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The definition of land cover is fundamental, because in many existing classifications and legends it is confused with land use. It is defined as:

Land cover is the observed (bio)physical cover on the earth's surface.

When considering land cover in a very pure and strict sense it should be confined to describe vegetation and man-made features. Consequently, areas where the surface consists of bare rock or bare soil are describing land itself rather than land cover. Also, it is disputable whether water surfaces are real land cover. However, in practise, the scientific community usually describes those aspects under the term land cover.

Land use is characterized by the arrangements, activities and inputs people undertake in a certain land cover type to produce, change or maintain it. Definition of land use in this way establishes a direct link between land cover and the actions of people in their environment.

The following examples are a further illustration of the above definitions:


Classification is an abstract representation of the situation in the field using well-defined diagnostic criteria: the classifiers (Figures 1 and 2). Sokal (1974) defined it as: "the ordering or arrangement of objects into groups or sets on the basis of their relationships." A classification describes the systematic framework with the names of the classes and the criteria used to distinguish them, and the relation between classes. Classification thus necessarily involves definition of class boundaries that should be clear, precise, possibly quantitative, and based upon objective criteria.

A classification should therefore be:

A legend is the application of a classification in a specific area using a defined mapping scale and specific data set (Figure 3). Therefore a legend may contain only a proportion, or sub-set, of all possible classes of the classification. Thus, a legend is:

Abstract presentation of a classification consisting of a continuum with two gradients: circles and triangles in red and white representing the concrete situation in the field - Figure 2 - (From Kuechler and Zonneveld, 1988).

Concrete situation in the field in a particular area (From Kuechler and Zonneveld, 1988).

Legend as application of a classification in a particular area.


Classification systems come in two basic formats, hierarchical and non-hierarchical. Most systems are hierarchically structured because such a classification offers more consistency owing to its ability to accommodate different levels of information, starting with structured broad-level classes, which allow further systematic subdivision into more detailed sub-classes. At each level the defined classes are mutually exclusive. At the higher levels of the classification system few diagnostic criteria are used, whereas at the lower levels the number of diagnostic criteria increases. Criteria used at one level of the classification should not be repeated at another, i.e., lower, level.


Classification can be done in two ways, that is either a priori or a posteriori (Figure 4). In an a priori classification system the classes are abstractions of the types actually occurring. The approach is based upon definition of classes before any data collection actually takes place. This means that all possible combinations of diagnostic criteria must be dealt with beforehand in the classification. This method is used extensively in plant taxonomy and soil science (e.g., The Revised Legend of the Soil Map of the World (FAO, 1988) and the USDA Soil Taxonomy (United States Soil Conservation Service, 1975)). The main advantage is that classes are standardized independent of the area and the means used. The disadvantage, however, is that this method is rigid, as some of the field samples may not be easily assignable to one of the pre-defined classes.

A posteriori classification differs fundamentally by its direct approach and its freedom from preconceived notions. The approach is based upon definition of classes after clustering similarity or dissimilarity of the field samples collected. The Braun-Blanquet method, used in vegetation science (this is a floristic classification approach using the total species combination to cluster samples in sociological groups (Kuechler and Zonneveld, 1988)), is an example of such an approach. The advantage of this type of classification is its flexibility and adaptability compared to the implicit rigidity of the a priori classification. The a posteriori approach implies a minimum of generalization. This type of classification better fits the collected field observations in a specific area. At the same time, however, because an a posteriori classification depends on the specific area described and is adapted to local conditions, it is unable to define standardized classes. Clustering of samples to define the classes can only be done after data collection, and the relevance of certain criteria in a certain area may be limited when used elsewhere or in ecologically quite different regions.

Example of an a priori (above) and a posteriori (below) classification related to a concrete situation in the field (adapted from Kuechler and Zonneveld, 1988).

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