The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conversely, when using the maximum-likelihood classifier, the highest accuracy (83.06%) was achieved with FLAASH. The results demonstrate significant variations in accuracies for different land cover classes, which emphasizes the importance of per-class accuracy. The results highlight the critical role of preprocessing techniques and classifier selection in optimizing the classification processes and land cover mapping accuracy for remote sensing geospatial applications. Finally, the actual differences in classification accuracy between processing levels are larger than those given by the confusion matrix. So, the consideration of alternative evaluation methods with the absence of reference images is critical.
Abstract
This research aims to assess and measure the quality of health services provided by the Baghdad Educational Hospital using five dimensions of 5Qs , Developer model by (Zinelidin), 2006), the problem of the research is to try to determine the quality of health services provided at the hospital as well as the investigation of the existence of the elements of quality contribute to achieve the requirements of customers and their needs, and used for the purposes of this research two approaches, first used Applied Research to 5Qs dimension model and use the Checklist as a Key tool to collection and analysis of data and the second descriptive analytical me
... Show MoreRoller-Compacted Concrete (RCC) is a zero-slump concrete, with no forms, no reinforcing steel, no finishing and is wet enough to support compaction by vibratory rollers. Because the effectiveness of curing on properties and durability, the primary scope of this research is to study the effect of various curing methods (air curing, emulsified asphalt(flan coat) curing, 7 days water curing and permanent water curing) and different porcelanite (local material used as an Internal Curing agent) replacement percentages (volumetric replacement) of fine aggregate on some properties of RCC and to explore the possibility of introducing more practical RCC for road pavement with minimum requirement of curing. Cubes specimens were sawed from the slab
... Show MoreThe research starts from studying the contractual budget, which is one of the modern trends in preparing public budgets, both operational and capital, in addition to meeting the requirements of the global trend to achieve sustainable growth in all fields, whether financial or non-financial, and tools for the contractual budget have been identified (participation contracts, planning Implementation, monitoring) and studying its impact in supporting sustainable development through its dimensions (economic, social, and environmental). The method of the questionnaire was adopted as a main tool in collecting information on research variables and distributing it to a sample of (70) individuals who dictate positions of professional respo
... Show MoreBig data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
... Show MoreThis study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in t
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreIntroduction: Since the hallmark of gestational trophoblastic disease is trophoblastic proliferation, Ki67 is regarded as the best marker in studying hydatidiform mole.This study was conducted to evaluate the role of this proliferative marker in distinguishing among hydropic abortion, partial and complete hydatidiform mole. Materials and methods: This is a cross sectional study involving the application of Ki67 on a total of 90 histological samples of curetting materials from molar (partial and complete mole) and non molar hydropic abortion belong to Iraqi females, so three study groups were created. Immunohistochemical expression in villous cytotrophoblasts, syncytiotrophoblasts and stromal cells were recorded separately by three i
... Show MoreObjective(s): The present study aims at studying the relationship between immunoglobulin IgG, IgA,
IgM , as well as to C-3 and C-4 in brain tumours patients immunity (meningioms and gliomas).
Methodology: Forty sera of brain tumour patients were included 20 glioma and 20 meningioma was
tested to determine the levels of IgM, IgG IgA, C-3 and C-4 by using single radial immune-diffusion
technique and compared with 20 apparently healthy blood donors.
Results: The study revealed a significant decreasing in IgG levels in glioma as compare to meningioma
and control. The concentration of two other serum immunoglobulins and complement in both
meningioma and glioma show no significant differences with those in control group.