Dear Ismail Mondal

Use both (Multispectral and Microwave).

Please check these out:

Dear Ismail Mondal

Use both (Multispectral and Microwave).

Please check these out:

@Ismail Mondal

maybe the more important question is what data do you have access to?

what is data available for you.

you can used both techniques and compare between them

Thank you so much for your valuable document

@ Kamal Azizi

Thank You so much, Sir, @ Paweł Bronisław Dąbek

I am using both data Sentinel 1 and Multi spectral Landsat OLI

SAR data good accuracy R square value

Thank You, @ Aysar Jameel Abdalkadhum

I am using both data Sentinel 1 and Multispectral Landsat OLI

SAR data good accuracy R square value

Ismail Mondal

what do you want to evaluate exactly?

biomass increase through DSM differential analysis?

or rather the degree / state of vegetation?

do you have field measurements to calibrate microwave data?

In our article (DOI: 10.4336/2016.pfb.36.88.1134), we tested optical imagery from two different satellite sensors to estimate forest timber volume. The optical data worked relativelly well up to a saturation point (high LAI)-a classical problem, that is, the continued increase in biomass not always brings an increase/decrease in the reflected radiance measured by the orbital sensors.

Yes sir

Field data and Sentinel 1 data evaluate to create a model,

Finally, SAR data result very well

Bonjour M. Mondial,

Je veux lire votre texte. Je n'arrive pas à télécharger.

You may want to look at:

Preprint A New Model of “Color” Vision for Remote Sensing

Thank Sir for your valuable information

Mr. Ismail, that depends on what are you aiming in your study.

OK sir

Thank You

Places with predominant grassy vegetation and low to medium amount of biomass (LAI