This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being conducted to analyze and understand the strengths and weakness of the proposed new method. This research shows that spectral indices are easy and accurate tool for rapid mapping of paddy rice fields in complicated environment where urban features are dominated. The outcomes of this research could help mapping and decision makers to progress their productivity and strategic plans for better management of rice fields.
Kiffil Shinafiya project was selected as it’s been conducted and covering the areas of grain crops agriculture in Najaf and Qadissiya provinces. Lands of this project are considered as a part of the Mesopotamian plain located in between N32⁰ 15′, N31⁰ 30′ and E44⁰ 44’, E44⁰ 20′. Three hydrosequences were disclosed with three transects (T1, T2, T3) in the area of study. The first hydrosequence was perpendicular on the other two sequences. Fifteen pedons were outcropped, five pedons in each transect in addition to eighteen more surface samples to be a total samples of 33 locations. Pedons were morphologically described due to soil survey manual (Soil Survey Staff, 2017). Spatial distribution of soil salinity showed that the
... Show MoreThis study was conducted to estimate some heavy metals cadmium, lead, nickel and iron in 15 samples of Iraqi honey with 3 replicates for each sample which were collected from apiaries near potential contamination areas in five Iraqi governorates, including Baghdad, Karbala, Babylon, Diyala and Salah al-Din. The atomic absorption technique was used to estimate the concentrations of heavy metals, the results showed that there were significant differences at (P≤0.05) between the concentrations of these elements in the honey samples, the highest concentrations of cadmium 0.123 mg/kg were recorded in Baghdad, near the petrochemical production complex, lead 4.657 mg/kg and nickel 0.023 mg/kg in Babylon near the power plant, iron was
... 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 MoreAn oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification
... Show MoreThe general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe
... Show MoreAims of this research to determine asbestos fibers levels in surrounding air of some crowded sites of Baghdad city were monitored in summer 2020. Collection of samples was conducted by directing air flow to a mixed cellulose ester membrane filter mounted on an open‑faced filter holder using sniffer a low flow sampling pump, samples of air were collected from five studied areas selected in some heavy traffic areas of Baghdad city, (Al-Bayaa and Al-Shurta tunnel, Al-Jadriya, and Al-Meshin commercial complex, control), then analyzed to determine concentrations of asbestos fibers. Counting of asbestos on the filters was carried out through using both scanning electron microscope SEM and an energy dispersive X‑ray system EDS to count
... Show MoreInterest in belowground plant growth is increasing, especially in relation to arguments that shallow‐rooted cultivars are efficient at exploiting soil phosphorus while deep‐rooted ones will access water at depth. However, methods for assessing roots in large numbers of plants are diverse and direct comparisons of methods are rare. Three methods for measuring root growth traits were evaluated for utility in discriminating rice cultivars: soil‐filled rhizotrons, hydroponics and soil‐filled pots whose bottom was sealed with a non‐woven fabric (a potential method for assessing root penetration ability). A set of 38 rice genotypes including the Oryza
The research aims to derive the efficient industrial plans for Al – shaheed public company under risk by using Target MOTAD as a linear alternative model for the quadratic programming models.
The results showed that there had been a sort of (trade- off) between risk and the expected gross margins. And if the studied company strives to get high gross margin, it should tolerate risk and vice versa. So the management of Al- Shaheed Company to be invited to apply the suitable procedures in the production process, in order to get efficient plans that improves it's performance .
Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ
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