Iranian Remote Sensing and GIS Society / Shahid Beheshti University Iranian Journal of Remote Sensing and GIS 2008-5966 9 4 2017 07 23 Evaluation of Vegetation Indices to Recognizing Wheat Leaf and Yellow Rust at Canopy Scale Evaluation of Vegetation Indices to Recognizing Wheat Leaf and Yellow Rust at Canopy Scale 111 128 96398 FA D Ashourloo Assistant Prof. of R.S. & GIS Research Center, Shahid Beheshti University 0000-0001-6244-2929 H Aghighi Assistant Prof. of R.S. & GIS Research Center, Shahid Beheshti University A.A Matkan Prof. of R.S. & GIS Research Center, Shahid Beheshti University 0000-0001-5394-4599 H Nematollahi M.Sc. Student of R.S. & GIS, Remote Sensing & GIS Research Center, Shahid Beheshti University Journal Article 2018 05 15 Wheat rust is one of the important diseases of cereal crops in Iran and other countries in the world which imposes irreparable damages to the agricultural economy. In this study, the effects of the leaf and yellow rust disease on wheat leaves reflectance were studied. For this purpose, various vegetation indices derived from leaf spectra were measured. To do this, diseases ratio and varying degrees of disease were extracted by using digital camera and multi-step algorithm including color Transformation, mask preparation, texture and maximum likelihood classification. Results show variation in the values of the parameters with changing in proportion of disease whereas the data scattering of indexes Increase quickly. The highest correlation was for the NDVI (0.9) and the minimum was for the red slope (0.2). With the similarity criteria, range and inter-class scattering relations of spectra and disease were studied and with Increasing of the disease ratio. These criteria are altered by developing of disease ratio .Further investigation showed, spectrum mixing in different fraction of yellow, orange, brown and dead is a cause for data scattering with disease development. Wheat rust is one of the important diseases of cereal crops in Iran and other countries in the world which imposes irreparable damages to the agricultural economy. In this study, the effects of the leaf and yellow rust disease on wheat leaves reflectance were studied. For this purpose, various vegetation indices derived from leaf spectra were measured. To do this, diseases ratio and varying degrees of disease were extracted by using digital camera and multi-step algorithm including color Transformation, mask preparation, texture and maximum likelihood classification. Results show variation in the values of the parameters with changing in proportion of disease whereas the data scattering of indexes Increase quickly. The highest correlation was for the NDVI (0.9) and the minimum was for the red slope (0.2). With the similarity criteria, range and inter-class scattering relations of spectra and disease were studied and with Increasing of the disease ratio. These criteria are altered by developing of disease ratio .Further investigation showed, spectrum mixing in different fraction of yellow, orange, brown and dead is a cause for data scattering with disease development. https://gisj.sbu.ac.ir/article_96398_e7c63dbcf0e02fd22e37d3a1219f4516.pdf