One of the main environmental problems which affect extensively the areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Landsat satellite (TM & ETM+) images have been analyzed to study soil pollution (Exacerbation of salinity in the soil without the use of abandoned agricultural for a long time) at west of Baghdad city of Iraqi country for the years 1990, 2001 & 2007. All of the th

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

Hydromorphometric analysis as a method is considered one of the most reliable and used methods in solving hydrological problems. Where it is possible to know the volume of runoff and the rest of the elements that enter into the water balance. Geographical Information System and Remote Sensing is the technique that used the hydro-morphometric analysis of the Wadi Al-Mohammadi basin. Wadi Al-Mohammadi, located in the Western Desert, is one of the main valleys that flow into the Euphrates River. It is considered an important basin, because of its many characteristics, including its relatively large area and the amount of water drained through, which is used mainly in watering livestock and agriculture, in addition to industrial purposes suc

This study appears GIS techniqueand remote sensing data are matching with the field observation to identify the structural features such as fault segments in the urban area such as the Merawa and Shaqlawa Cities. The use of different types of data such as fault systems, drainage patterns (previously mapped), lineament, and lithological contacts with spatial resolution of 30m was combined through a process of integration and index overlay modeling technique for producing the susceptibility map of fault segments in the study area. GIS spatial overlay technique was used to determine the spatial relationships of all the criteria (factors) and subcriteria (classes) within layers (maps) to classify and map the potential ar

The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

This paper describes the use of remote sensing techniques in verification of the polluted area in Diyala River and Tigris River and the effected of AL-Rustamiyah wastewater treatment plant, which is located on Diyala River, one of the branches of Tigris River in south of Baghdad. SPOT-5 a French satellite image of Baghdad, Iraq was used with ground resolution of 2.5 m in May 2016. ENVI 5.1 software programming was utilized for Image processing to assess the water pollution of Diyala and Tigris River’s water. Five regions were selected from a study area and then classified using the unsupervised ISODATA method. The results indicated that four classes of water quality which are successful in assessing and mapping water pollution which confi

The study addressed the water ecosystems of the marshes of Maysan Governorate as one of the important areas in Iraq in terms of the environmental, economic and tourism aspects. This area was exposed to great environmental changes due to natural and human factors which greatly affected the water ecosystem and made the area susceptible to many problems that affected the biological life of living organisms. The marshes of Maysan Governorate was affected by vital factors and non-vital factors. The marshes of Maysan Governorate was characterized by the UN Organization as one of the most important centers of biodiversity in the world because of the abundance of different and rare living organisms such as birds, fish, and reptiles as well as the e

This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

The marshes are one of the important environmental features affecting human and animal systems, so the studying of changes they undergo is one of the important topics. This study is concerned with the changes occurring in the Al Saadya marsh for the period from 1987 to 2017 exclusively in the winter season (the marshes’ revival season in Iraq revive). In order to inspect the changes in this marsh, we choose 7 years to cover the study period as a criterion years, namely 1987, 1990, 1995, 2000, 2007, 2014 and 2017. The “Maximum Likelihood” classifier was used to separate the stacked land cover features, where the minimum overall accuracy ratio that recorded for all years of study was 96%. The results revealed that Al-Saadya marsh went t