Soil moisture estimation in Ferlo region (Senegal) using radar (ENVISAT/ASAR) and optical (SPOT/VEGETATION) data

Complementarity of Sentinel-1 and Sentinel-2 Data for Mapping Agricultural Areas in Senegal

“…The dispersion of radar data was evaluated by comparing the mean and median values of the backscattering coefficients of each crop to see the influence of the extreme values. This is usually caused by the sensitivity of the radar signal to humidity and soil roughness, especially at the beginning of the growing season when the plant cover is low [22] [26]. Subsequently, the temporal profiles of the signals of the three cultures following under two polarizations (VV and VH) were analysed and compared in order to look for differences in backscattering between the cultures during their phenological cycle.…”

“…The signals for each of the three crops were similar during the growth phase ( Figure 6(a)). This situation is explained by the fact that during this period, the contribution of soil (roughness and humidity) was often greater than that of vegetation because of the low vegetation cover [22]. It was therefore difficult to discriminate crops during the first part of the rainy season.…”

“…Conversely, radar data are not disturbed by atmospheric conditions but their sensitivity to different surface parameters (soil roughness, soil moisture and vegetation) limit their efficiency in the monitoring and mapping of herbaceous vegetation [22]. However, analysing the temporal profile of these data under different polarizations can provide important information to discriminate types of crops, especially because of differences in phenological cycles plant shapes and sizes during the various stages of the growing season [23].…”

Algorithm for the Joint Flight of Two Uncrewed Aerial Vehicles Constituting a Bistatic Radar System for the Soil Remote Sensing

“…There are also several algorithms (Nguyen et al, 2022), models (Pandey & Jain, 2022;Yang et al, 2021), and software products (Salam et al, 2019;Kim, 2021;Barca et al, 2021) available for real use (Saddik et al, 2021). However, most of the information about SM obtained using radiometric remote (satellite) sensing systems (ASCAT, AMSR-E, AMSR2, SMAP, SMOS) (Amazirh et al, 2018;Faye et al,2018;Mandal et al,2020) are usually surface SM (a few millimeters deep for optical and thermal range) (Barca et al, 2021;Elkharrouba et al, 2022) or near surface SM (a few centimeters deep for X-, C-, or L-frequency microwave sensors) (Bandini et al, 2020;Ivushkin et al, 2021). It is not possible to estimate the moisture content of the root zone.…”