Relative diffuse reflection measurements from the original and ground surfaces using a He-Ne laser are reported. The intensity measurements for the metallic, transparent dielectric, matte plastic surfaces and colored papers are presented. Our results indicate that among metallic surfaces tested, aluminum has the highest diffuse reflectance; while the original stainless steel surface shows the lowest. The primary result is that for the ground metallic surfaces, there seems to be an optimum condition and roughness that result in the maximum diffuse reflection. For the color matte plastics, the yellow color has the highest diffuse reflectance and the black one shows the lowest. For the colored papers the yellow paint shows a maximum diffuse reflectance; whereas the gray one has the lowest diffuse reflectance. Our results agree with the theoretical predictions and also with the other experimental results.

The non-context-based approach is used for the synthesis of spectral reflectance curves of objects with known CIEXYZ tristimulus values. The method introduces two sets of features, i.e., the standard color-matching functions normalised by their sum in each wavelength and a group of two sigmoidal and one Gaussian bases that approximately fit the first set. The assigned spectra for the desired tristimulus colorimetric values are calculated using an additive color-mixing approach. Results of different methodologies are numerically compared in terms of root mean squared error (RMSE), goodness fit coefficient (GFC), and CIELAB color difference values between the actual and synthesised spectra. It is found that the synthesised spectra by the suggested primaries better resemble the actual behaviours of spectral reflectances of natural and synthetic objects in comparison to using three Gaussian primaries. Compared to other context and non-context-based approaches to spectral reconstruction, the suggested method is faster and does not require iterative optimisation.

CEC is the most important soil engineering properties used to determine the swelling potential of soil. Measuring CEC of soil is difficult, time-consuming, costly and consuming of dangerous chemical materials. In this study the ability of spectral reflectance to estimate the amount of CEC were investigated. So 45 soil samples were collected from Namkhaneh series of Kheyrood kenar Forest and their reflectance were measured in the range 350-2500 nm in dark room. Then the relationship between CEC and reflectance and first derivative of reflectance were analyzed by single band Pearson correlation, PLSR and two groups of narrowband soil indices (RI, DI). The results of this study showed that narrowband indices have stronger relationship than PLSR and the DI index in case first derivative have highest correlation (R2=0.82, RMSE=5.01). In the PLSR method between reflectance and CEC strong relationship was observed while the indices of first derivation reflectance and CEC have stronger relationship than row reflectance. So reflectance can be as a nondestructive, fast, easy and Cost effective method to estimate the CEC.

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 (a=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.

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