The Iraqi Marshlands has natural and economic potential through its environment rich in various forms of lives. This region has suffered numerous setbacks due to human and natural factors, especially in the last two decades of the last century, which led to significant environmental degradation. The purpose of this paper is to prepare spatial data for the area of the marshes in Iraq as a base (Hour-al Hoveizah and central marshes and Hammar). Also, the other aim is to produce a digital geodatabase for the marshes for the years 1973, 1986, 1999, 2006 and 2016 by using ArcGIS. The process of building geodatabase has been through done in three stages: the first stage is including data collection. The second stage will be by merging the satellite images covering the Iraqi marshes and add to images in order to get the image mosaic process. Also, a georeferencing of satellite images is to be done with all the traditional maps of the same area of the marsh. Finally, complete the full geodatabase for the area of interest by using ArcGIS as the in Cartography Design. The results of this research would be a geodatabase for the Iraqi marshes.

The research deals with the thermal island in Baghdad city and the effect of urban expansion on it. Cities are suffering from a marked rise in temperature, compared with the surrounding rural areas, this problem occurs in most cities of the world. The reason for their formation is the increasing of human activity in the form of city components, such as buildings and roads that replace green spaces and open spaces. This means that most of these materials have the ability to absorb solar radiation and convert it into heat energy that increases the heat of their environment. Remote sensing technique is used to determine the thermal island through using Landsat satellite images as well as the use of GIS technology in mapping and analysis of spatial variation for thermal island. Normalized Difference Vegetation Index (NDVI) is calculated to extract vegetation cover from 2003 to 2018. The land surface temperature is estimated from the thermal band of satellite images for the same period. The change in vegetation cover is linked to the change in land surface temperature to determine the effect of vegetation cover degradation on surface temperature, also to determine the relationship between thermal island and land uses. The values of NDVI was high in 2003 and it ranged from (-0.714 - 0.693); this indicates a high vegetal cover, while its value is decreased to (-0.22 - 0.509) in 2018, pointing out to the significant deterioration of vegetation cover in 15 years. The land surface temperature is increased from (10.93-36.26) in 2003 to (22.62-50.29) in 2018; all this at the expense of converting the green, open and agricultural areas to residential, commercial and industrial uses as well as the large number of random settlements that appeared in Baghdad after 2003.

Urban growth driven by uncontrolled expansion is one of the greatest problems that reduces the fertile lands in Karbala Governorate, Iraq. This phenomenon is the cause for variety of urban environmental problems such as an increase in local temperature, cost of land, and loss of agricultural produce.  Multiple images of different time periods were used, passing them through a series of image processing steps according to the methodology of work to achieve the aims of the paper by calculating land cover changes for Karbala City from 1992 to 2013. The aim of this research is to take the temporal and subtle changes in urbanization and land cover primarily to take into account a superior perception of the connection and activities between urban growth and urban environmental problems. To take action and greater control of land surface features, the data from Landsat 4 (MSS) 1992, Landsat 7 Thematic Mapper (ETM) 2003, and Landsat 8 Operational Land Imager (OLI) 2013 were used to deliver the research's aim.

Pollutant emissions are considered to be a major threat to air quality and human health in urban areas. Therefore, accurate modeling and assessment tools are required. In this study, a model was done by the integration of machine learning algorithms and a geographic information system model. This model included the optimization of the support vector regression model by using the principal component analysis algorithm. Then, the integration of the regression model with spatial analysis modeling via a grid (100 x 100 m) was done in order to generate prediction maps during holidays and workdays in the daytime and at nighttime in a highly congested area in Baghdad city, Iraq. The data used in this study categorized into two categories. The first category is the data acquired through field surveying that includes temperature, humidity, wind speed, wind direction, and traffic flow data (e.g., the number of light and heavy vehicles), as well as carbon monoxide samples by using mobile equipment. The second category is the information derived from geographic information system data, such as land use, road network, and building height. The accuracy of the proposed model is 81%, and the lowest value of root mean square error was 0.067 ppm. The integration between air pollution models and geographic information system techniques could be a promising tool for urban air quality assessment and urban planning. These tools effectively utilized by stakeholders and decision-makers to outline proper plans and strategies to mitigate air pollutants in urban areas.

Now a day, the Global Positioning System (GPS) is used in engineering surveying application, civil engineering construction and for correct object positioning, as in other fields (soil mapping characterization, military applications, and so on). As a result of the multipath error that increases when GPS signal is reflected by smooth surfaces around the antenna, the accuracy of positioning is reduced. For GPS signals this effect mainly appears in the neighbourhood of large buildings. In this research the faculty of engineering at University of Tikrit was chosen as a study area and the points were established at nearby building whose surface was able to reflect the incoming signals. The reflected signal takes more time to reach the receiver than the direct signal. The multipath effect is caused by reflection of satellite signals (radio waves) on objects. This paper shows the result of error obtained by (RTK and static observations) in different situations based on the GPS signals with different differential GPS receiver’s system that was caused by multipath error reflected.