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GENERATING FARM DESCRIPTIONS IN A WATERSHED FROM INCOMPLETE DATA USING SIMULATED ANNEALING 1
Author(s) -
Stone Nicholas D.,
Cline Ben E.,
Pease James
Publication year - 2002
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2002.tb04322.x
Subject(s) - watershed , simulated annealing , computer science , heuristic , spatial analysis , environmental science , agriculture , hydrology (agriculture) , agricultural engineering , remote sensing , geography , algorithm , artificial intelligence , engineering , machine learning , geotechnical engineering , archaeology
A fundamental problem faced in developing spatially explicit, simulation‐based analyses of watershed management and policy options is determining the distribution and spatial location of agricultural resources within a watershed based on incomplete information. This paper describes the use of simulated annealing, a heuristic scheduling process, to generate an assignment of all livestock and agricultural fields in a watershed to hypothetical farms such that the combined distribution of farm types, livestock, and farmland within the watershed is a reasonable representation of watershed‐level data. Compared to a manual method using GIS‐based analysis and data from aerial photography, the heuristic method was more likely to generate realistic spatial characterizations of the distribution of agricultural resources and practices in a watershed. Also compared to the manual method, the heuristic process was considerably more efficient and could more easily accommodate multiple criteria and modifications to those criteria.