Delimitation of low topsoil moisture content areas in a vineyard using remote sensing imagery (Sentinel-1 and Sentinel-2) in a Mediterranean-climate region

Abstract

Irrigation can be responsible for salt accumulation in the root zone of grapevines when late autumn and winter precipitation is not enough to leach salts from the soil upper horizons, turning the soil unsuitable for grape production. The aim of this work is to present a novel methodology to outline areas, within a drip-irrigated vineyard, with a low soil moisture content (SMC) during, and after, an 11-month agricultural drought. Soil moisture (SM) field measurements were performed in two plots at the vineyard, followed by a geostatistical method (indicator kriging) to estimate the SM class probabilities according to a threshold value, enlarging the training set for the classification algorithms. The logistic regression (LR) and Random Forest (RF) methods used the features of the Sentinel-1 and Sentinel-2 images and terrain parameters to classify the SMC probabilities at the vineyard. Both methods classified the highest SMC probabilities above 14% that is located close to the stream at the lower altitudes. The RF method performed very well in classifying the topsoil zones with a lower SMC during the autumn-winter period. This delineation allows the prevention of the occurrence of areas affected by salinisation, indicating which areas will need irrigation management strategies to control the salinity, especially under climate change, and the expected increase in droughts.

Synergistic estimation of soil salinity based on Sentinel-1 image texture and Sentinel-2 salinity spectral indices

“…The successful application of multisource remote sensing fusion data in predicting soil properties depends heavily on the match of spatial and temporal scales 6 . Unfortunately, the date of the soil sample collection in this study did not exactly coincide with the date of remote sensing data collection, and the data collection of S-1 and S-2 also had temporal variability, which was also frequently seen in previous SSC digital mapping studies 54 , 55 . Although there were no significant changes in soil salinity in the study area during our data collection time, sudden changes in external factors can have a large impact on soil salinity content and distribution, especially during irrigation periods and rainy seasons.…”

“…6 Unfortunately, the date of the soil sample collection in this study did not exactly coincide with the date of remote sensing data collection, and the data collection of S-1 and S-2 also had temporal variability, which was also frequently seen in previous SSC digital mapping studies. 54,55 Although there were no significant changes in soil salinity in the study area during our data collection time, sudden changes in external factors can have a large impact on soil salinity content and distribution, especially during irrigation periods and rainy seasons. Therefore, further studies on the remote sensing data acquisition date are needed to reduce the impact on SSC mapping.…”

Synthetic Aperture Radar in Vineyard Monitoring: Examples, Demonstrations, and Future Perspectives

“…A methodology using soil moisture measurements, satellite images from Sentinel-1 and Sentinel-2, and terrain parameters to identify areas with low soil moisture content in a drip-irrigated vineyard during an agricultural drought is presented in Mendes et al [62]. The study highlights the potential of using remote sensing data as a cost-effective solution for monitoring soil moisture content and predicting areas at risk of salinization in vineyards, especially considering the expected increase in droughts due to climate change.…”

Detecting Variability and Analyzing Vineyards Vegetation Characteristics Using Satellite Remote Sensing Data in Aswan, Egypt

“…For example, essential for regional crop monitoring and accurate management rice (Yang et al, 2021). Sentinel-1 has gained usage in monitoring crop meteorological disasters and assessing losses, specifically for detecting frost damage in grapes (Li et al, 2021), and drought monitoring (Mendes et al, 2021). The widespread utilization of Sentinel-1 radar data highlights its potential in detecting changes and monitoring various fields.…”