The Experts below are selected from a list of 63129 Experts worldwide ranked by ideXlab platform
Jeffrey P Walker - One of the best experts on this subject based on the ideXlab platform.
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requirements of a global near surface soil moisture Satellite Mission accuracy repeat time and spatial resolution
Advances in Water Resources, 2004Co-Authors: Jeffrey P Walker, Paul R HouserAbstract:Soil moisture Satellite Mission accuracy, repeat time and spatial resolution requirements are addressed through a numerical twin data assimilation study. Simulated soil moisture profile retrievals were made by assimilating near-surface soil moisture observations with various accuracy (0, 1, 2, 3, 4, 5 and 10%v/v standard deviation) repeat time (1, 2, 3, 5, 10, 15, 20 and 30 days), and spatial resolution (0.5, 6, 12 18, 30, 60 and 120 arc-min). This study found that near-surface soil moisture observation error must be less than the model forecast error required for a specific application when used as data assimilation input, else slight model forecast degradation may result. It also found that near-surface soil moisture observations must have an accuracy better than 5%v/v to positively impact soil moisture forecasts, and that daily near-surface soil moisture observations achieved the best soil moisture and evapotranspiration forecasts for the repeat times assessed, with 1–5 day repeat times having the greatest impact. Near-surface soil moisture observations with a spatial resolution finer than the land surface model resolution (30 arc-min) produced the best results, with spatial resolutions coarser than the model resolution yielding only a slight degradation. Observations at half the land surface model spatial resolution were found to be appropriate for our application. Moreover, it was found that satisfying the spatial resolution and accuracy requirements was much more important than repeat time. Published by Elsevier Ltd.
G Raju - One of the best experts on this subject based on the ideXlab platform.
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megha tropiques Satellite Mission in flight performances results
International Geoscience and Remote Sensing Symposium, 2012Co-Authors: Nadia Karouche, C Goldstein, Alain Rosak, C Malassingne, G RajuAbstract:MEGHA-TROPIQUES is an CNES-ISRO collaborative Satellite Mission designed to study atmospheric water cycles and energy exchanges in the tropical belt. The Satellite was launched successfully by ISRO in October 2011 from Sriharikota launch pad (India).
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megha tropiques Satellite Mission sensors performances
Remote Sensing, 2010Co-Authors: Nadia Karouche, G RajuAbstract:MEGHA-TROPIQUES is an CNES-ISRO collaborative Satellite Mission designed to study processes related to large tropical convective systems and their life cycle, and to provide key elements related to atmospheric energy and water budget at various time and space scales. The Satellite will perform high repetitive measurements using a low inclined (20°) orbit, and will carry 4 instruments : • MADRAS Instrument: A conical scanning microwave imager designed to estimate precipitations and clouds properties. • SAPHIR Instrument: A microwave sensor used to retrieve vertical humidity profiles. • SCARAB Instrument: An wide band optical radiometer used to retrieve Earth Radiation budget parameters. • GPS-ROS instrument: The sensor will provide temperature and humidity profiles of the Earth's atmosphere The MEGHA-TROPIQUES Satellite is planned to be launched in 2011 by the Indian PSLV launcher. This paper presents the Mission, the Satellite definition and the measured performances of the sensors.
Paul R Houser - One of the best experts on this subject based on the ideXlab platform.
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requirements of a global near surface soil moisture Satellite Mission accuracy repeat time and spatial resolution
Advances in Water Resources, 2004Co-Authors: Jeffrey P Walker, Paul R HouserAbstract:Soil moisture Satellite Mission accuracy, repeat time and spatial resolution requirements are addressed through a numerical twin data assimilation study. Simulated soil moisture profile retrievals were made by assimilating near-surface soil moisture observations with various accuracy (0, 1, 2, 3, 4, 5 and 10%v/v standard deviation) repeat time (1, 2, 3, 5, 10, 15, 20 and 30 days), and spatial resolution (0.5, 6, 12 18, 30, 60 and 120 arc-min). This study found that near-surface soil moisture observation error must be less than the model forecast error required for a specific application when used as data assimilation input, else slight model forecast degradation may result. It also found that near-surface soil moisture observations must have an accuracy better than 5%v/v to positively impact soil moisture forecasts, and that daily near-surface soil moisture observations achieved the best soil moisture and evapotranspiration forecasts for the repeat times assessed, with 1–5 day repeat times having the greatest impact. Near-surface soil moisture observations with a spatial resolution finer than the land surface model resolution (30 arc-min) produced the best results, with spatial resolutions coarser than the model resolution yielding only a slight degradation. Observations at half the land surface model spatial resolution were found to be appropriate for our application. Moreover, it was found that satisfying the spatial resolution and accuracy requirements was much more important than repeat time. Published by Elsevier Ltd.
