Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

Abstract

The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (ENVISAT/ASAR and FORMOSAT-2). Time series of images were collected over the Yaqui irrigated area (Mexico) throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data indicates that the sensitivity of the radar signal to vegetation is masked by the variability of soil conditions. On-going irrigated areas can be detected all over the wheat growing season. The empirical algorithm developed for the retrieval of topsoil moisture from ENVISAT/ASAR images takes advantage of the unique capabilities of the FORMOSAT-2 instrument to monitor the seasonality of wheat canopies. Topsoil moisture estimates are scattered at the timing of plant emergence and during plant senescence. Estimates are much more accurate from tillering to grain filling stages with an absolute error about 9% (0.09 m<sup>3</sup> m<sup>−3</sup>, 35% in relative value). This result is attractive since topsoil moisture is estimated at a high spatial resolution (i.e. over subfields of about 5 ha) for a large range of biomass water content (from 5 and 65 t ha<sup>−1</sup>) independently from the viewing angle of ASAR acquisition (incidence angles IS1 to IS6)

Consistency between In Situ, Model-Derived and High-Resolution-Image-Based Soil Temperature Endmembers: Towards a Robust Data-Based Model for Multi-Resolution Monitoring of Crop Evapotranspiration

“…Meteorological data, including air temperature, relative air humidity, solar radiation and wind speed, were acquired every half hour, from 27 December 2007-17 May 2008 from a station located in the center of the region. The acquisition height was 10 m. Further details on the experiment can be found in [14,[30][31][32].…”

Calibration of the Water Cloud Model at C-Band for Winter Crop Fields and Grasslands

“…This vegetation parameter could be estimated from optical data. Therefore, the best way for soil moisture retrieval over areas covered by vegetation is to combine SAR and optical data [4][5][6][16][17][18][19][20]. Currently, the high temporal repetitiveness of Sentinel-1 and Sentinel-2 data makes it possible to combine SAR and optical data for soil moisture monitoring at time scale close to user requirements (weekly to daily depending on the applications).…”

Usefulness of Technological Capacity Evaluation for Brazilian Farmer Stakeholders: A Bibliometric Analysis

“…Figure 5 shows one proposal of a model structure that will be built to increase new technologies that can be adopted later on. In the image is shown a model with two new technologies that are not found in the survey made about the technological capacity indicators and that will be used in the productive process: geolocalization for correcting the soil [15], and the adoption of a consortium of cultures [16]. This structure will allow for including as many technologies as needed for making the model more realistic-for example, the technologies shown in blue in Figure 5, or any other new technology that may be adopted later for correcting the soil.…”