The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform

Ferran Martín - One of the best experts on this subject based on the ideXlab platform.

M.c. Dobson - One of the best experts on this subject based on the ideXlab platform.

  • sensitivity to soil moisture by active and passive Microwave Sensors
    IEEE Transactions on Geoscience and Remote Sensing, 2000
    Co-Authors: Yanlei Du, F.t. Ulaby, M.c. Dobson
    Abstract:

    The backscatter measured by radar and the emission measured by a radiometer are both very sensitive to the moisture content m/sub /spl upsi// of bare-soil surfaces. Vegetation cover complicates the scattering and emission processes, and it has been presumed that the addition of vegetation masks the soil surface, thereby reducing the radiometric and radar soil-moisture sensitivities. Even though researchers working in the field of Microwave remote sensing of soil moisture are all likely to agree with the preceding two statements, numerous claims and counterclaims have been voiced, primarily at symposia and workshops, espousing the superiority of the radiometric technique over the radar, or vice versa. The discussion is often reduced to disagreements over the answer to the following question "Which of the two sensing techniques is less impacted by vegetation cover?" This paper is an attempt to answer that question. Using realistic radiative-transfer models for the emission and backscatter, calculations were performed for three types of canopies, all at 1.5 GHz. The results lead to two major conclusions. First, the accepted presumption that vegetation cover reduces the soil-moisture sensitivity is not always true. Over certain ranges of the optical depth /spl tau/ of the vegetation canopy and the roughness of the soil surface, vegetation cover can enhance, not reduce, the radar sensitivity to soil moisture. The second conclusion is that under most vegetation and soil-surface conditions, the radiometric and radar soil-moisture sensitivities decrease with increasing /spl tau/, and the rates are approximately the same for both Sensors, suggesting that at least as far as vegetation effects are concerned, neither sensor can claim superiority over the other.

  • Sensitivity to soil moisture by active and passive Microwave Sensors
    IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293), 1999
    Co-Authors: Yang Du, F.t. Ulaby, M.c. Dobson
    Abstract:

    The backscatter measured by a radar and the emission measured by a radiometer are both very sensitive to the moisture content m, of bare-soil surfaces. Vegetation cover complicates the scattering and emission processes, presumably masking the soil surface and reducing soil-moisture sensitivity. Although researchers generally agree with the preceding statement, numerous claims and counterclaims have been voiced, espousing the superiority of the radiometric technique over the radar, or vice versa. The discussion often reduces to disagreements over the answer to the following question "Which of the two sensing techniques is less impacted by vegetation cover?" This paper is an attempt to answer that question. Using realistic radiative transfer models for the emission and backscatter, calculations were performed for three types of canopies, all at 1.5 GHz. The results lead to two major conclusions. First, the presumption that vegetation cover reduces the soil moisture sensitivity, is not always true. Over certain ranges of the optical depth /spl tau/ of the vegetation canopy and the roughness of the soil surface, vegetation cover can enhance, not reduce, the radar sensitivity to soil moisture. The second conclusion is that under most vegetation and soil-surface conditions, the radiometric and radar soil moisture sensitivities decrease with increasing /spl tau/ and the rates are approximately the same for both Sensors, suggesting that, at least as far as vegetation effects are concerned, neither sensor can claim superiority over the other.

Thomas Ohde - One of the best experts on this subject based on the ideXlab platform.

  • Impact of Saharan Dust on Ocean Surface Wind Speed Derived by Microwave Satellite Sensors
    Journal of Infrared Millimeter and Terahertz Waves, 2010
    Co-Authors: Thomas Ohde
    Abstract:

    In the present paper ground truth and remotely sensed datasets were used for the investigation and quantification of the impact of Saharan dust on Microwave propagation, the verification of theoretical results, and the validation of wind speeds determined by satellite Microwave Sensors. The influence of atmospheric dust was verified in two different study areas by investigations of single dust storms, wind statistics, wind speed scatter plots divided by the strength of Saharan dust storms, and wind speed differences in dependence of Microwave frequencies and dust component of aerosol optical depth. An increase of the deviations of satellite wind speeds to ground truth wind speeds with higher Microwave frequencies, with stronger dust storms, and with higher amount of coarse dust aerosols in coastal regions was obtained. Strong Saharan dust storms in coastal areas caused mean relative errors in the determination of wind speed by satellite Microwave Sensors of 16.3% at 10.7 GHz and of 20.3% at 37 GHz. The mean relative errors were smaller in the open sea area with 3.7% at 10.7 GHz and with 11.9% at 37 GHz.

