摘要：Persian oak (Quercus Brantii Lindl) is the most abundant tree species in Zagros mountain range that is affected by western dust storms and harsh droughts in recent years. The lack of spectral-temporal information about these trees has caused limitations on the usage of remote sensing images to make a synoptic estimation of damages caused by dust storms and drought. The objective of this research is to analyse the spectral-temporal behaviour of Persian oak under the stress of water deficiency and dust storms. The aim is to improve the competitive abilities of experts on modelling the stress of water deficiency and dust storms on trees using remote sensing images. For the purpose of this experimental investigation, a greenhouse laboratory has been built. Analysis of the experiments was carried out using 54 two-year-old oak tree seedlings; Fieldspec-3-ADD; and wind tunnel at the greenhouse of the faculty of agriculture of the Tarbiat Modares University in 2016. Results show that the water stress could be modelled much better using geometrical indices extracted from continuum removed spectrum. Area and the depth were best indices. Water stress has been modelled better that dust stress.
其他摘要：Persian oak ( Quercus Brantii Lindl) is the most abundant tree species in Zagros mountain range that is affected by western dust storms and harsh droughts in recent years. The lack of spectral-temporal information about these trees has caused limitations on the usage of remote sensing images to make a synoptic estimation of damages caused by dust storms and drought. The objective of this research is to analyse the spectral-temporal behaviour of Persian oak under the stress of water deficiency and dust storms. The aim is to improve the competitive abilities of experts on modelling the stress of water deficiency and dust storms on trees using remote sensing images. For the purpose of this experimental investigation, a greenhouse laboratory has been built. Analysis of the experiments was carried out using 54 two-year-old oak tree seedlings; Fieldspec-3-ADD; and wind tunnel at the greenhouse of the faculty of agriculture of the Tarbiat Modares University in 2016. Results show that the water stress could be modelled much better using geometrical indices extracted from continuum removed spectrum. Area and the depth were best indices. Water stress has been modelled better that dust stress.
