Sentinel-2 Satellite Imagery Application to Monitor Soil Salinity and Calcium Carbonate Contents in Agricultural Fields

The estuary tides affect groundwater dynamics;these areas are susceptible to waterlogging and salinity issues.A study was conducted on two fields with a total area of 60 hectares under a center pivot irrigation system that works with solar energy and belong to a commercial farm located in Northern Sudan.To monitor soil salinity and calcium carbonate in the area and stop future degradation of soil resources,easy,non-intrusive,and practical procedures are required.The objective of this study was to use remote sensing-determined Sentinel-2 satellite imagery using various soil indices to develop prediction models for the estimation of soil electrical conductivity(EC)and soil calcium carbonate(CaCO_(3)).Geo-referenced soil samples were collected from 72 locations and analyzed in the laboratory for soil EC and CaCO_(3).The electrical conductivity of the soil saturation paste extract was represented by average values in soil dataset samples from two fields collected from the topsoil layer(0 to 15 cm)characteristic of the local salinity gradient.The various soil indices,used in this study,were calculated from the Sentinel-2 satellite imagery.The prediction was determined using the root mean square error(RMSE)and cross validation was done using coefficient of determination.The results of regression analysis showed linear relationships with significant correlation between the EC analyzed in laboratory and the salinity index-2“SI2”(Model-1:R^(2)=0.59,p=0.00019 and root mean square error(RMSE=1.32%)and the bare soil index“BSI”(Model-2:R^(2)=0.63,p=0.00012 and RMSE=6.42%).Model-1 demonstrated the best model for predicting soil EC,and validation R^(2)and RMSE values of 0.48%and 1.32%,respectively.The regression analysis results for soil CaCO_(3)determination showed linear relationships with data obtained in laboratory and the bare soil index“BSI”(Model-3:R^(2)=0.45,p=0.00021 and RMSE=1.29%)and the bare soil index“BSI”&Normalized difference salinity index“NDSI”(Model-4:R^(2)=0.53,p=0.00015 and RMSE=1.55%).The validation confirmed the Model-3 results for prediction of soil CaCO_(3)with R^(2)and RMSE values of 0.478%and 1.29%,respectively.Future soil monitoring programs might consider the use of remote sensing data for assessing soil salinity and CaCO_(3)using soil indices results generated from satellite image(i.e.,Sentinel-2).

Impacts of center pivot irrigation system uniformity on growth of potato crop and residual soil nitrogen

Maintaining the homogeneity of soil nitrogen(N)and plant vigor across agricultural fields is a major concern for farmers and agricultural scheme planners,particularly fields that are irrigated through pressurized systems,such as center pivots.Therefore,this study was carried out on a 30 hm2 potato field located 650 km south of Riyadh,the capital city of the Kingdom of Saudi Arabia,to investigate the impacts of the center pivot irrigation distribution uniformity on the crop development and the spatial distribution of residual soil N.Irrigation performance test was designed to investigate water application rate and distribution uniformities.The overall water application uniformity coefficients(Cu),determined through Christiansen(Cud)and Heerman(CuH)methods,were determined at 81.29%and 80.64%,respectively.However,the overall water distribution uniformity(Du)was determined at 70%.A considerable variability in the distribution uniformity of irrigation water was observed across the experimental field(a Du value of 67%over the medium spans compared to a Du value of 88%over the inner spans).Results of this study showed a linear correlation between the irrigation water distribution uniformity and the soil N(R^(2)=0.88).On the other hand,the vegetation cover distribution,indicated by the Cumulative Normalized Difference Vegetation Index(CNDVI),was not found to be much responsive to the irrigation distribution uniformity(R^(2)=0.11).A time series of successive NDVI maps extracted throughout the potato crop growth stages showed a consistent trend in the distribution of NDVI across the field,with R2 values that ranged between 0.25-0.73.

Sub-pixel analysis to enhance the accuracy of evapotranspiration determined using MODIS images

A study was carried out to estimate the actual evapotranspiration(ET)over a 1074 km2 of the humid area of Perak State(Malaysia),where water and evaporation cycle deeply influences the climate,natural resources and human living aspects.Images from both Terra and Aqua platforms of the Moderate Resolution Imaging Spectroradiometer(MODIS)sensor were used for ET estimation by employing the Surface Energy Balance Algorithm for Land(SEBAL)model.As a part of the accuracy assessment process,in-situ measurements on soil temperature and reference ET(ET0)were recorded at the time of satellite overpass.In order to enhance the accuracy of the generated ET maps,MODIS images were subjected to sub-pixel analysis by assigning weights for different land surface cover(urban,agriculture and multi-surface areas)reflections.The weighting process was achieved by integrating ET from pure pixels with the respective site-specific ET0 of each land cover.The enhanced SEBAL model estimated ET exhibited a good correlation with the in-situ measured Penman-Montieth ET0,with R2 values for the Aqua and the Terra platforms of 0.67 and 0.73,respectively.However,the correlation of the non-enhanced ET maps resulted in R2 values of 0.61 and 0.68 for the Aqua and the Terra platforms,respectively.Hence,the results of this study revealed the feasibility of employing the sub-pixel analysis method for an accurate estimation of ET over large areas.

Determining soil organic carbon concentration in agricultural fields using a handheld spectroradiometer:Implication for soil fertility measurement

The soil organic carbon(SOC)plays a vital role in plant growth and development,and therefore is considered as one of the most important indicators of soil quality.This study was carried out in the central region of Saudi Arabia to explore the potential of spectroscopy in determining the SOC concentration in low-fertility soils.Spectral reflectance data were collected,under the controlled laboratory conditions on 39 air-dried 2.0 mm sieved soil samples,using a handheld spectroradiometer of a wavelength range between 350 nm and 2500 nm in the direct contact probe mode.The concentration of the SOC was determined using the Walkley and Black(W&B)and the UV-VIS spectrophotometric methods.The increase in the concentration of SOC was associated with a decrease in the corresponding spectral reflectance.Regression analysis showed linear relationships with high significant correlation between the spectral reflectance and the SOC measured by both the UV-VIS(Model-1:R^(2)=0.46,p=0.00015 and RMSE=6.6 g/kg)and the W&B(Model-2:R^(2)=0.48,p=8.92E-05 and RMSE=2.8 g/kg)methods.For these models,two wavebands with wavelengths of 2167 nm(Model-1)and 1359 nm(Model-2)were identified as the most sensitive bands to the SOC concentration.The cross-validation confirmed the validity of Model-1 with R^(2),p and RMSE values of 0.50,0.0099 and 6.6 g/kg,respectively.The validation results of the Model-2 showed values of R^(2),p and RMSE of 0.72,0.00023 and 4.0 g/kg,respectively.Results of this study revealed the possibility and the potential of using the spectral reflectance technique in predicting the concentration of SOC.