Xingming Zheng - One of the best experts on this subject based on the ideXlab platform.
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soil moisture experiment in the luan river supporting new Satellite Mission opportunities
Remote Sensing of Environment, 2020Co-Authors: Tianjie Zhao, Jiancheng Shi, Deqing Chen, Qian Cui, Thomas J Jackson, Guangjian Yan, Li Jia, Liangfu Chen, Kai Zhao, Xingming ZhengAbstract:Abstract The Soil Moisture Experiment in the Luan River (SMELR) was conducted from 2017 to 2018 in the semi-arid Luan River watershed located in the North of China. One of the objectives of SMELR is to serve as an assessment tool and demonstration for a new Terrestrial Water Resources Satellite (TWRS) concept with one-dimensional synthetic aperture microwave techniques, for which soil moisture retrieval under variable Satellite observing configurations (mainly in terms of incidence angels) is the greatest challenge. This proposed Mission is targeted to provide continuity for the current Satellite L-band microwave observations, and further improve the accuracy and spatial resolution of soil moisture mapping through the synergistic use of active, passive and optical remote sensing data. Multi-resolution, multi-angle and multi-spectral airborne data were obtained four times over a 70 km by 12 km area in the Shandian River basin, and one time over a 165 km by 5 km area that includes the Xiaoluan River basin. The near surface soil moisture (0 cm–5 cm) was measured extensively on the ground in fifty 1 km by 2 km quadrats (targeted to compare with the airborne radiometer), and two hundred and fifty 200 m by 200 m quadrats corresponding to radar observations. Two networks were established for continuous measurement of the soil moisture and temperature profile (3 cm, 5 cm, 10 cm, 20 cm, 50 cm) and precipitation in the Shandian and Xiaoluan River basin, respectively. Supporting ground measurements also included ground temperature, vegetation water content, surface roughness, continuous measurement of microwave eMission and backscatter at a pasture site, reflectance of various land cover types, evapotranspiration and aerosol observations. Preliminary results within the experimental area indicate that (1) the near surface soil moisture spatial variability at a 200 m scale was up to ~0.1 cm3/cm3 at an intermediate value of ~0.35 cm3/cm3. (2) The difference of soil and vegetation temperature in grass and croplands reach its maximum of 11 K around solar noon time, and the soil temperature gradient is largest at around 15 P.M. (3) Both the airborne and ground measurements cover a wide range of conditions. The L-band active and passive observations exhibit a large variation of ~30 dB and ~80 K, respectively, corresponding to soil moisture range from 0.1 cm3/cm3 to 0.5 cm3/cm3. The sensitivity of both active and passive data to soil moisture is compared at corresponding spatial resolutions and show high information complementarity for better accuracy and resolution soil moisture retrieval.
A J Mannucci - One of the best experts on this subject based on the ideXlab platform.
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demonstrating soil moisture remote sensing with observations from the uk techdemosat 1 Satellite Mission
Geophysical Research Letters, 2016Co-Authors: Clara Chew, Rashmi Shah, Cinzia Zuffada, G A Hajj, Dallas Masters, A J MannucciAbstract:The ability of spaceborne Global Navigation Satellite System (GNSS) bistatic radar receivers to sense changes in soil moisture is investigated using observations from the low Earth orbiting UK TechDemoSat-1 Satellite (TDS-1). Previous studies using receivers on aircraft or towers have shown that ground-reflected GNSS signals are sensitive to changes in soil moisture, though the ability to sense this variable from space has yet to be quantified. Data from TDS-1 show a 7 dB sensitivity of reflected signals to temporal changes in soil moisture. If the effects of surface roughness and vegetation on the reflected signals can be quantified, spaceborne GNSS bistatic radar receivers could provide soil moisture on relatively small spatial and temporal scales.
