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1.
The microwave radiometric measurements made by the Skylab 1.4 GHz radiometer and by the 6.6 GHz and 10.7 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer were analyzed to study the large-area soil moisture variations of land surfaces. Two regions in Texas, one with sparse and the other with dense vegetation covers, were selected for the study. The results gave a confirmation of the vegetation effect observed by ground-level microwave radiometers. Based on the statistics of the satellite data, it was possible to estimate surface soil moisture in about five different levels from dry to wet conditions with a 1.4 GHz radiometer, provided that the biomass of the vegetation cover could be independently measured. At frequencies greater than about 6.6 GHz, the radiometric measurements showed little sensitivity to moisture variation for vegetation-covered soils. The effects of polarization in microwave emission were studied also.  相似文献   

2.
Synergistic measurements of both active and passive nadir looking microwave sensors onboard Topex/Poseidon (T/P) satellite are explored for their instantaneous rain estimation capability over tropical oceans. Data of T/P altimeter (the differential radar backscatter at C and Ku band frequencies, i.e. δσ°?=?σ°C?σ°Ku), and Topex microwave radiometer (TMR) (brightness temperatures at 18, 21 and 37?GHz frequencies) coincident with special sensor microwave/imager (SSM/I) and tropical rainfall measuring mission (TRMM)–microwave radiometer (TMI) have been analysed for this purpose. The rainfall response has been separated from the surface variability and atmospheric water content (in terms of water vapour and liquid water), by analysing the TMR data in view of the radiative response of its channels under different ocean–atmospheric conditions over the Indian oceanic region. Among a large collocated data on different spatial and temporal scales, the most restrictive criteria (<?10?km spatial, <?30?min temporal difference) produce the better statistics (in terms of correlation and rms errors) from the rainfall rate from SSM/I and TMI with the combined radar and radiometric observations from T/P and TMR respectively. The analysis thus shows the added advantage of optimally integrated active and passive microwave measurements for instantaneous rain estimation as compared to our earlier study (Varma et al. ) by passive TMR measurements alone, for both better estimation of rain and corrections to T/P radar backscatter due to its path attenuation. The equation is further used to estimate monthly averaged global rain rate maps for its qualitative and quantitative assessment. Typical rain rate maps from blended radar and radiometer for two contrasting seasons for the months of January and July for the year 2000 (during the north‐east and south‐west monsoon respectively), are compared with similar maps of TRMM–precipitation radar of monthly rainfall accumulations, showing most of the regional and global tropical features delineated.  相似文献   

3.
Monitoring the characteristics of spatially and temporally distributed soil moisture is important to the study of hydrology and climatology for understanding and calculating the surface water balance. The major difficulties in retrieving soil moisture with Synthetic Aperture Radar (SAR) measurements are due to the effects of surface roughness and vegetation cover. In this study we demonstrate a technique to estimate the relative soil moisture change by using multi‐temporal C band HH polarized Radarsat ScanSAR data. This technique includes two components. The first is to minimize the effects of surface roughness by using two microwave radar measurements with different incidence angles for estimation of the relative soil moisture change defined as the ratio between two soil volumetric moistures. This was done by the development of a semi‐empirical backscattering model using a database that simulated the Advanced Integral Equation Model for a wide range of soil moisture and surface roughness conditions to characterize the surface roughness effects at different incidence angles. The second is to reduce the effects of vegetation cover on radar measurements by using a semi‐empirical vegetation model and the measurements obtained from the optical sensors (Landsat TM and AVHRR). The vegetation correction was performed based on a first‐order semi‐empirical backscattering vegetation model with the vegetation water content information obtained from the optical sensors as the input. For the validation of this newly developed technique, we compared experimental data obtained from the Southern Great Plain Soil Moisture Experiment in 1997 (SGP97) with our estimations. Comparison with the ground soil moisture measurements showed a good agreement for predication of the relative soil moisture change, in terms of ratio, with a Root Mean Square Error (RMSE) of 1.14. The spatially distributed maps of the relative soil moisture change derived from Radarsat data were also compared with those derived from the airborne passive microwave radiometer ESTAR. The maps of the spatial characteristics of the relative soil moisture change showed comparable results.  相似文献   

4.
Passive microwave remote-sensing techniques can monitor surface soil freeze/thaw states at the frozen soil surface. Studies found that the negative spectral gradient at 19 and 37 GHz is a good criterion for the determination of frozen soil. To remove vegetation effects on soil microwave emission signatures, only vegetation attenuation was considered, omitting vegetation emission contributions. Studies on vegetation effects indicated that at high frequencies, scattering and attenuation effects should be considered. In this article, a matrix-doubling microwave emission model evaluated vegetation effects in a cold environment at 18.7 and 36.5 GHz. To verify the model, a multi-channel truck-mounted radiometer collected emission data at a young tree stand and a grass-like field in 2008. Comparisons between model simulations and field measurements corresponded well. The model then established an emission database of natural, vegetated surface in the freezing environment, matched with the τ–ω model (which is a zeroth-order microwave emission model) in the same environment using least-square error. The effective scattering and attenuation of vegetation at both frequencies in the freezing environment were retrieved.  相似文献   

