Volume 13, Issue 7 (2011)                   JAST 2011, 13(7): 1091-1104 | Back to browse issues page

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1- Faculty of Natural Resources, University of Tehran, Karaj, Islamic Republic of Iran.
2- Department of Forest Science, Faculty of Natural Resources and Earth Science, University of Shahre-Kord, Shahre-Kord, Islamic Republic of Iran.
3- Department of Geography, University of Zurich-Irchel, Winterthurerstrasse 190 , CH-8057 Zurich, Switzerland.
Abstract:   (7862 Views)
Rice cultivated areas and yield information is indispensable for sustainable management and economic policy making for this strategic food crop. Introduction of high spectral and special resolution satellite data has enabled production of such information in a timely and accurate manner. Knowledge of the spectral reflectance of various land covers is a prerequisite for their identification and study. Evaluation of the spectral reflectance of plants using field spectroradiometry provides the possibility to identify and map different rice varieties especially while using hyperspectral remote sensing. This paper reports the results of the first attempt to evaluate spectral signatures of seven north Iranian rice varieties (Fajr, Hybrid, Khazar, Nemat, Neda, Shiroudi and Tarom plots) in the experimental station of the Iranian Rice Research Institute (main station in Amol, Mazanderan Province). Measurements were carried out using a field spectroradiometer in the range of 350-2,500 nm under natural light and environmental conditions. In order to eliminate erroneous data and also experimental errors in spectral reflectance curves, all curves were individually quality controlled. A set of important vegetation indices sensitive to canopy chlorophyll content, photosynthesis intensity, nitrogen and water content were employed to enhance probable differences in spectral reflectance among various rice varieties. Analysis of variance and Tukey’s paired test were then used to compare rice varieties. Using Datt and PRI1 indices, significant differences (= 0.01) were found among rice varieties reflectances in 19 out of 21 cases. This promises the possibility of accurate mapping of rice varieties cultivated areas based on hyperspectral remotely sensed data.
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Received: 2010/10/19 | Accepted: 2011/04/17 | Published: 2011/09/25

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