From Descriptors to Decisions: Structuring the Libyan National Land Cover Reference System with Land Cover Meta Language

The accurate representation of land cover is fundamental to sustainable land management, environmental monitoring, and spatial policy development. However, many national systems lack semantic interoperability, flexibility, and are often developed for narrowly focused purposes. This study presents an ontology-based approach to developing the Libyan National Land Cover Reference System (LLCRS) using the Land Cover Meta Language (LCML), defined in ISO 19144-2. The aim is to shift from fixed class labels to a structured set of observable descriptors—such as cover percentage, phenology, height, and spatial pattern—allowing for more precise, scalable, and interoperable representations of land cover. Using Libyan national classification schemes as a foundation, land cover classes were translated into LCML descriptors through iterative modeling and validation, supported by the Land Characterization System (LCHS) software. The resulting reference system offers a standardized, modular structure that facilitates crosswalks between national, regional, and global classification frameworks. It enhances consistency across mapping efforts and supports integration into national land monitoring workflows. The framework is tailored to Libya’s arid context but offers potential for adaptation and reusability in other arid/semi-arid regions, such as those in the Sahel or Arabian Peninsula, by adjusting descriptors to local environmental conditions while maintaining biophysical focus and excluding socio-economic or land-use dynamics.