5.
FY-3微波成像仪地表参数反演研究   总被引:5,自引:2,他引:5  
风云3号卫星FY-3是实现全球、全天候、三维、定量、多光谱遥感的我国第2代极轨气象卫星系列。风云3号气象卫星资料中含有丰富的生态环境变化信息,既可以用于对水、火、冰、雪等灾害的监测,也可以用于对植被、土地利用、气溶胶参量的分析。这些结果将会对农业、林业、环境、市政、交通以及政府决策部门提供有效的决策服务。其中搭载的微波成像仪为我国第一个星载微波遥感仪器,其设计频率为10.65 GHz、18.7 GHz、23.8 GHz、36.5 GHz、89 GHz,每个频率有V、H两种不同极化模式,相应的星下点空间分辨率分别为51 km×85 km、30 km×50 km、27 km×45 km、18 km×30 km、9 km×15 km根据FY-3微波成像仪传感器参数特性,利用微波地表辐射传输方程,在10.65、18.7 GHz频段上模拟了地表微波辐射特性,在此基础上建立了地表参数反演算法,
可以同时得到地表土壤水分和地表温度参数。
  相似文献   

6.
7.
Abstract

Microwave radiometer measurements of soil moisture content were made over bare and vegetated fields with dual polarized microwave radiometers at 1·55GHz (L-band) and 19·1 GHz (K.-band). Two typical Indian crops Bazra and Gawar have been studied. The bare field measurements were used to investigate the effect of soil texture on sensitivity of a radiometer to soil moisture and for soil moisture sampling depth. It is found that expression of soil moisture as available moisture content in the soil can minimize the texture effect. The estimated soil moisture sampling depth for L-band is 2-5 cm, while for K-band it is less than 2 cm. The vegetation cover affects the sensitivity of the radiometer to soil moisture. This effect is more pronounced the denser the vegetation and higher the frequency of observation. The measured polarization factor over a vegetated field at L-band was found to be appreciably reduced compared to that over a bare field. The difference between normalized brightness temperature from L-band and K-band is sensitive to vegetation type. The soil moisture under vegetation cover at L-band can be predicted well using Jackson's parametric model.  相似文献   

8.

A simple formulation relating the L-band microwave brightness temperature detected by a passive microwave radiometer to the near surface soil moisture was developed using MICRO-SWEAT, a coupled microwave emission model and soil-vegetation-atmosphere-transfer (SVAT) scheme. This simple model provides an ideal tool with which to explore the impact of sub-pixel heterogeneity on the retrieval of soil moisture from microwave brightness temperatures. In the case of a bare soil pixel, the relationship between apparent emissivity and surface soil moisture is approximately linear, with the clay content of the soil influencing just the intercept of this relationship. It is shown that there are no errors in the retrieved soil moisture from a bare soil pixel that is heterogeneous in soil moisture and texture. However, in the case of a vegetated pixel, the slope of the relationship between apparent emissivity and surface soil moisture decreases with increasing vegetation. Therefore for a pixel that is heterogeneous in vegetation and soil moisture, errors can be introduced into the retrieved soil moisture. Generally, under moderate conditions, the retrieved soil moisture is within 3% of the actual soil moisture. Examples illustrating this discussion use data collected during the Southern Great Plains '97 Experiment (SGP97).  相似文献   

9.
Data gathered during the NASA sponsored Multisensor Aircraft Campaign Hydrology (MACHYDRO) experiment in central Pennsylvania (U.S.A.) in July, 1990 have been analysed to study the combined use of active and passive microwave sensors for estimating soil moisture from vegetated areas. These data sets were obtained during an eleven-day period with NASA's Airborne Synthetic Aperture Radar (AIRSAR), and Push-Broom Microwave Radiometer (PBMR) over an instrumented watershed, which included agricultural fields with a number of different crop covers. Simultaneous ground truth measurements were also made in order to characterize the state of vegetation and soil moisture under a variety of meteorological conditions. Various multi-sensor techniques are currently under investigation to improve the accuracy of remote sensing estimates of the soil moisture in the presence of vegetation and surface roughness conditions using these data sets. One such algorithm involving combination of active and passive microwave sensors is presented here, and is applied to representative corn fields in the Mahantango watershed that was the focus of study during the MACHYDRO experiment. In this algorithm, a simple emission model is inverted to obtain Fresnel reflectivity in terms of ground and vegetation parameters. Since Fresnel reflectivity depends on soil dielectric constant, soil moisture is determined from reflectivity using dielectric-soil moisture relations. The algorithm requires brightness temperature, vegetation and ground parameters as the input parameters. The former is measured by a passive microwave technique and the later two are estimated by using active microwave techniques. The soil moisture estimates obtained by this combined use of active and passive microwave remote sensing techniques, show an excellent agreement with the in situ soil moisture measurements made during the MACHYDRO experiment.  相似文献   

10.
被动微波遥感反演土壤水分进展研究   总被引:13,自引:2,他引:13  
在地球系统中, 地表土壤水分是陆地和大气能量交换过程中的重要因子, 并对陆地表面蒸散、水的运移、碳循环有很强的控制作用, 大面积监测土壤水分在水文、气象和农业科学领域具有较大的应用潜力。被动微波遥感是监测土壤含水量最有效的手段之一, 相比红外与可见光, 它具有波长长, 穿透能力强的优势, 相比主动微波雷达, 被动微波辐射计具有监测面积大、周期短, 受粗糙度影响小, 对土壤水分更为敏感, 算法更为成熟的优势。然而微波辐射计观测到的亮温除了受土壤水分影响外, 还要考虑如植被覆盖、土壤温度、雪覆盖以及地形、地表粗糙度、土壤纹理和大气效应以及地表的异质性等其它因子的影响。目前, 已研究出许多使用被动微波辐射计反演土壤水分的方法,这些方法大部分是围绕着土壤湿度与亮温温度之间的关系进行, 同时也考虑其它各种不同因子对
地表微波辐射的影响。从介绍被动微波反演地表参数的原理入手, 重点介绍被动遥感反演土壤水分当前的算法进展、研究趋势等。  相似文献   

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