A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM/I satellites

Paloscia, S.; Macelloni, Giovanni; Santi, Emanuele; Koike, Takao

doi:10.1109/36.942543

Cited by 155 publications

(69 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…6 which shows the relationship between T b at C-band (H pol., and q = 50°) and SMC of the first 2.5 cm of soil. Here, experimental points, which are rather spread out, have been separated into three groups according to their vegetation cover: (a) bare soils, (b) lowvegetated, and (c) well-vegetated fields, and fitted by the following regression lines, respectively: To correct the SMC retrieval for vegetation effects, a multifrequency algorithm was proposed by Macelloni et al, 2000 andPaloscia et al, 2001c. The algorithm is based on the sensitivity of the Polarization Index, PI, at X-band to the vegetation biomass.…”

Section: Smc Measurements At C-and X-bandmentioning

confidence: 99%

Microwave radiometric measurements of soil moisture in Italy

Macelloni¹,

Paloscia²,

Pampaloni³

et al. 2003

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

Within the framework of the MAP and RAPHAEL projects, airborne experimental campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz). The aim of the experiments was to collect soil moisture and vegetation biomass information on agricultural areas to give reliable inputs to the hydrological models. It is well known that microwave emission from soil, mainly at L-band (1.4 GHz), is very well correlated to its moisture content. Two experimental areas in Italy were selected for this project: one was the Toce Valley, Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence, where flights were performed in 2000. Measurements were carried out on bare soils, corn and wheat fields at different growth stages and on meadows. Ground data of soil moisture (SMC) were collected by other research teams involved in the experiments. From the analysis of the data sets, it has been confirmed that L-band is well related to the SMC of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more affected by the presence of surface roughness and vegetation, especially at high incidence angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to moisture of the brightness temperature at C-band, has been tested using the collected data set. The results of the algorithm, which is able to correct for the effect of vegetation by means of the polarisation index at X-band, have been compared with soil moisture measurements in the ground. Finally, the sensitivity of emission at different frequencies to the soil moisture profile was investigated. Experimental data sets were interpreted by using the Integral Equation Model (IEM) and the outputs of the model were used to train an artificial neural network to reproduce the soil moisture content at different depths.

show abstract

Section: Smc Measurements At C-and X-bandmentioning

confidence: 99%

Microwave radiometric measurements of soil moisture in Italy

Macelloni¹,

Paloscia²,

Pampaloni³

et al. 2003

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, there is an urgent need to adapt other microwave sensors to this application (Jackson 1997, Paloscia et al, 2001Jackson et al, 2002;Walker and Houser, 2004). Working in the framework of hydro-geological risk mitigation, where the critical problem is to follow the rapid variations of superficial conditions, the choice will be addressed towards those satellite sensors which ensure high revisit time (Schmugge et al, 2002).…”

Section: The Advanced Microwave Sounding Unit (Amsu)mentioning

confidence: 99%

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Lacava

Greco

Leo

et al. 2005

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltrationrunoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weatherrelated satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards.Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques.Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past.Correspondence to: N. Pergola (pergola@imaa.cnr.it)In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the SWVI was able to identify the presence of a sort of "early" signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability.

show abstract

“…Since the advent of spaceborne microwave sensors in the late 1970s, various large-scale surface soil moisture products have been derived from C-and/or X-band data collected by the Scanning Multichannel Microwave Radiometer (SMMR) [1], followed by the Special Sensor Microwave/Imager (SSM/I) [2], Advanced Microwave Instrument (AMI) [3], Advanced Microwave Scanning Radiometer (AMSR) [4] and Advanced Scatterometer (ASCAT) [5], among others. More recently, the first space mission dedicated to observing surface soil moisture globally was launched in November, 2009 [6].…”

Section: Introductionmentioning

confidence: 99%

Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco

et al. 2015

View full text Add to dashboard Cite

Data disaggregation (or downscaling) is becoming a recognized modeling framework to improve the spatial resolution of available surface soil moisture satellite products. However, depending on the quality of the scale change modeling and on the uncertainty in its input data, disaggregation may improve or degrade soil moisture information at high resolution. Hence, defining a relevant metric for evaluating such methodologies is crucial before disaggregated data can be eventually used in fine-scale studies. In this paper, a new metric, named G DOWN , is proposed to assess the potential gain provided by disaggregation relative to the non-disaggregation case. The performance metric is tested during a four-year period by comparing 1-km resolution disaggregation based on physical and theoretical scale change (DISPATCH) data with the soil moisture measurements collected by six stations in central Morocco. DISPATCH data are obtained every 2-3 days from 40-km resolution SMOS (Soil Moisture Ocean Salinity) and 1-km resolution optical MODIS (Moderate Resolution Imaging Spectroradiometer) data. The correlation coefficient between G DOWN and the disaggregation gain in time series correlation, mean bias and bias in the slope of the linear fit ranges from 0.5 to 0.8. The new metric is found to be a good Remote Sens. 2015, 7 3784 indicator of the overall performance of DISPATCH. Especially, the sign of G DOWN (positive in the case of effective disaggregation and negative in the opposite case) is independent of the uncertainties in SMOS data and of the representativeness of localized in situ measurements at the downscaling (1 km) resolution. In contrast, the traditional root mean square difference between disaggregation output and in situ measurements is poorly correlated (correlation coefficient of about 0.0) with the disaggregation gain in terms of both time series correlation and bias in the slope of the linear fit. The G DOWN approach is generic and thus could help test a range of downscaling methods dedicated to soil moisture and to other geophysical variables.

show abstract

A multifrequency algorithm for the retrieval of soil moisture on a large scale using microwave data from SMMR and SSM/I satellites

Cited by 155 publications

References 16 publications

Microwave radiometric measurements of soil moisture in Italy

Microwave radiometric measurements of soil moisture in Italy

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco

Contact Info

Product

Resources

About