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Hi,

I am interested in transforming the RGB bands of an S-1 image to better visualize the oil spills. For this I have found the following script that allows the ORM index to be visualized in the EO browser at https://custom-scripts.sentinel-hub.com /sentinel-1/orm_index/#.

Contains this:


//Oil slicks and Red tide monitoring  

//By TIZNEGAR Startup Co, www.tiznegar.com

//Dataset:Sentinel-1 AWS-IW-VVVH



var ORM = Math.log(0.01/(0.01+VV*2)); 



if (ORM < [ 0] &&  VV< [ 0.018]&&  VH< [ 0.00126]) { 

    

   return colorBlend   

    (ORM,	            

         [-1.6, -1.4, -1.2, -1, -.8, -.6, -.4, -.2, 0], 

        [     

   

     [0,0,.1 ],

     [0,0,.4 ],

     [0,0,.8],

     [1,0,.5],

     [1,0,0],

     [1,.5,.2],

     [1,.8,.2],

     [1,1,.4],

     [.5,.8,.3],

           



      ]);

}

else {

 return [2.5*VV,2.5*VV,2.5*VV]

}

Captura

If I want to use this code in python using the original VV and VH images from S-1. Between what values are the VV and VH that are evaluated through the EO browser (the original images are of the order of 0-6000) and how could I implement it in python using the original polarizations?


Thanks for the help

Hi,

EO Browser processes the original Sentinel-1 GRD data. The only conditional statement in the script is that it returns visualisation if ORM < [0] && VV < [0.018] && VH < [0.00126] and for other cases it returns [2.5*VV,2.5*VV,2.5*VV].

As you mentioned you’re using python, please have a look at the Sentinel Hub python package, which is an official python interface of our services. I would also suggest going through our technical documentation and starting with Processing API. You could also go through the Processing API webinar, which should give you a general introduction of what our services are about.

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