E. Santi - One of the best experts on this subject based on the ideXlab platform.

  • Global monitoring of hydrological parameters in Africa by using both active and passive Microwave Sensors
    2009 IEEE International Geoscience and Remote Sensing Symposium, 2009
    Co-Authors: S. Paloscia, P. Pampaloni, S. Pettinato, E. Santi, F. Conti, S. De Santis
    Abstract:

    The possibility of a global monitoring of hydrological parameters in Africa was endeavored by using both active and passive Microwave Sensors. Two ALOS/PALSAR images of Ethiopia were compared with optical data and ground information collected on site by the Istituto Agronomico per l'Oltremare, in Florence. Moreover, AMSR-E data were used as a reference for investigating soil moisture and vegetation conditions. The brightness temperature and the backscattering coefficient values have been related to land features, obtained from ground data and cartographic and meteorological information.

  • Monitoring Snow Cover Characteristics with Multifrequency Active and Passive Microwave Sensors
    2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
    Co-Authors: M. Brogioni, G. Macelloni, S. Paloscia, P. Pampaloni, S. Pettinato, E. Santi
    Abstract:

    The importance of Microwave Sensors in monitoring snow parameters is well recognized. However, several problems are still open regarding the reliability of remote sensing for operational use. In 2002-2005 a series of ERS SAR and ENVISAT ASAR images were collected on the Italian Alps to monitor the temporal evolution of snow cover. In the same time a long sequence of multi-frequency radiometric data was collected with ground based Sensors. The measurements confirmed the potential of Microwave active and passive Sensors in monitoring the extent of wet snow cover and in estimating the liquid water content of wet snow and the snow water equivalent of refrozen snow.

Dennis L. Eggett - One of the best experts on this subject based on the ideXlab platform.

  • Use of Hi-resolution data for evaluating accuracy of traffic volume counts collected by Microwave Sensors
    Journal of Traffic and Transportation Engineering (English Edition), 2017
    Co-Authors: David K Chang, Grant G. Schultz, Mitsuru Saito, Dennis L. Eggett
    Abstract:

    Over the past few years, the Utah Department of Transportation has developed the signal performance metrics (SPMs) system to evaluate the performance of signalized intersections dynamically. This system currently provides data summaries for several performance measures, one of them being turning movement counts collected by Microwave Sensors. As this system became public, there was a need to evaluate the accuracy of the data placed on the SPMs. A large-scale data collection was carried out to meet this need. Vehicles in the Hi-resolution data from Microwave Sensors were matched with the vehicles by ground-truth volume count data. Matching vehicles from the Microwave sensor data and the ground-truth data manually collected required significant effort. A spreadsheet-based data analysis procedure was developed to carry out the task. A mixed model analysis of variance was used to analyze the effects of the factors considered on turning volume count accuracy. The analysis found that approach volume level and number of approach lanes would have significant effect on the accuracy of turning volume counts but the location of the Sensors did not significantly affect the accuracy of turning volume counts. In addition, it was found that the location of lanes in relation to the sensor did not significantly affect the accuracy of lane-by-lane volume counts. This indicated that accuracy analysis could be performed by using total approach volumes without comparing specific turning counts, that is, left-turn, through and right-turn movements. In general, the accuracy of approach volume counts collected by Microwave Sensors were within the margin of error that traffic engineers could accept. The procedure taken to perform the analysis and a summary of accuracy of volume counts for the factor combinations considered are presented in this paper.

  • How Accurate Are Turning Volume Counts Collected by Microwave Sensors
    International Conference on Transportation and Development 2016, 2016
    Co-Authors: David K Chang, Grant G. Schultz, Mitsuru Saito, Dennis L. Eggett
    Abstract:

    The Utah Department of Transportation (UDOT) has recently developed the Signal Performance Metrics System (SPMS) to evaluate the performance of signalized intersections dynamically. This system currently provides data summaries for several performance measures, one of them being turning movement volume counts. As this system became public, there was a need to evaluate the accuracy of the data collected by Microwave Sensors for the SPMS. UDOT considered first that sensor position, number of approach lanes, and volume level would affect the accuracy. Later, speed limit was added as another factor. Data were collected manually and compared with volume count data reported by the system. A mixed model analysis of variance was employed to analyze the effect of each factor on the accuracy of traffic volume counts. The volume level and number of approach lanes factors were found to have a statistically significant effect on the accuracy of traffic volume counts by Microwave Sensors.