SCR predicition

This module performs Signal-to-Clutter ratio (SCR) prediction over candidate site for corner reflector installation.

First, prepare coreg stacks using SNAP processing.

SCR prediction is done in a crop around specified geodetic coordinates. It is driven by input in planning.json:

{
  "id": "PEM2",
  "longitude": 18.340544,
  "latitude": 48.630174,
  "elevation": 250.952,
  "cropSize": 200,
  "RCS": 30,
  "stackDir": "/data/CR_Partizanske/DSC124/",
  "oversamplingFactor": 16,
  "outTiff": "/data/CR_Partizanske/SCR/SCR_DSC124.tiff"
}

Note

cropSize is radius in metres. RCS is expected reflector’s Radar Cross Section in [dBm2]. Expected RCS of chosen reflector type can be simulated using tools in the gecoris.crUtils module.

SCR simulation is performed by:

python gecoris/scrSimul.py planning.json

Result is a GeoTIFF with predicted SCR over your AOI.

Example output

_images/predictedSCR_example.png

Maps of predicted SCR, given 1 m inner-leg-length square trihedral reflector (30 dBm2 RCS), computed on the 1-year of Sentinel-1 time series over specific landslide area in Slovakia.