Assessing the potential of fully-polarimetric simultaneous mono- and bistatic airborne SAR acquisitions in L-band for applications in agriculture and hydrology

Theoretical studies have shown that the use of simultaneous mono- and bistatic synthetic aperture radar (SAR) data could be beneficial to agriculture and soil moisture monitoring. This study makes use of extensive ground-truth measurements and synchronous high-resolution fully-polarimetric mono- and bistatic airborne SAR data in L-band to assess and compare the sensitivity of mono- and multistatic systems to maize crop variables, soil moisture, and surface roughness. Its results suggest that bistatic data, even with a very small bistatic angle, provide valuable additional information for maize crop biophysical parameter retrieval. However, this does not appear to be the case for soil moisture retrieval over bare soils

Assessing the Potential of Fully Polarimetric Mono- and Bistatic SAR Acquisitions in L-band for Crop and Soil Monitoring

Theoretical studies have shown that the use of simultaneous mono- and bistatic synthetic aperture radar (SAR) data could be beneficial to agriculture and soil moisture monitoring. This study makes use of extensive ground-truth measurements and synchronous high-resolution fully polarimetric mono- and bistatic airborne SAR data in L-band to assess and compare the sensitivity of mono- and multistatic systems to the maize canopy row structure and biophysical variables, as well as to soil moisture, and surface roughness in both vegetated and bare fields. The effect of the row structure of maize crops is assessed through the impact of the orientation of the planting rows relative to the sensor beam on microwave scattering measurements. The results of this analysis suggest that the row orientation of maize crops has a significant influence on both mono- and bistatic scattering measurements in both co-polarizations, and especially in HH, while the cross-polarizations are not affected. Furthermore, the study also shows through a linear regression analysis that bistatic data, even with a very small bistatic baseline, can provide valuable additional information for maize crop biophysical variable retrieval, which however does not appear to be the case for soil moisture retrieval over bare soils

Soil Moisture Retrieval Using Multistatic L-Band SAR and Effective Roughness Modeling

International audienceThe interest in bistatic SAR systems for soil moisture monitoring has grown over recent years, since theoretical studies suggest that the impact of surface roughness on the retrieval of soil moisture decreases when multistatic, i.e., simultaneous mono-and bistatic, radar measurements are used. This paper presents a semi-empirical method to retrieve soil moisture over bare agricultural fields, based on effective roughness modeling, and applies it to a series of L-band fully-polarized SAR backscatter and bistatic scattering observations. The main advantage of using effective roughness parameters is that surface roughness no longer needs to be measured in the field, what is known to be the main source of error in soil moisture retrieval applications. By means of cross-validation, it is shown that the proposed method results in accurate soil moisture retrieval with an RMSE well below 0.05 m3 /m3, with the best performance observed for the cross-polarized backscatter signal. In addition, different experimental SAR monostatic and bistatic configurations are evaluated in this study using the proposed retrieval technique. Results illustrate that the soil moisture retrieval performance increases by using backscatter data in multiple polarizations simultaneously, compared to the case where backscatter observations in only one polarization mode are used. Furthermore, the retrieval performance of a multistatic system has been evaluated and compared to that of a traditional monostatic system. The recent BELSAR campaign (in 2018) provides time-series of experimental airborne SAR measurements in two bistatic geometries, i.e., the across-track (XTI) and along-track (ATI) flight configuration. For both configurations, bistatic observations are available in the backward region. The results show that the simultaneous use of backscatter and bistatic scattering data does not result in a profound increase in retrieval performance for the bistatic configuration flown during BELSAR 2018. As theoretical studies demonstrate a strong improvement in retrieval performance when using backscatter and bistatic scattering coefficients in the forward region simultaneously, the introduction of additional bistatic airborne campaigns with more promising multistatic SAR configurations is highly recommended

Green Area Index and Soil Moisture Retrieval in Maize Fields Using Multi-Polarized C- and L-Band SAR Data and the Water Cloud Model

