Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a

       Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a low v

In this study, the synoptic analysis of dust storm for spring and summertime in Iraq were investigated. The images for dust provided by NASA are used to emphasize the dust storm days, while the composite maps of wind vector and geopotential 850hPa are mapped to investigate the pressure and wind direction patterns appearing with the dust condition in the same days. Spring has more dust frequency than summertime, especially in May. The frontal type of dust storm is dominant on spring, the cold air pushes the warm air that picking up the sand to the air through the vertical wind, but the southwestern high-speed wind and drought condition were controlled on the dust in summer. The northwestern wind is the main factor that carries the dust for l

Dust storms are among the most important weather phenomena in Middle East. The Shamal dust storms are dominated across Iraq and the whole Middle East, especially in summer. However, frontal type of dust storms is possible in winter and spring. In this research, a comprehensive case study was conducted to a dust storm that occurred on 20 March 2016 from many perspectives: synoptic, satellite imagery, dust concentration analysis, visibility reduction, and aerosol optical depth. The study shows that the dust storm initiated inside Syria and moved eastward with the movement of the front. Dust concentrations and aerosol optical depth were also discussed that simulate the dust storm over Iraq in a reasonable way with some differences. The dust

The Normalized Difference Vegetation Index (NDVI) is commonly used as a measure of land surface greenness based on the assumption that NDVI value is positively proportional to the amount of green vegetation in an image pixel area. The Normalized Difference Vegetation Index data set of Landsat based on the remote sensing information is used to estimate the area of plant cover in region west of Baghdad during 1990-2001. The results show that in the period of 1990 and 2001 the plant area in region of Baghdad increased from (44760.25) hectare to (75410.67) hectare. The vegetation area increased during the period 1990-2001, and decreases the exposed area.

The current study was applied in Al-Zafaraniya area southeast of the capital Baghdad from October 2021 to April 2022. This is to evaluate some heavy elements (Cd, Co, Cu, Fe, Pb, and Mn) in the street, storm, and suspended dust. Four sampling sites were selected, and codes A, B, C, and D were given to represent the industrial activity sites, service workshops, business activity, and residential areas.

        The results showed that the concentration rates of elements (Cd, Co, Cu, Fe, Pb, Mn) in street dust samples were (1.15, 6.6, 60.15, 26770, 44.4, 6, 489.8). In storm dust (2, 10, 49.3, 54760, 24.3, 827.2) ppm, respectively, the results of suspended dust revealed that the general rates of element concentrations were (0.7

In this research, attempt to overcome and quantities the problem of the large number of frequency of dust storms and the areas that generated and then identifying these areas in order to be held by the agricultural areas, as has been the adoption of many of the techniques and methods of processing image in remote sensing and geographic information systems and linking them together to identify those areas in Iraq or the neighbors, especially the northern and north-west wind of the fact that Iraq is in the northern and north - western most days of the year. Research has included the use of images from the satellite (MODIS) with quality (Aqua) and (Terra) with the assembly of the amount of dust, these storms, it was determining the values o

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Climate change is one of the global issues that is receiving wide attention due to its clear impact on all living organisms. This is essential for Iraq since it was classified as the fifth most vulnerable country to climate change. One of the manifestations of these changes in Iraq is the increasing frequency and severity of dust storms. In this study, the Normalized Difference Dust Index (NDDI) spectral index for Moderate Resolution Imaging Spectroradiometer (MODIS) sensor bands was used to measure and track the dust storm that occurred on May 16, 2022, as well as to test the validity of one of the daily products of this sensor, MOD11A1, to measure surface temperature and emissivity before and after the storm. It was found that the MOD0