:: Volume 6, Issue 2 (9-2018) ::
jgit 2018, 6(2): 125-141 Back to browse issues page
The spectral behavior of trees affected by traffic pollution using filed spectroscopy
Leila Mousaei Kordshami, Mozhgan Abbasi *, Ali Jafari
Shahrekord University
Abstract:   (1756 Views)
Today, Industry and traffic can be a major contributor to the air pollution in the cities. The traditional methods for the study of air pollution are based on chemical measurements and analysis which requires time, labor along with relatively high costs. Study of spectral behavior of Plants affected by environmental stresses is one of the non-destructive methods in remote sensing science. The visible and near-infrared spectroscopy of plants technique, since it’s quick, easy to use and precise, is widely used to predict the biochemical components of plants and their changes. The aim of this study is to study the spectral reflectance behavior of leaves exposed to traffic pollution of a part of Imam Khomeini highway, Isfahan-Iran. Spectral characteristics of the leaf surface of infected species including ash, cypress and elm using spectral indices sensitive to stress and chlorophyll were studied. The results of artificial neural network to distinguish the control and polluted species using spectral indices (PRI, NDVI, Gitelson and …) shows the accuracy of 73.4%. The PLS regression model was conducted simultaneously for three species in polluted and control modes and it does not have any acceptable results. In addition, the model was conducted separately for each species; it showed acceptable results for ash trees in polluted and control modes.
Keywords: Air pollution, Filed Spectroscopy, Artificial Neural Network, Spectral Indices, Imam Khomeini Highway
Full-Text [PDF 1458 kb]   (1189 Downloads)    
Type of Study: Research | Subject: RS
Received: 2017/02/12 | Accepted: 2017/11/20 | Published: 2018/09/22



XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 6, Issue 2 (9-2018) Back to browse issues page