Microwave remote sensing of soil moisture, volume 1

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone

Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms, volume 2

Agricultural crop classification models using two or more spectral regions (visible through microwave) were developed and tested and biomass was estimated by including microwave with visible and infrared data. The study was conducted at Guymon, Oklahoma and Dalhart, Texas utilizing aircraft multispectral data and ground truth soil moisture and biomass information. Results indicate that inclusion of C, L, and P band active microwave data from look angles greater than 35 deg from nadir with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels. In addition, two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass

Multifrequency remote sensing of soil moisture

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture

Development of visible/infrared/microwave agriculture classification and biomass estimation algorithms

Agricultural crop classification models using two or more spectral regions (visible through microwave) are considered in an effort to estimate biomass at Guymon, Oklahoma Dalhart, Texas. Both grounds truth and aerial data were used. Results indicate that inclusion of C, L, and P band active microwave data, from look angles greater than 35 deg from nadir, with visible and infrared data improve crop discrimination and biomass estimates compared to results using only visible and infrared data. The microwave frequencies were sensitive to different biomass levels. The K and C band were sensitive to differences at low biomass levels, while P band was sensitive to differences at high biomass levels. Two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass. It is implied that inclusion of active microwave sensors with visible and infrared sensors on future satellites could aid in crop discrimination and biomass estimation

Wind tunnel turning vanes of modern design

Rehabilitation of the Altitude Wind Tunnel includes the need for new corner turning vanes to match its upgraded performance. The design and experimental performance results from a 0.1-full scale model of the highest speed corner (M = 0.35) are presented and discussed along with some two dimensional inviscid analyses of two vaned corners. With a vane designed by an inverse two dimensional technique, the overall corner loss was about 12% of the inlet dynamic pressure of which about 4% was caused by vane skin friction. Comparable values with a conventionally designed circular arc vane were about 14% overall with about 7% due to skin friction

Measurement of soil moisture trends with airborne scatterometers

In an effort to investigate aircraft multisensor responses to soil moisture and vegetation in agricultural fields, an intensive ground sampling program was conducted in Guymon, Oklahoma and Dalhart, Texas in conjunction with aircraft data collected for visible/infrared and passive and active microwave systems. Field selections, sampling techniques, data processing, and the aircraft schedule are discussed for both sites. Field notes are included along with final (normalized and corrected) data sets

Sentinel surveillance of HIV-1 transmitted drug resistance, acute infection and recent infection.

BackgroundHIV-1 acute infection, recent infection and transmitted drug resistance screening was integrated into voluntary HIV counseling and testing (VCT) services to enhance the existing surveillance program in San Francisco. This study describes newly-diagnosed HIV cases and characterizes correlates associated with infection.Methodology/principal findingsA consecutive sample of persons presenting for HIV VCT at the municipal sexually transmitted infections (STI) clinic from 2004 to 2006 (N = 9,868) were evaluated by standard enzyme-linked immunoassays (EIA). HIV antibody-positive specimens were characterized as recent infections using a less-sensitive EIA. HIV-RNA pooled testing was performed on HIV antibody-negative specimens to identify acute infections. HIV antibody-positive and acute infection specimens were evaluated for drug resistance by sequence analysis. Multivariable logistic regression was performed to evaluate associations. The 380 newly-diagnosed HIV cases included 29 acute infections, 128 recent infections, and 47 drug-resistant cases, with no significant increases or decreases in prevalence over the three years studied. HIV-1 transmitted drug resistance prevalence was 11.0% in 2004, 13.4% in 2005 and 14.9% in 2006 (p = 0.36). Resistance to non-nucleoside reverse transcriptase inhibitors (NNRTI) was the most common pattern detected, present in 28 cases of resistance (59.6%). Among MSM, recent infection was associated with amphetamine use (AOR = 2.67; p<0.001), unprotected anal intercourse (AOR = 2.27; p<0.001), sex with a known HIV-infected partner (AOR = 1.64; p = 0.02), and history of gonorrhea (AOR = 1.62; p = 0.03).ConclusionsNew HIV diagnoses, recent infections, acute infections and transmitted drug resistance prevalence remained stable between 2004 and 2006. Resistance to NNRTI comprised more than half of the drug-resistant cases, a worrisome finding given its role as the backbone of first-line antiretroviral therapy in San Francisco as well as worldwide. The integration of HIV-1 drug resistance, recent infection, and acute infection testing should be considered for existing HIV/STI surveillance and prevention activities, particularly in an era of enhanced efforts for early diagnosis and treatment

Technology and Technical Change in the MIT EPPA Model

Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).Potential technology change has a strong influence on projections of greenhouse gas emissions and costs of control, and computable general equilibrium (CGE) models are a common device for studying these phenomena. Using the MIT Emissions Prediction and Policy Analysis (EPPA) model as an example, two ways of representing technology in these models are discussed: the sector-level description of production possibilities founded on social accounting matrices and elasticity estimates, and sub-models of specific supply or end-use devices based on engineering-process data. A distinction is made between exogenous and endogenous technical change, and it is shown how, because of model structure and the origin of key parameters, such models naturally include shifts in production process that reflect some degree of endogenous technical change. As a result, the introduction of explicit endogenous relations should be approached with caution, to avoid double counting.The CGE model underlying this analysis was supported by the US Department of Energy, Office of Biological and Environmental Research [BER] (DE-FG02-94ER61937), the US Environmental Protection Agency (X-827703-01-0), the Electric Power Research Institute, and by a consortium of industry and foundation sponsor