The current research was aimed at the following:
1. Measurement of Personality Type Observer of the University students.
2. Identify the differences in Personality Type Observer among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary)
3. Measurement of Withdrawal of the University students.
4. Identify the differences in Withdrawal among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary).
5. Identify the relationship between Personality Type Observer and Withdrawal.
To achieve this aims of the research, the researchers set up the instrument is scale of Personality Type Observer that consistent (24) item and Withdrawal that consistent (20) item. And the researcher applying this scale on the sample amounted to (200) University students. Then after data processing statistically, the researchers reached the following results:
1. University students have Personality Type Observer.2. There is no differences in Personality Type Observer among the University students according to variable of Sex (male / female). And There is differences according to variable of Specialization (scientific / literary) for literary
3. University students have Withdrawal.
4. There is no differences in Withdrawal among the University students according to variable of Sex (male / female). And There is no differences according to variable of Specialization (scientific / literary).
5. There is relationship between Personality Type Observer and Withdrawal.
In light of the results of this research the researchers came out with a number of recommendations and suggestions.
This paper is based on the Sentinel-2 satellite data: the thermal, red, and NIR bands. The Babylon city was chosen in this study for different reasons: its location in the middle of Iraq and it represents the largest capitals of the Mesopotamia civilization in the word. The Land Surface Temperature (LST) was determined using a method that incorporates remote sensing, geographic information systems, and statistics. This process has made it possible to monitor the relationship between land usage and the land surface temperature for four seasons in the year 2021. The mapswere processed and analyzed by using ArcGIS software. Five maps of the LST were constructed. Each map represents diffe
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