:: Volume 6, Issue 4 (3-2019) ::
jgit 2019, 6(4): 17-30 Back to browse issues page
Wheat Leaf Rust Disease Severity Estimation Using Reflectance Spectrum Coding Methods
Mohamad Reza Mobasheri *, Pegah Darouei, Davood Ashourloo
Khavaran Institute of Higher Education
Abstract:   (2508 Views)
Using spectroradiometry and remote sensing techniques is an effective and rapid method in diagnosing vegetation diseases which enforced mostly by using spectral vegetation indices and statistical methods.  The present study aimed to deploy encoding technique for the reflectance spectrum of the wheat leaves to assess the severity of the Rust disease. This is unlike to the spectral vegetation indices in which the shape of the spectrum, in all bands, independent from time and place is examined. A comprehensive laboratory spectroradiometry were used in the present study in which different stages of the development of the wheat rust stage were considered.  The encoding methods were applied to the reflectance spectrum and its derivatives by the Equal Intervals Coding (EIC) and 1bit, 2bit and 3bit information and Threshold Coding (TC) methods for the 500-800 and 400-1050nm wavelength ranges. In this respect, the healthy green leaf code used as a reference. Then the similarity between any other leaf codes and the green leaf code were used to find the degree of the severity of the disease. Beside the reflectance spectrum, the progress of the disease on the leaf under observation were determined using a digital camera. The best result found to be for 3bit- TC in the 500-800 nm wavelength region with R2 and RMSE of the order of 0.95 and 0.05, respectively. Finally, the portion of the rust affected leaf was determined in four levels based on the green spot absence in which, the overall accuracy and Kappa coefficient were 85.96% and 0.81%, respectively.
Keywords: Reflectance, Encoding, Similarity Angle, Wheat Rust, Derivation.
Full-Text [PDF 1059 kb]   (777 Downloads)    
Type of Study: Research | Subject: RS
Received: 2016/12/14 | Accepted: 2017/02/1 | Published: 2019/03/20

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Volume 6, Issue 4 (3-2019) Back to browse issues page