3. Methodology
Time series datasets, microwave data from Sentinel-1 and optical data
from Sentinel-2 were taken. The microwave data was splitted. Calibrate
and Deburst as a part of pre-processing. Thereafter the backscatter
parameters σ0, β0 and
γ0 were retrieved during calibration. Thereafter, the
data was geocoded using terrain correction from SRTM (Shuttle RADAR
Topography Mission) plugin. Thereafter, the data was multilooked to
generate square pixels and remove radiometric distortions.
The optical data of Sentinel-2, of the same dates as microwave data was
taken and layer stacked to put together all 13 bands as a single
imagery. Since the study area was not covered in one image tile, the
different image tiles were mosaiced together. Thereafter, the study area
of Rupnagar was clipped out from its district shape file. From the
clipped imageries, band rationing was done to derive Normalised
Differential Salinity Index (NDSI) which is an indicator of soil
salinity from optical satellite data.
Since optical data does not have an all-weather availability and
microwave data suffers from speckle noise, this study was aimed at
retrieval of salinity sensitive parameters from both the datasets and
put them together into one salinity estimation model. The model also
uses field data collected using an instrument from FieldScout Ltd, USA.
Surface Soil moisture, soil temperature and Electrical conductivity were
recorded from this instrument at surface as well as at 60 cm below the
surface in early stages of wheat crop growth (November
20th, 2019, December 27th, 2019, and
January 20th, 2020).
The SAR Backscatter coefficients, NDSI, surface soil moisture, soil
electrical conductivity (EC) and soil temperature were fed into an
Ordinary Least Squares Model. R2 statistics, F-test
and Durbin-Watson test were carried out to assess the model accuracy.
The detailed methodology flow diagram is mentioned in Figure 2.
Prior to model development, correlative plots were made to check the
sensitivities of all other parameters used in the model with the most
indicative of Soil Salinity – EC and NDSI. Also, the three backscatter
parameters were plotted for correlation with Sigma Nought
σ0 for any major variation since use of excess
parameters could lead to model overfitting.