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Matching spatial databases and quantitative models in land resource assessment
Author(s) -
Burrough P.A.
Publication year - 1989
Publication title -
soil use and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.709
H-Index - 81
eISSN - 1475-2743
pISSN - 0266-0032
DOI - 10.1111/j.1475-2743.1989.tb00753.x
Subject(s) - computer science , land use , matching (statistics) , land use planning , land information system , resource (disambiguation) , linkage (software) , process (computing) , geographic information system , spatial analysis , land management , order (exchange) , data mining , database , data science , environmental resource management , geography , remote sensing , environmental science , statistics , business , mathematics , computer network , biochemistry , civil engineering , chemistry , finance , engineering , gene , operating system
. Good land management needs information about land resources and the processes taking place in the landscape. In practical land evaluation this information is often expressed in terms of land qualities. The original survey data are stored in geographical information systems where they can be used to estimate the values of appropriate land qualities. Land qualities are complex attributes of land used in planning that may be derived from the original attributes through empirical threshold or regression models, or from process‐based deterministic or stochastic simulation models. In order to improve estimates of the distribution of land qualities in space and time, and hence to improve planning decisions, the models require data with a much better spatial resolution than is usually available. The problems and dangers associated with the ad hoc linkage of simulation models and GIS are discussed. Particular attention needs to be paid to the problems of error propagation and costs and benefits when using models.