The useful of remote sensing techniques in Environmental Engineering and another science is to save time, Coast and efforts, also to collect more accurate information under monitoring mechanism. In this research a number of statistical models were used for determining the best relationships between each water quality parameter and the mean reflectance values generated for different channels of radiometer operate simulated to the thematic Mappar satellite image. Among these models are the regression models which enable us to as certain and utilize a relation between a variable of interest. Called a dependent variable; and one or more independent variables

Spot panchromatic satellite image had been employed to study and know the difference Between ground and satellite data( DN ,its values varies from 0-255) where it is necessary to convert these DN values to absolute radiance values through special equations ,later it converted to spectral reflectance values .In this study a monitoring of the environmental effect resulted from throwing the sewage drainages pollutants (industrial and home) into the Tigris river water in Mosul, was achieved, which have an effect mostly on physical characters specially color and turbidity which lead to the variation in Spectral Reflectance of the river water ,and it could be detected by using many remote sensing techniques. The contaminated areas within th

In this study; a three-dimensional model was created to simulate groundwater in Al-Haydariyah area of the governorate of Al-Najaf. A solid model was created to utilize the cross sections of 25 boreholes in the research region, and it was made out of two layers: sand and clay. The steady-state calibration was employed in six observation wells to calibrate the model and establish the hydraulic conductivity, which was 17.49 m/d for sand and 1.042 m/d for clay, with a recharge rate of 0.00007 m/day. The wells in the research region were reallocated with a distance of 1500 m between each well, resulting in 140 wells evenly distributed throughout the study area and with a discharge of 5 l/s, and the scenarios were run for 1000

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

The Tel Hajar formation in the studied area has been divided into five microfacics units:

1) Fine hiogenic dolomite facies.

2) Sandy rich dolomite facies.

3) Dolomite diagenetic facies.

4) Recrystal1ized wackestone in microfacies.

5) Mudsione facies.

Microfacics reflect shallow marine water with open Circulation in the lower part of the formation and the environment of the upper is enclosed between upper tide and tide. The most important diagenesis was recrystallization and spary calcite deposit inside fossils chambers and pores.