Abstract

Abstract. Carbon farming, a crucial strategy in mitigating climate change and promoting sustainable agriculture, requires precise monitoring to assess its effectiveness. This study explores the transformative potential of remote sensing data, with a focus on the fusion of Multispectral and Synthetic Aperture Radar satellite data, to enhance the precision and efficiency of carbon farming monitoring. Our research addresses the fundamental question: How can remote sensing data optimize the monitoring of carbon farming practices? This question drives our investigation into the practical applications of remote sensing technology in the context of carbon farming. In this article, the research is carried out in Lithuania, which is often covered with clouds or their shadows, so the application of various satellite images becomes even more meaningful. The study shows that the use of SAR image fusion for the identification of permanent meadows is appropriate and meaningful. The use of MSI image fusion for the identification of intermediate crops and stubble is also appropriate, but more research is needed that focuses on distinguishing these practices from other spectrally very similar practices.

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