Updated October 1998
by Louisa J.M. Jansen (FAO/AGLS) and Antonio Di Gregorio (GCP/RAF/287/ITA Africover East Africa Project, SDRN). From GCTE-LUCC: The Earth's Changing Land, Open Science Conference, 14-18 March, Barcelona, Spain
Land cover changes take two forms: conversion from one land cover category to another (e.g. from forest to grassland) and modification within one category (from closed forest to open forest). The broader and fewer the categories used to describe land cover, the fewer the instances of conversion from one to another. Conversion is reasonably well-documented in land cover change studies; modification, however, is less well studied and at global scale often ignored. The ecological consequences, though, are as important.
Classification systems are tools for change detection when they offer the capability to describe classes through a set of well-defined independent diagnostic criteria (classifiers) that allow to build up these classes, rather than using for the traditional system using descriptive class names.
If land cover is defined as the observed (bio) physical cover on the earth's surface than land use could be defined as being characterized by the arrangements, activities and inputs people undertake in a certain land cover type to produce, change or maintain it. As such the link between land cover and land use focuses on the human interventions on the land and land use change detection becomes immediately related to the role of humans in the environment.
FAO developed the Land Cover Classification System, a comprehensive parametric classification that can accommodate any land cover anywhere in the world. This system uses the classifier approach that also allows correlation with other existing classifications and legends. The advantages of the approach adopted is that change detection becomes possible at the level of conversion of a class, and that modification within a certain class type becomes immediately identifiable by a difference in classifier, or through the use of additional classifiers. The more classifiers used at the beginning of the monitoring process, the greater the detail of the defined class and the greater the possibility to detect changes in any of the used parameters.