INTERREG-SUDOE Openpas Project: Evaluation of pasture conservation using open science, sensors and machine learning.

Community interest grassland habitats play a fundamental role in shaping the landscape and maintaining biodiversity in the Sudoe area. This type of habitat is not only crucial for flora and fauna diversity but also provides essential ecosystem services, acting as significant carbon sinks, helping to prevent soil erosion, and contributing to the regulation of the water cycle. Furthermore, its importance is linked to key economic activities in rural areas, such as traditional grazing, extensive livestock farming, and other high-value-value agricultural activities.

Despite their legal protection and their classification as Habitats of Community Interest under the 1992 Habitats Directive, the conservation status of many of these grassland habitats is not entirely favorable, showing degradation compared to previous periods. Among other reasons, the effects of climate change (droughts, alterations in rainfall and temperature patterns), pollution, changes in land use, and the abandonment of traditional activities that shaped this ecosystem, such as grazing, explain this trend.

Developing smarter, more accurate, and more affordable assessment systems is a necessary step to improve the conservation status of grasslands, enabling proactive and comprehensive decision-making. Currently, habitat conservation status assessments are typically conducted through field sampling, which can be invasive in highly fragile contexts, difficult to carry out in remote areas, and costly.

In this context, the OpenPAS project aims to improve the methodology for assessing the conservation status of grassland habitats of community interest by developing a tool based on remote sensing, image processing, and machine learning. This will allow natural area managers and other users to receive highly accurate and relevant information to support their decision-making.