Abstract
This study compares land suitability index (LSI) maps created using a geographic information system (GIS) with frequency ratio (FR), analytical hierarchy process (AHP), logistic regression (LR), and artificial neural network (ANN) approaches to forecasting urban land-use changes. Various social, political, topographic, and geographic factors were used as predictors of land-use change, including elevation, slope, aspect, distance from roads and urban areas, road ratio, land use, environmental score, and legal restrictions. Then, LSI maps were created using FR, AHP, LR, and ANN approaches, and significance and correlation were examined among the models using relative operating characteristic (ROC), overall accuracy, and kappa analyses. The ROC analyses gave results of 0.940, 0.937, 0.922, and 0.891 for the LR, FR, AHP, and ANN LSI maps, respectively. The highest correlation was found between the LR and AHP LSI maps (0.816911), and the lowest correlation was between the ANN and FR LSI maps (0.759701). The ANN approach produced the highest overall accuracy at 92.3%, followed by 91.74% for FR, 89.12% for AHP, and 88.93% for LR. In the kappa analysis, the highest K̂ statistic was 45.38% for FR, followed by 40.84% for ANN, 30 representing the city area, the ANN method had a relatively high value of 71.71%, and the FR, LR, and AHP methods had similar accuracies of 57.68, 55.05, and 54.31%, respectively. These results indicate that the FR, AHP, LR, and ANN approaches produced similar LSI maps for Korea.
Original language | English |
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Pages (from-to) | 104-114 |
Number of pages | 11 |
Journal | Landscape and Urban Planning |
Volume | 99 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2011 Feb 28 |
Bibliographical note
Funding Information:This research was financially supported by Korea Ministry of Environment and Korea Environment Institute.
Keywords
- Analytical hierarchy process
- Artificial neural network
- Frequency ratio
- Geographic information system
- Land suitability index map
- Logistic regression
ASJC Scopus subject areas
- Ecology
- Nature and Landscape Conservation
- Management, Monitoring, Policy and Law