Sensitivity analysis of X-band SAR to wheat and barley leaf area index in the Merguellil Basin

Fontanelli, Giacomo; Paloscia, S.; Zribi, Mehrez; Chahbi, Aîcha

doi:10.1080/2150704x.2013.842285

Cited by 66 publications

(37 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unfortunately, we obtained CSK images at VV polarization just in the first growth phase of wheat crops and therefore the decreasing trend was not confirmed at higher values of biomass for the presented data. Further investigations, carried out on a test site in Tunisia, on wheat fields well-developed confirmed instead this trend by using TerraSAR-X data too [Fontanelli et al, 2013]. An analogous behavior was observed on colza, which, at the beginning of its growth, is a plant with characteristics significantly different from those of wheat.…”

Section: Sensitivity To Vegetationmentioning

confidence: 63%

HydroCosmo: The Monitoring of Hydrological Parameters on Agricultural Areas by using Cosmo-SkyMed Images

Fontanelli¹,

Paloscia²,

Pampaloni³

et al. 2013

European Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

In this paper, the results of an experiment carried out for exploiting the capabilities of X-band Cosmo-SkyMed data in the monitoring of soil and vegetation characteristics are summarized. SAR data have been collected in two agricultural areas in Italy and compared with ground truth measurements of soil and vegetation parameters. A rather good sensitivity to vegetation features, biomass and the moisture of bare or slightly vegetated soils has been confirmed. On bare surfaces the effect of surface roughness was significant, as expected, due to the high observation frequency. Model simulations have also been performed for better explaining the backscattering response to soil moisture at this frequency. The different backscattering response according to vegetation types, which has already been observed at C-band, has been confirmed at X-band, too. The absorption due to thin vertical stems was observed on wheat crops, whereas sunflower showed a prevalent scattering behavior due to the large circular leaves.

show abstract

Section: Sensitivity To Vegetationmentioning

confidence: 63%

HydroCosmo: The Monitoring of Hydrological Parameters on Agricultural Areas by using Cosmo-SkyMed Images

Fontanelli¹,

Paloscia²,

Pampaloni³

et al. 2013

European Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…[5]. Active and passive microwave remote-sensing techniques are thus an important source of data, for which numerous studies have proposed various inversion algorithms for soil and vegetation characterization, including operational estimations [6][7][8][9][10][11][12]. The Global Navigation Satellite System-Reflectometry (GNSS-R) is a microwave technique based on bistatic radar observations, which appeared at the beginning of the 1990s.…”

Section: Introductionmentioning

confidence: 99%

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

et al. 2018

Self Cite

View full text Add to dashboard Cite

Abstract:The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI'2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

show abstract

“…In addition, the increase in the vegetation contribution as a function of the LAI, combined with the decrease in the soil moisture contribution (Mv between 0.10 and 0.20 cm [87][88][89][90][91][92][93]. Previous results have shown that the radar signal decreases with an increase in the LAI for narrow leaf crops (wheat, alfalfa, and barley), and increases for board leaf crops (sunflower, corn, sorghum, and sugarcane) [91,93]. For example, Champion [87] studied the sensitivity of radar signals in C and X bands to the LAI of wheat crops (soil moisture values between 0.05 and 0.20 cm decreases as vegetation density increases (higher sensitivity for biomass lower than 1 kg/m 2 ).…”

mentioning

confidence: 99%

Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data

Hajj¹,

Baghdadi²,

Belaud³

et al. 2014

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Abstract:The objective of this study was to analyze the sensitivity of radar signals in the X-band in irrigated grassland conditions. The backscattered radar signals were analyzed according to soil moisture and vegetation parameters using linear regression models. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT and LANDSAT) images was acquired at a high temporal frequency in 2013 over a small agricultural region in southeastern France. Ground measurements were conducted simultaneously with the satellite data acquisitions during several grassland growing cycles to monitor the evolution of the soil and vegetation characteristics. The comparison between the Normalized Difference Vegetation Index (NDVI) computed from optical images and the in situ Leaf Area Index (LAI) showed a logarithmic relationship with a greater scattering for the dates . Results showed that the radar signal depends on variations in soil moisture, with a higher sensitivity to soil moisture for biomass lower than 1 kg/m². HH and HV polarizations had approximately similar sensitivities to soil moisture. The penetration depth of the radar wave in the X-band was high, even for dense and high vegetation; flooded areas were visible in the images with higher detection potential in HH polarization than in HV polarization, even for vegetation heights reaching 1 m. Lower sensitivity was observed at the X-band between the radar signal and the vegetation parameters with very limited potential of the X-band to monitor grassland growth. These results showed that it is possible to track gravity irrigation and soil moisture variations from SAR X-band images acquired at high spatial resolution (an incidence angle near 30°).

show abstract

Sensitivity analysis of X-band SAR to wheat and barley leaf area index in the Merguellil Basin

Cited by 66 publications

References 31 publications

HydroCosmo: The Monitoring of Hydrological Parameters on Agricultural Areas by using Cosmo-SkyMed Images

HydroCosmo: The Monitoring of Hydrological Parameters on Agricultural Areas by using Cosmo-SkyMed Images

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data

Contact Info

Product

Resources

About