A Carbon Monitoring System for Lithuanian Soils Utilizing Remote Sensing and XAI Techniques

Description

Overview

To safeguard natural capital of soils, in a continuously volatile landscape of reduced resources and environmental changes and pave the way for the development of evidence-based conservation recommendations for Common Agricultural Policy, it is essential to improve capacities for soil health monitoring by adopting multidimensional and integrated approaches. However, the available soil maps correspond to a not up-to date and coarse representation of the various soil properties, making their use impossible for Good Agricultural and Environmental Conditions (GAECs) monitoring in the framework of cross-compliance. This action facilitates the access to and integration of national spatial data with untapped GEOSS research-based soil data and different spaceborne sources such as Copernicus, into user's oriented applications.                                                                 
In the light of the above, we addressed the challenges of big data handling and analysis by adopting and further developing cutting edge technologies in the domain of ICT and eXplainable Artificial Intelligence (XAI).  Ηere we provide an answer to the issue of data limitation to scale, and transform into digital, the monitoring and reporting capacities from farm to regional datasets having the desired spatio-temporal representativeness and reliability. As a result, the produced product (Bare soil, SOC and clay content, SOC stocks) exhibit a high spatial resolution and can effectively discriminate changes at both intra-field and inter-field levels.

Access

The Carbon Monitoring System for Lithuanian Soils application can be found here.

Funding

The authors acknowledge the funding received by the EIFFEL project (funded by the European Union's Horizon 2020 research and innovation program under grant agreement No. 101003518).

 

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