Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. In this paper the two sensors are used to monitoring the agriculture condition and detection the changing in the area of plant covers, the stability and calibration of the ETM+ has been monitored extensively since launch although it is not monitored for many years, TM now has a similar system in place to monitor stability and calibration. By referring to statistical values for the classification process, the results indicated that the state of vegetation in 1990 was in the proportion of 42.8%, while this percentage rose to 52.5% for the same study area in

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

The central marshes are one of the most important wetlands/ecosystems in the southern area of Iraq. This study evaluates the bed soil's mechanical, physical, and chemical properties at certain southern Iraqi central marshes sites. This was conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops and for construction purposes. Soil samples were collected from 15 sites at 10-100 cm depth. Hence, numerous parameters were determined: index properties, unconfined compressive strength, direct shear strength, consolidation, texture, and sieve analysis, water content, specific gravity, dry density, permeability, pH, total soluble salts (TSS), organic materials (OM) and total sulfate con

The central marshes are one of the most important wetlands/ecosystems in the southern area of Iraq. This study evaluates the bed soil's mechanical, physical, and chemical properties at certain southern Iraqi central marshes sites. This was conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops and for construction purposes. Soil samples were collected from 15 sites at 10-100 cm depth. Hence, numerous parameters were determined: index properties, unconfined compressive strength, direct shear strength, consolidation, texture, and sieve analysis, water content, specific gravity, dry density, permeability, pH, total soluble salts (TSS), organic materials (OM) and total