically based approach for computing E(0), and by comparing 20 different methods of estimating E(0), Jensen et al. (1990) showed that the Penman-Monteith equation provides the most accurate estimate of monthly E(0) from well-watered grass or alfalfa. In the present study, monthly total E(0) for 24 months (January 1987 to December 1988) was calculated from the Penman-Monteith equation, with prescribed albedo of 0.23 and surface resistance of 70 s/m, which are considered to be representative of actively growing well-watered grass covering the ground. These calculations have been done using spatially representative data derived from satellite observations and data assimilation results. Satellite observations were used to obtain solar radiation, fractional cloud cover, air temperature, and vapor pressure, while four-dimensional data assimilation results were used to calculate the aerodynamic resistance. Meteorologic data derived from satellite observations were compared with the surface measurements to provide a measure of accuracy. The accuracy of the calculated E(0) values was assessed by comparing with lysimeter observations for evaporation from well-watered grass at 35 widely distributed locations, while recognizing that the period of present calculations was not concurrent with the lysimeter measurements and the spatial scales of these measurements and calculations are vastly different. These comparisons suggest that the error in the calculated E(0) values may not be exceeded, on average, 20% for any month or location, but are more likely to be about 15%. These uncertainties are difficult to quantify for mountainous areas or locations close to extensive water bodies. The difference between the calculated and observed E(0) is about 5% when all month and locations were considered. Errors are expected to be less than 15% for averages of E(0) over large areas or several months. Further comparisons with lysimeter observations could provide a better appraisal of the calculated values. Global pattern of E(0) was presented, together with zonal average values.

Choudhury, Bhaskar J.↗

NASA NTRS1997

The Effects of Laterite and Associated Terrain Components on PBMR Response in HAPEX-Sahel

Terrain characteristics such as roughness and vegetation have been shown to significantly affect the interpretation of microwave brightness temperatures (T(B)s) for mapping soil moisture. This study, a part of the 1992 HAPEX-Sahel experiment (Hydrologic Atmospheric Pilot Experiment in the Sahel), aimed to determine the effects of laterite and associated terrain components (i.e. vegetation, soil, and exposed water bodies) on the T(B) response of the Pushbroom Microwave Radiometer (PBMR, L-band, 21 cm wavelength), using the NS001 Thematic Mapper Simulator data as a surrogate for ground data. Coincident PBMR and NS001 data acquired from the high altitude (about 1500 m) long transect flights were processed to obtain TBs and radiances, respectively. The transects covered a range of moisture conditions. For this preliminary evaluation, no atmospheric corrections were applied, and the data sets were aligned by matching the acquisition times of the data records. NS001 pixels (about 4 m) were averaged to approximate the resolution of the PBMR (about 450 m), before their flight line data were compared. The laterite plateaux were found to have a surprisingly strong effect on the PBMR T(B) response. T(B) variations along the flight line could largely be explained by a combination of density and dielectric properties of laterite. The effect of surface moisture was distinguishable from the laterite effect, with the distinction apparently related to the occurrence of ephemeral pools of water after rainfall. Model simulated T(B)s agreed reasonably well with the observed T(B)s.

Teng, William L.↗

NASA NTRS1994

On the relation between SMMR 37-GHz polarization difference and the rainfall over Africa and Australia

A major difficulty in interpreting coarse resolution satellite data in terms of land surface characteristics is unavailability of spatially and temporally representative ground observations. Under certain conditions rainfall has been found to provide a proxy measure for surface characteristics, and thus a relation between satellite observations and rainfall might provide an indirect approach for relating satellite data to these characteristics. Relationship between rainfall over Africa and Australia and 7-year average (1979-1985) polarization difference (PD) at 37 GHz from scanning multichannel microwave radiometer (SMMR) on board the Nimbus-7 satellite is studied in this paper. Quantitative methods have been used to screen (accept or reject) PD data considering antenna pattern, geolocation uncertainty, water contamination, surface roughness, and adverse effect of drought on the relation between rainfall and surface characteristics. The rainfall data used in the present analysis are climatologic averages and also 1979-1985 averages, and no screening has been applied to this data. The PD data has been screened considering only the location of rainfall stations, without any regard to rainfall amounts. The present analysis confirms a non-linear relation between rainfall and PD published previously.

Choudhury, Bhaskar J.↗

NASA NTRS1992

Multispectral satellite observations for arid land studies

Multispectral satellite data when properly calibrated and standardized can be used synergistically for a quantitative analysis of processes and surface characteristics, and for quantifying land surface change. Relationships among multispectral satellite data (visible reflectance, surface temperature and polarization difference of microwave emission at 37 GHz frequency) have been used to develop hypotheses concerning the relative sensitivity of these data to varied land surface characteristics, which needs to be verified by field observations. Radiative transfer models have also been developed to understand these multispectral data. Interannual variations of visible reflectance and polarization difference for the period 1982-1986 over the Sahel and the Sudan zones of Africa show a lagged response with respect to the rainfall deficit during recovery from drought, which needs to be understood in terms of biophysical parameters.

