Name
Abstract | ||
|---|---|---|
The green space information extraction is significant for study on urban remote sensing because of its ecological and socioeconomic functions. And with the traditional methods the precision is very low, we educe decision tree of extraction to raise the accuracy rate. We take Shanghai as a case study area from QUICKBIRD imagery, analyzing spectral characteristics of 4 multi-spectral bands. And we also introduce accessorial information vegetation index (NDVI) to get rid of other land use types. The final result suggests that the extraction method of decision tree can accurately get the green space information. The accurate rate is over 95%. It can be widely used in the field of urban vegetation remote sensing analyses. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/GEOINFORMATICS.2010.5567526 | Geoinformatics |
Keywords | Field | DocType |
land use type,urban green space extraction,multispectral band image,ndvi,china,quickbird imagery,urban green space information extraction,spectral characteristics,feature extraction,geophysical image processing,accessorial information vegetation index,ecological function,socioeconomic function,vegetation mapping,shanghai,urban remote sensing,decision tree,decision trees,vegetation,information extraction,green space,land use,indexes,remote sensing | Decision tree,Data mining,Vegetation,Computer science,Vegetation Index,Remote sensing,Vegetation remote sensing,Feature extraction,Normalized Difference Vegetation Index,Information extraction,Land use | Conference |
ISBN | Citations | PageRank |
978-1-4244-7301-4 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chenglei Shen | 1 | 1 | 1.74 |
| Manchun Li | 2 | 211 | 45.40 |
| Feixue Li | 3 | 1 | 5.48 |
| Jieli Chen | 4 | 1 | 1.74 |
| Yili Lu | 5 | 0 | 0.34 |