The green area index (GAI) and the soil moisture under the canopy are two key variables for agricultural monitoring. The current most accurate GAI estimation methods exploit optical data and are rendered ineffective in the case of frequent cloud cover. Synthetic aperture radar (SAR) measurements could allow the remote estimation of both variables at the parcel level, on a large scale and regardless of clouds. In this study, several methods were implemented and tested for the simultaneous estimation of both variables using the water cloud model (WCM) and dual-polarized radar backscatter measurements. The methods were tested on the BELSAR-Campaign data set consisting of in-situ measurements of bio-geophysical variables of vegetation and soil in maize fields combined with multi-polarized C- and L-band SAR data from Sentinel-1 and BELSAR. Accurate GAI estimates were obtained using a random forest regressor for the inversion of a pair of WCMs calibrated using cross and vertical co-polarized SAR data in L- and C-band, with correlation coefficients of 0.79 and 0.65 and RMSEs of 0.77 m2m−2 and 0.98 m2m−2, respectively, between estimates and in-situ measurements. The WCM, however, proved inadequate for soil moisture monitoring in the conditions of the campaign. These promising results indicate that GAI retrieval in maize crops using only dual-polarized radar data could successfully substitute for estimates derived from optical data

The BELSAR dataset: Mono- and bistatic full-pol L-band SAR for agriculture and hydrology

Abstract The BELSAR dataset consists of high-resolution multitemporal airborne mono- and bistatic fully-polarimetric synthetic aperture radar (SAR) data in L-band, alongside concurrent measurements of vegetation and soil biogeophysical variables measured in maize and winter wheat fields during the summer of 2018 in Belgium. Its collection was funded by the European Space Agency (ESA) to address the lack of publicly-accessible experimental datasets combining multistatic SAR and in situ measurements. As such, it offers an opportunity to advance the development of SAR remote sensing science and applications for agricultural monitoring and hydrology. This paper aims to facilitate its adoption and exploration by offering comprehensive documentation and integrating its multiple data sources into a unified, analysis-ready dataset

The impact of COVID-19 confinement measures on the canopy urban heat island intensity of Ghent (Belgium)

In the context of the COVID-19 outbreak, a strict lockdown was ordered by Belgian authorities from 18/03/2020 till 04/05/2020. This led to a limitation of industrial production, human activities and transport use where only essential motorized transport were permitted. This research is an attempt to study the impact of these measures on the canopy layer urban heat island intensity in the city of Ghent. We used the high-accuracy observational MOCCA (MOnitoring the City’s Climate and Atmosphere) network. This network is monitoring the urban climate of the city of Ghent since July 2016. The network consists of six weather stations in the Ghent region and provides a database of hourly observation including 2m temperature at six locations (including dense urban, industrial and suburban). Only clear-sky days with an average wind speed lower than 3 m/s were selected for both the confinement period in 2020 and for similar periods in the reference years 2017, 2018 and 2019. For the years 2017, 2018 and 2019 respectively 3, 3 and 7 reference days were retained to compare with 9 selected days of the 2020 confinement period. Results indicate a lower UHI intensity during the day for 2020 compared to the reference years for the dense, industrial and suburban site. A statistically significant difference was found at 15h, 16h, and 17h for the dense urban site (Provinciehuis). The statistical test did not give significant difference for the suburban site (Wondelgem). Human activities in the urban dense areas release a large amount of heat, which can directly heat the air and during the daytime around 16h when the storage heat flux switch from positive to negative values with weak value of the net radiation fluxes, the external source of energy due to the anthropogenic heat can drive the surrounding hot air to mix with local air and further warm near‐surface air temperature (2 m above ground level). However, during the lockdown period this external contribution to the surface energy balance was absent inducing a cooling gradient of the temperature in the dense urban site (Provinciehuis) up to 0.4°C/h around 18h-19h stronger in 2020 compared to the references years. During nighttime the UHI intensity becomes larger mainly driven by the release of energy stored during the day and the UHI intensities are similar for 2020 and the reference years indicating that the lockdown measures will not have had an impact on the UHI intensity during the night