Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtractive between the bands
of the two images and the ratio of the red to blue bands was also
computed. Change detection mask using minimum distance
classification or detection after classification have be also used to
compute the changes between the resultant classes, many statistical
properties of the original and process image have been illustrated in
this research
This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin
ST Alawi, NA Mustafa, Al-Mustansiriyah Journal of Science, 2013
ABSTRACT
The aim of the research is to identify the impact of the areas of organizational change in strategic marketing planning in cement factories operating within the city of Al-Khums, and this effect was measured using a questionnaire consisting of 28 phrases, and it was relied on the descriptive approach that suits the nature of the subject of the research, while the research community consists of heads And members of the board of directors, authorized managers, unit managers and heads of departments in the factories under study, which numbered 55 respondents, during the month of September of the year 2021, and a sample of the compreh
... Show MoreAccurate land use and land cover (LU/LC) classification is essential for various geospatial applications. This research applied a Spectral Angle Mapper (SAM) classifier on the Landsat 7 (ETM+ 2010) & 8 (OLI 2020) satellite scenes to identify the land cover materials of the Shatt al-Arab region which is located in the east of Basra province during ten years with an estimate of the spectral signature using ENVI 5.6 software of each cover with the proportion of its area to the area of the study region and produce maps of the classified region. The bands of these datasets were analyzed using the Optimum Index Factor (OIF) statistic. The highest OIF represents the best and most appropr
لقد كان حرص المؤلف على إصدار هذا الكتاب نابعا ً من قناعة تامة بأن مجال التقويم والقياس بحاجة إلى كتاب علمي حديث يتناول عرض أدوات الاختبار والقياس والمتمثلة بالصدق والثبات ويتسم بالوضوح في التعبير عن المفاهيم والمصطلحات والأنواع لكل منها ليكون وسيلة مبسطة بأيدي الأساتذة والباحثين وطلبتي الدراسات العليا الماجستير والدكتوراه لإستخراج صدق وثبات الاختبارات والمقاييس بطرق إحصائية متقدمة من خلال إستخدام البرنا
... Show MoreThe agricultural lands that depend on supplementary irrigation methods for winter wheat cultivating in wide areas of the Nineveh province are most vulnerable to climate change concerns. Due to frequent rainfall shortages and the temperature increase recently noticed and predicted by the climate scenarios. Hence important to assess the climate effect on the crop response in terms of water consumption during the periods (2021-2040) and (2041-2060) by using high-resolution data extracted from 6 global climate data GCMs under SSP5-8.5 fossil fuel emission scenarios in changing and fixed CO2 concentration. And validate the Aqua-Crop model to estimate the yield and water productivity. And gives the RRSME of 7.1- 4.1
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