A statistical model to predict and analyze air surface temperature based on remotely sensed observations.

Air surface temperature (AST) is a crucial importance element for many applications such as hydrology, agriculture, and climate change studies. The aim of this study is to develop regression equation for calculating AST and to analyze and investigate the effects of atmospheric parameters (O3, CH4, CO, H2Ovapor, and outgoing longwave radiation (OLR)) on the AST value in Iraq. Dataset retrieved from the Atmospheric Infrared Sounder (AIRS) at EOS Aqua Satellite, spanning the years of 2003 to 2016, and multiple linear regression were used to achieve the objectives of the study. For the study period, the five atmospheric parameters were highly correlated (R, 0.855-0.958) with predicted AST. Statistical analyses in terms of ß showed that OLR (0.310 to 1.053) contributes significantly in enhancing AST values. Comparisons among selected five stations (Mosul, Kanaqin, Rutba, Baghdad, and Basra) for the year 2010 showed a close agreement between the predicted and observed AST from AIRS, with values ranging from 0.9 to 1.5 K and for ground stations data, within 0.9 to 2.6 K. To make more complete analysis, also, comparison between predicted and observed AST from AIRS for four selected month in 2016 (January, April, July, and October) has been carried out. The result showed a high correlation coefficient (R, 0.87 and 0.95) with less variability (RMSE ≤ 1.9) for all months studied, indicating model's capability and accuracy. In general, the results indicate the advantage of using the AIRS data and the regression analysis to investigate the impact of the atmospheric parameters on AST over the study area.

Near infrared spectral linearisation in quantifying soluble solids content of intact carambola.

This study presents a novel application of near infrared (NIR) spectral linearisation for measuring the soluble solids content (SSC) of carambola fruits. NIR spectra were measured using reflectance and interactance methods. In this study, only the interactance measurement technique successfully generated a reliable measurement result with a coefficient of determination of (R2) = 0.724 and a root mean square error of prediction for (RMSEP) = 0.461° Brix. The results from this technique produced a highly accurate and stable prediction model compared with multiple linear regression techniques.

NIR spectroscopic properties of aqueous acids solutions.

Acid content is one of the important quality attributes in determining the maturity index of agricultural product, particularly fruits. Despite the fact that much research on the measurement of acidity in fruits through non-destructive spectroscopy analysis at NIR wavelengths between 700 to 1,000 nm has been conducted, the same response towards individual acids is not well known. This paper presents NIR spectroscopy analysis on aqueous citric, tartaric, malic and oxalic solutions through quantitative analysis by selecting a set of wavelengths that can best be used to measure the pH of the solutions. The aquaphotomics study of the acid solutions has generated R² above 0.9 for the measurement of all acids. The most important wavelengths for pH are located at 918-925 nm and 990-996 nm, while at 975 nm for water.

A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery.

Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.

Turbidimeter design and analysis: a review on optical fiber sensors for the measurement of water turbidity.

Turbidimeters operate based on the optical phenomena that occur when incident light through water body is scattered by the existence of foreign particles which are suspended within it. This review paper elaborates on the standards and factors that may influence the measurement of turbidity. The discussion also focuses on the optical fiber sensor technologies that have been applied within the lab and field environment and have been implemented in the measurement of water turbidity and concentration of particles. This paper also discusses and compares results from three different turbidimeter designs that use various optical components. Mohd Zubir and Bashah and Daraigan have introduced a design which has simple configurations. Omar and MatJafri, on the other hand, have established a new turbidimeter design that makes use of optical fiber cable as the light transferring medium. The application of fiber optic cable to the turbidimeter will present a flexible measurement technique, allowing measurements to be made online. Scattered light measurement through optical fiber cable requires a highly sensitive detector to interpret the scattered light signal. This has made the optical fiber system have higher sensitivity in measuring turbidity compared to the other two simple turbidimeters presented in this paper. Fiber optic sensors provide the potential for increased sensitivity over large concentration ranges. However, many challenges must be examined to develop sensors that can collect reliable turbidity measurements in situ.