Sentinel-1 to NDVI for Agricultural Fields Using Hyperlocal Dynamic Machine Learning Approach
Ran Pelta, P.h.D., Remote sensing and data scientist
May 2022
Ran Pelta’s research on how to generate NDVI from SAR (radar) satellite images is now published online in “Remote Sensing” journal!
The study suggests a new method for converting Sentinel-1 (SAR) images to NDVIs for agricultural fields by utilizing a hyperlocal machine learning approach.
The model was tested on 548 commercial fields from 18 countries with 28 crop types and was based on 6,880 paired NDVI–SAR images.
The outcome of this study aspires to a persistent seamless stream of NDVI values, regardless of the atmospheric conditions and clouds, and it can assist in providing better, more accurate irrigation decisions.
Read the full study here
Manna, an Irrigation Intelligence leader, provides growers around the world with the actionable information they need to make better-informed and more confident irrigation decisions. Its sensor-free, software-only approach leverages high-resolution, frequently refreshed satellite data and hyper-local weather information to deliver highly affordable and accessible solutions for site-specific irrigation recommendations.
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