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https://doi.org/10.4060/cd0064...
Book . 2024 . Peer-reviewed
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The land characterization meta-language

Authors: Antonio Di Gregorio; Matieu Henry; Fatima Mushtaq; Charles Douglas O'Brien; Nicola Mosca; Chris Hill; John Latham;

The land characterization meta-language

Abstract

There is a clear relationship between land cover (LC) and land use (LU). In fact, many existing LU classifications are based on LC information and vice versa. In practice, in many instances LC and LU concepts are so closely interrelated that often the meaning of terms becomes interchangeable. The description of a portion of land includes both LC and LU information (described as the biophysical land components and the human activities that shape and/or modify them). In a modern and efficient system, one cannot substitute one for the other. However, the two are and must be well separated concepts. Therefore, an effective and functional relationship between LC and LU needs to be established formally.This publication attempts to show this relationship. The title, and characterization meta-language, is used in this paper to represent the combination of the description of the terms LC and LU. The land characterization meta-language includes both LC and LU and the bridging relationships between them. The land characterization meta-language schema follows the premise that an effective and functional LC and LU relationship can be built only with a change of paradigm creating a unified modelling language schema based on the three-way relationship between the biophysical cover, the activities being performed and the functions to which the land is devoted at a point in time.

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Italy
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Keywords

land information systems, land cover, land use, land classification, classification systems, models, biophysical models, standards

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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