Name
Title | ||
|---|---|---|
Importance of spatially distributed hydrologic variables for land use change modeling. |
Abstract | ||
|---|---|---|
Land use changes have a pronounced impact on hydrology. Vice versa, hydrologic changes affect land use patterns. The objective of this study is to test whether hydrologic variables can explain land use change. We employ a set of spatially distributed hydrologic variables and compare it against a set of commonly used explanatory variables for land use change. The explanatory power of these variables is assessed by using a logistic regression approach to model the spatial distribution of land use changes in a meso-scale Indian catchment. When hydrologic variables are additionally included, the accuracies of the logistic regression models improve, which is indicated by a change in the relative operating characteristic statistic (ROC) by up to 11%. This is mostly due to the complementarity of the two datasets that is reflected in the use of 44% commonly used variables and 56% hydrologic variables in the best models for land use change. Display Omitted Hydrologic patterns can contribute towards explaining land use change.Hydrologic variables complement commonly used explanatory variables for land use change.Modeled hydrologic variables improve land use change modeling. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.envsoft.2016.06.005 | Environmental Modelling and Software |
Keywords | Field | DocType |
Land use modeling,Land-Use/Cover Change (LUCC),Logistic regression,Hydrologic modeling,India | Complementarity (molecular biology),Hydrological modelling,Statistic,Drainage basin,Computer science,Hydrology,Land use, land-use change and forestry,Explanatory power,Logistic regression,Land use | Journal |
Volume | Issue | ISSN |
83 | C | 1364-8152 |
Citations | PageRank | References |
4 | 0.64 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul D. Wagner | 1 | 16 | 3.04 |
| Björn Waske | 2 | 435 | 24.75 |