Would it be possible to to implement a system with a combination of satellite imagery and ground sensors? The ground sensors can provide real-time moisture information and can this calibrate the information from Sentinel-1 SAR ? Eventually such a system can then reduce the number of sensors needed in the field too.
This is an agricultural application, so vegetation also needs to be considered. However, some sensors can be placed in a region which are not covered by vegetation.
I see plenty of discussion topics about soil moisture estimation using Sentinel-1 data and seeing that it is not straight forward. However, if you can provide some insights on an approach to this problem, it would be of great help!
I am only starting to learn about estimating soil moisture with SAR data, but I am working with some other scientists that are experts. The difficult step is separating the effects of vegetation on the SAR backscatter amplitude from the effects of soil moisture. You might want to look at the papers on the NASA Soil Moisture Active-Passive (SMAP) satellite data analysis. They are using Sentinel-1 SAR as one of their data inputs since about two or three years ago, combining it with the passive radiometer data on the SMAP satellite.
Thank you for the pointers @EJFielding. I am currently looking into literature that I found in the forum and outside to include the NDVI as well into the model for calculation of soil moisture. I will update this post if I have some results interesting to share.
@hriston_bg: This is a great find for me. Thanks for pointing me to this tool. From the first look, the two water related products seems quite useful already. I will create an account and look at these products.
Have you also seen this one perhaps? Any thoughts?
@kiranjayaraj , i belive that what you are looking for is already being done by this company https://www.refarmo.com/.
However i would strongly argue on why do you need the local sensors instead of trying to replace them.