The Land Cover Classification System (LCCS) was developed by FAO to provide a consistent framework for the classification and mapping of land cover. Its main objectives were to overcome the rigidity of a-priori land cover classifications, which in many practical situations do not allow easy assignment into one of the pre-defined classes and are therefore not very suitable for mapping. LCCS instead opted for an approach based on two main phases. The first phase is an initial ‘Dichotomous Phase’, in which eight major land cover types are defined: (1) Cultivated and Managed Terrestrial Areas, (2) Natural and Semi-Natural Terrestrial Vegetation, (3) Cultivated Aquatic or Regularly Flooded Areas, (4) Natural and Semi-Natural Aquatic or Regularly Flooded Vegetation, (5) Artificial Surfaces and Associated Areas, (6) Bare Areas, (7) Artificial Waterbodies, Snow and Ice, and (8) Natural Waterbodies, Snow and Ice. The Dichotomous Phase is followed by a subsequent ‘Modular-Hierarchical Phase’, in which land cover classes are created by the combination of sets of pre-defined classifiers, which are different for each of the eight major land cover types. For example, common classifiers used for (semi-) natural terrestrial vegetation types are Life Form, Cover, Height, Macropattern. For aquatic or regularly flooded natural and semi-natural vegetation, water seasonality is an indispensable classifier. LCCS offers several advantages from a conceptual point of view. LCCS is a real a priori classification system in the sense that, for the classifiers considered, it covers all their possible combinations. The classification is also hierarchical and the more classifiers used, the greater the detail of the defined land cover class. The classes derived from the proposed classification system are all unique and unambiguous, due to the internal consistency and systematic description of the classes. LCCS is designed to map at a variety of scales, from small to large. From a practical viewpoint LCCS offers several advantages: (1) easy incorporation into GIS and databases, (2) allows flexible response to information available in a given area, project budget and time constraints, (3) unlinks the field data collection from the interpretation process.