Name
Abstract | ||
|---|---|---|
Land use change (LUC) model is fundamental in decision making process for regional sustainable development. It is practically important to analyze LUC in rapidly urbanizing region, such as Panyu District of Guangzhou, China, where a fast economy development makes it necessary to study the rule of urban land use change. Taking time-spatial land use change as the key point, a case study is carried out to analyze the land use change process, based on the land use data of 1996, 2005, and 2009. The transformation matrix of land use is calculated to show the spatial pattern and reveal the spatial change process of land use between 1996 and 2009. A multi-logistic regression model which takes five dependent factors is adopted to analyze the land use change process and predict the land use change tendency and proven to be feasible and efficient. This study may provide a guide to future research in land use change. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GEOINFORMATICS.2010.5567581 | Geoinformatics |
Keywords | Field | DocType |
terrain mapping,urban land use change,multilogistic regression model,economy development,transformation matrix,multi-logistic regression model,decision making,ad 2005,china,sustainable development,panyu district,land use data,spatial pattern,urban land use,time-spatial land use change,regional sustainable development,ad 2009,ad 1996,land use change model,vegetation mapping,variation change,spatial change process,decision making process,guangzhou,land use change,mathematical model,logistic regression model,land use,predictive models,construction industry | Common spatial pattern,Data mining,Environmental resource management,Computer science,Regression analysis,China,Land use, land-use change and forestry,Construction industry,Sustainable development,Decision-making,Land use | Conference |
ISBN | Citations | PageRank |
978-1-4244-7301-4 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lu Wang | 1 | 1 | 0.71 |
| Liting Fang | 2 | 0 | 0.34 |
| Yueming Hu | 3 | 17 | 7.92 |
| Xiaofei Hu | 4 | 20 | 3.06 |
| Lun Wu | 5 | 26 | 6.94 |
| Yuan Tian | 6 | 3 | 5.43 |