Title | ||
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Gaining prediction accuracy in land use modeling by integrating modeled hydrologic variables |
Abstract | ||
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Land use and hydrology are interdependent, so that land use modeling could benefit from hydrologic modeling. This study aims to integrate spatial predictions of hydrologic variables as provided by a hydrologic model into a land use model for a rapidly urbanizing catchment in India. The benefits of this integration are quantified by comparing predictions of a land use model that uses a basic set of explanatory variables to a land use model that additionally uses the modeled hydrologic variables. Our results indicate that the integration of the hydrologic variables improved the model accuracy indicated by overall accuracy (+3 and + 4 percentage points (pp)), class specific user and producer accuracies (up to +8 pp) and figure of merit (+4 and + 5.3 pp) when compared with land use classifications at two points in time. Moreover, the land use patterns show that the integration of the hydrologic variables helped to avoid allocation errors. |
Year | DOI | Venue |
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2019 | 10.1016/j.envsoft.2019.02.011 | Environmental Modelling & Software |
Keywords | Field | DocType |
Land use modeling,Hydrologic modeling,Land-Use/Cover Change (LUCC),CLUE-s,India | Water resource management,Hydrological modelling,Drainage basin,Hydrology,Computer science,Percentage point,Land use | Journal |
Volume | ISSN | Citations |
115 | 1364-8152 | 0 |
PageRank | References | Authors |
0.34 | 7 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Paul D. Wagner | 1 | 16 | 3.04 |
Nicola Fohrer | 2 | 8 | 1.63 |