Volume 17, Issue 44 (6-2017)                   jgs 2017, 17(44): 7-24 | Back to browse issues page

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Mobasheri: M R, Ranjbar S. Detection of the wheat rust disease infected farms using Landsat images. jgs. 2017; 17 (44) :7-24
URL: http://jgs.khu.ac.ir/article-1-2720-en.html
1- , Mohammadreza.mobasheri@khi.ac.ir
Abstract:   (6222 Views)

The goal of this study is to identify farms which are affected by wheat rust disease. For this, the sensor data of Landsat 7 satellites in growing season of 2013 and 2014 along with some laboratorial data containing reflectance spectrum of leaf and leaf health degree in different levels of disease are used. The reflectance values of leaf are collected by an ASD spectroradiometer in the range of red and near infrared spectrum. The spectral are simulated for Landsat sensor bands using their spectral response functions. Then with the index of DVI and data obtained for leaf health, the Wheat Health Index was introduced. The correlation coefficient obtained is 0.82 and the relevant RMSE is 0.089 which is really good result for diagnosing highly advanced disease. The results show that, this index has a good performance in wheat high growing season when the greenness is high. It can diagnose regions that are healthy from those whom are blighted. Because the WHI index is a spectral index and is sensitive to leaf color, if the acquired images are close to the harvesting time, its performance will be weakened. The selected region in this survey is located in Fars, province, Saadatshahr city.

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Type of Study: Research |
Received: 2017/03/18 | Accepted: 2017/03/18

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