# Remote and Proximal Sensing Techniques for Site-Specific Irrigation Management in the Olive Orchard
## 2 Materials and Methods
### Proximal Soil Sensing and Soil Analysis  
Two different proximal soil sensors (PSS) were used to map soil spatial variability at high resolution. The proximal sensors used were: (i) EM38-Mk2 electromagnetic induction sensor (Geonics Ltd., Mississauga, ON, Canada); (ii) \"The Mole\", gamma-ray spectro-radiometer (Soil Company, Groningen, The Netherlands). The EM38-Mk2 measures the apparent electrical conductivity (ECa) of the soil at two depth ranges of about 0-0.75 (ECa\({}_{1}\)) and 0-1.50 m (ECa\({}_{2}\)) [50]. Soil physical properties, such as texture, stoniness, bulk density [51], soil moisture and water availability [52; 53], soil depth [54], as well as organic matter [55] all affect ECa. \"The Mole\" spectroradiometer continuously measures the natural gamma-ray emission coming from the first 0.3-0.4 m of the soil and rocks, through a Cesium Iodide scintillator crystal [56]. The gamma-ray spectra were analyzed by a Full Spectrum Analysis (FSA), using \"The Gammman\" software (Medusa Systems, The Netherlands) [22]. This method identifies and deletes data outliers, as well as processes gamma-ray spectrum for calculation of individual nuclide concentrations (40 K, 238 U, 232 Th) and total counts (TC_gamma) in Bq-kg\({}^{-1}\). TC_gamma depicts the total count measured by the CsI scintillator for the whole range of energy bands. Proximal gamma-radiometrics has been used to survey topsoil features, such as texture [57], gravel content [22], potassium [58]), and organic carbon [59]. Both the gamma-ray spectroradiometer and EM38-Mk2 were manually driven (without using a tractor or ATV), since the size of the experimental field was relatively small. The sensors were supplied with GPS and rugged PC for data-logging. Soil sensing was performed continuously along each tree row, with the sensors at 0.2 m height above the soil surface, to minimize the signal attenuation. The data were interpolated across the whole area using ordinary kriging (OK), which is widely used or the interpolation of soil proximal sensing data [14; 17; 19]. The OK parameters, namely lag size, number of lags, and maximum range were selected in order to minimize the estimation error.  
Six soil profiles were dug to account for the variability across the field, in terms of proximal soil sensing maps and irrigation management. The soil profiles were described following the international guidelines for soil description [60] and classified according to the Word Reference Base for Soil Resources [61]. Soil samples were collected from several genetic horizons of each soil profile. The samples were air-dried, sieved to 2.0 mm, and analysed for physical and chemical properties using standard laboratory methods. In particular, soil texture was determined by the Micromeritics Sedigraph analyser [62], total organic C (TOC) and total N (TN) were measured by dry combustion with a ThermoFlash 2000 CN soil analyser, after removal of carbonates by HCl 10%. The total equivalent CaCO\({}_{3}\) content was calculated from the difference between the total C measured by dry combustion in the untreated soil (mineral C + organic C) and in the HCl-treated soil (organic C). Soil pH was measured potentiometrically in a 1:2.5 soil-water suspension, whereas electrical conductivity was measured in a 1:2 soil-water filtered extract after 2 h shaking and overnight standing. Available water capacity (AWC, in cm cm\({}^{-1}\)) was calculated for all the soil horizons using the pedotransfer function of Saxton and Rawls [63] implemented in the software SPAW (U.S. Department of Agriculture, Washington D.C., MD, USA).