1. KappaZeta in the Living Planet Symposium
It is 23rd of May 2022 and we are glad to share that we are present at European Space Agency Living Planet Symposium in Bonn!
On Friday 27th of May, our CEO Kaupo Voormansik will give an oral presentation on “High quality food for AI – Sentinel-1 analysis-ready data (ARD) with interferometric coherence”. The presentation will focus on freshly launched KappaOne service. The SAR expertise of KZ helps to take full advantage of the interferometric and polarimetric data content of Sentinel-1. And for the end-user, it means calibrated and noise corrected imagery products with the highest possible spatial resolution using advanced speckle suppression methods.
On Tuesday our EO analyst Jelizaveta Vabistsevits will give a session on “KappaOne fresh Sentinel-1 data layers’ use case examples for the subsidy checks in Common Agricultural Policy”. She will tell you about KappaOne and its use case for the CAP subsidy checks through a hands-on experience!
On Friday there will also be a poster presentation on “AI-based Cloud Mask Processor for Sentinel-2” by Olga Wold, our Geospatial Data Quality Specialist. This presentation will describe the KappaMask model details and its progress on going global!
See you at the Living Planet Symposium 2022!
Olga Wold, geospatial data quality specialist
2. Crop Damage Detection
In KappaZeta we are among other things investigating the possibilities to use remotely sensed time-series data to detect crop damage on agricultural parcels.
The initial stage of the research was carried out with the cooperation of local farmers, who provided information about the general condition of agricultural parcels and granted access to the croplands for field surveying. During the in-person visits that took place early in July 2021, a visual assessment of various winter and spring vegetation types was performed and georeferenced images from across the fields were taken. Extra attention was paid to the difference between crop condition within damaged and healthy areas.
The results of the preliminary analysis on a test subset of agricultural parcels vary. The number of parcels in the current stage of analysis was quite limited and it caused several issues. Nevertheless, using simple unsupervised classification techniques it is possible to obtain a spatial representation of the damaged areas through the analysis of specific features of winter rapeseed at particular stages of its development.
At the next stage of the analysis, the work will be continued in the scope of supervised classification techniques combined with individual approaches to various agricultural crop types.
Anton Kostiukhin, software developer
