Abstract
To quickly obtain the information of urban vegetation stressed level is of great significance in maintaining urban vegetation health and improving urban eco-environment. Based on the analysis of stressed vegetations physiological and spectral characters, and by using Hyperion hyperspectral data, 14 hyperspectral vegetation indices related to stress were calculated, and a classifier of urban vegetation stressed level was developed based on this calculation and BP Neural network. The application of this classifier in identifying the vegetation stressed level in a case study area of Guangzhou City showed that the vegetations in commercial and residential districts were apparently experienced higher stress than those in suburban regions, and the stressed level showed a ringy distribution around large pieces of greenbelts. This classifier was able to quickly and accurately identify the vegetation stressed level, and thus, could be used as an effective tool in monitoring urban vegetation stressed condition.
| Original language | English |
|---|---|
| Pages (from-to) | 1286-1292 |
| Number of pages | 7 |
| Journal | Chinese Journal of Applied Ecology |
| Volume | 18 |
| Issue number | 6 |
| State | Published - Jun 2007 |
| Externally published | Yes |
Keywords
- BP neural network
- Hyperion
- Hyperspectrum
- Stressed level of urban vegetation