Choudhury, Bhaskar J.↗

NASA NTRS1992

Remote sensing of solar radiation absorbed and reflected by vegetated land surfaces

1D and 3D radiative-transfer models have been used to investigate the problem of remotely sensed determination of vegetated land surface-absorbed and reflected solar radiation. Calculations were conducted for various illumination conditions to determine surface albedo, soil- and canopy-absorbed photosynthetically active and nonactive radiation, and normalized difference vegetation index. Simple predictive models are developed on the basis of the relationships among these parameters.

Myneni, Ranga B.↗

NASA NTRS1991

Multispectral satellite data in the context of land surface heat balance

Multispectral satellite data are demonstrated to be an important potential contributor to the understanding and completeness of heat balance analysis. Satellite observations are presented, including visible, near-IR, IR, and microwave bands, which estimate surface characteristics and surface fluctuations. The relationship of the interannual variations of the satellite data and the land surface changes is discussed. It is shown that spatially representative values of global fluxes and parameters from multispectral data can consistently enhance the results of heat balance analysis. Daily net radiation can be estimated with a 10 percent error, while the error for albedo would be higher. Computations for all heat fluxes except the latent heat flux are shown. Soil moisture and surface temperature estimates can be derived from microwave and IR observations, respectively. Spectral reflectances in the visible and near-IR bands are suggested as important heat-balance indices for future consideration.

Choudhury, Bhaskar J.↗

NASA NTRS1991

A three dimensional radiative transfer method for optical remote sensing of vegetated land surfaces

In the application of remote sensing at optical wavelengths to vegetated surfaces from satellite borne high resolution instruments, an understanding of the various physical mechanisms that contribute to the measured signal is important. A numerical method of solving the radiative transfer equation in three dimensions is reported. The reliability of coding and accuracy of the algorithm are evaluated by benchmarching. Parametrization of the methods and results of a simulation are presented. The method is tested with experimental data of canopy bidirectional reflectance factors. The effect of spatial heterogeneity on the relationship between the simple ratio and normalized vrs absorbed Photosynthetically Active Radiation (PAR) is discussed.

Asrar, Ghassem↗

NASA NTRS1991

Synergistic use of multispectral satellite data for monitoring land surface change

Observations by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites were used to compute visible and near infrared reflectances and surface temperature, while passive microwave observations at 37 GHz frequency by the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) on board, respectively, the Nimbus-7 and DMSP-F8 satellites were used to compute polarization difference. These observations were analyzed along transects from rainforest to desert over northern Africa for the period 1979-1987, which included an unprecedented drought during 1984 over the Sahel zone. Model simulations were made to understand the interrelationship among multispectral data.

Choudhury, Bhaskar J.↗

NASA NTRS1989

Monitoring global land surface using Nimbus-7 37 GHz data - Theory and examples

Simplified radiative transfer models for 37 GHz brightness temperatures are developed and applied to observations taken with the Nimbus-7 scanning multichannel microwave radiometer. It is found that, as the vegetation density increases, polarization difference decreases. The polarization difference also decreases with increasing surface roughness. Empirical relations are established between the satellite observations and annual rainfall over Africa and Australia, primary productivity, and actual evaporation. Color-coded maps of primary productivity and evaporation are presented.

Choudhury, Bhaskar J.↗

NASA NTRS1989

A one- and two-layer model for estimating evapotranspiration with remotely sensed surface temperature and ground-based meteorological data over partial canopy cover

Surface-air temperature differences are commonly used in a bulk resistance equation for estimating sensible heat flux (H), which is inserted in the one-dimensional energy balance equation to solve for the latent heat flux (LE) as a residual. Serious discrepancies between estimated and measured LE have been observed for partial-canopy-cover conditions, which are mainly attributed to inappropriate estimates of H. To improve the estimates of H over sparse canopies, one- and two-layer resistance models that account for some of the factors causing poor agreement are developed. The utility of the two models is tested with remotely sensed and micrometeorological data for a furrowed cotton field with 20 percent cover and a dry soil surface. It is found that the one-layer model performs better than the two-layer model when a theoretical bluff-body correction for heat transfer is used instead of an empirical adjustment; otherwise, the two-layer model is better.

Kustas, William P.↗

NASA NTRS1988

Estimating soil wetness using satellite data

Improved estimates of soil wetness were obtained using observations from both the NIMBUS-7 Scanning Multichannel Microwave Radiometer (SMMR) and the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR). SMMR 66 GHz frequency, horizontal polarization, brightness temperature T(BH) was first correlated with soil wetness, as computed using an Antecedent Precipitation Index (API) model, for a number of SMMR ground resolution areas involving a fairly wide range of vegetation densities. The API generally accounted for more than 70 percent of the observed temporal variability in T(BH), with linear correlations being significant at the 1 percent level. The regression slope of T(BH) versus API correlated well, at the 1 percent level, with a vegetation index derived from AVHRR visible and near-infrared observations. The regression intercept was found to correlate less satisfactorily, but was significant at the 5 percent level. These linear regression results were used to develop a diagnostic model for soil wetness using SMMR and AVHRR data only.

Choudhury, Bhaskar J.↗