Search results for: landsat satellite images

Authors: S. M. Samkeyat Shohan

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This study is mainly focused on the determination and analysis of the photolysis rate of atmospheric, specifically tropospheric, ozone as function of cloud properties through-out the year 2007. The observational basis for ozone concentrations and cloud properties are the measurement data set of the Global Ozone Monitoring Experiment-2 (GOME-2) sensor on board the polar orbiting Metop-A satellite. Two different spectral ranges are used; ozone total column are calculated from the wavelength window 325 – 335 nm, while cloud properties, such as cloud top height (CTH) and cloud optical thick-ness (COT) are derived from the absorption band of molecular oxygen centered at 761 nm. Cloud fraction (CF) is derived from measurements in the ultraviolet, visible and near-infrared range of GOME-2. First, ozone concentrations above clouds are derived from ozone total columns, subtracting the contribution of stratospheric ozone and filtering those satellite measurements which have thin and low clouds. Then, the values of ozone photolysis derived from observations are compared with theoretical modeled results, in the latitudinal belt 5˚N-5˚S and 20˚N - 20˚S, as function of CF and COT. In general, good agreement is found between the data and the model, proving both the quality of the space-borne ozone and cloud properties as well as the modeling theory of ozone photolysis rate. The found discrepancies can, however, amount to approximately 15%. Latitudinal seasonal changes of photolysis rate of ozone are found to be negatively correlated to changes in upper-tropospheric ozone concentrations only in the autumn and summer months within the northern and southern tropical belts, respectively. This fact points to the entangled roles of temperature and nitrogen oxides in the ozone production, which are superimposed on its sole photolysis induced by thick and high clouds in the tropics.

Keywords: cloud properties, photolysis rate, stratospheric ozone, tropospheric ozone

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Authors: Fatima Achouri, Zakaria Smahi

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Bir El Djir is an important coastal township in Oran department, located at 450 Km far away from Algiers on northwest of Algeria. In this coastal area, the urban sprawl is one of the main problems that reduce the limited highly fertile land. So, using the remote sensing and GIS technologies have shown their great capabilities to solve many earth resources issues. The aim of this study is to produce land use and cover map for the studied area at varied periods to monitor possible changes that may occurred, particularly in the urban areas and subsequently predict likely changes. For this, two spatial images SPOT and Landsat satellites from 1987 and 2014 respectively were used to assess the changes of urban expansion and encroachment during this period with photo-interpretation and GIS approach. The results revealed that the town of Bir El Djir has shown a highest growth rate in the period 1987-2014 which is 521.1 hectares in terms of area. These expansions largely concern the new real estate constructions falling within the social and promotional housing programs launched by the government. Indeed, during the last census period (1998 -2008), the population of this town has almost doubled from 73 029 to 152 151 inhabitants with an average annual growth of 5.2%. This also significant population growth is causing an accelerated urban expansion of the periphery which causing its conurbation with the towns of Oran in the West side. The most urban expansion is characterized by the new construction in the form of spontaneous or peripheral precarious habitat, but also unstructured slums settled especially in the southeastern part of town.

Keywords: urban expansion, remote sensing, photo-interpretation, spatial dynamics

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Authors: N. Pegahfar, P. Ghafarian

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In this research, the synoptic weather conditions during the heavy flood of 10-12 January 2020 in the Sistan-va-Balouchestan Province of Iran will be analyzed. To this aim, reanalysis data from the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), NCEP Global Forecasting System (GFS) analysis data, measured data from a surface station together with satellite images from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) have been used from 9 to 12 January 2020. Atmospheric parameters both at the lower troposphere and also at the upper part of that have been used, including absolute vorticity, wind velocity, temperature, geopotential height, relative humidity, and precipitation. Results indicated that both lower-level and upper-level currents were strong. In addition, the transport of a large amount of humidity from the Oman Sea and the Red Sea to the south and southeast of Iran (Sistan-va-Balouchestan Province) led to the vast and unexpected precipitation and then a heavy flood.

Keywords: Sistan-va-Balouchestn Province, heavy flood, synoptic, analysis data

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Authors: Recep Gundogan, Turgay Dindaroglu, Hikmet Gunal, Mustafa Ulukavak, Ron Bingner

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A majority of total soil losses in agricultural areas could be attributed to ephemeral gullies caused by heavy rains in conventionally tilled fields; however, ephemeral gully erosion is often ignored in conventional soil erosion assessments. Ephemeral gullies are often easily filled from normal soil tillage operations, which makes capturing the existing ephemeral gullies in croplands difficult. This study was carried out to determine topographic features, including slope and aspect composite topographic index (CTI) and initiation points of gully channels, using images obtained from unmanned aerial vehicle (UAV) images. The study area was located in Topcu stream watershed in the eastern Mediterranean Region, where intense rainfall events occur over very short time periods. The slope varied between 0.7 and 99.5%, and the average slope was 24.7%. The UAV (multi-propeller hexacopter) was used as the carrier platform, and images were obtained with the RGB camera mounted on the UAV. The digital terrain models (DTM) of Topçu stream micro catchment produced using UAV images and manual field Global Positioning System (GPS) measurements were compared to assess the accuracy of UAV based measurements. Eighty-one gully channels were detected in the study area. The mean slope and CTI values in the micro-catchment obtained from DTMs generated using UAV images were 19.2% and 3.64, respectively, and both slope and CTI values were lower than those obtained using GPS measurements. The total length and volume of the gully channels were 868.2 m and 5.52 m³, respectively. Topographic characteristics and information on ephemeral gully channels (location of initial point, volume, and length) were estimated with high accuracy using the UAV images. The results reveal that UAV-based measuring techniques can be used in lieu of existing GPS and total station techniques by using images obtained with high-resolution UAVs.

Keywords: aspect, compound topographic index, digital terrain model, initial gully point, slope, unmanned aerial vehicle

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

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Authors: C. Gopi Jinimole, A. Harsha

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For detecting strokes, Computed Tomography (CT) scan is preferred for imaging the abnormalities or infarction in the brain. Because of the problems in the window settings used to evaluate brain CT images, they are very poor in the early stage infarction detection. This paper presents an automatic estimation method for the window settings of the CT images for proper contrast of the hyper infarction present in the brain. In the proposed work the window width is estimated automatically for each slice and the window centre is changed to a new value of 31HU, which is the average of the HU values of the grey matter and white matter in the brain. The automatic window width estimation is based on the average of median of statistical central moments. Thus with the new suggested window centre and estimated window width, the hyper infarction or post-stroke regions in CT brain images are properly detected. The proposed approach assists the radiologists in CT evaluation for early quantitative signs of delayed stroke, which leads to severe hemorrhage in the future can be prevented by providing timely medication to the patients.

Keywords: computed tomography (CT), hyper infarction or post stroke region, Hounsefield Unit (HU), window centre (WC), window width (WW)

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Authors: Sylvain Chardon, Timotéo Payre, Hugo Grardel, Yann Quentel, Mathieu Thomachot, Gérald Aigouy, Frank Claeyssen

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With the increasing digitalization of society, access to data has become vital and strategic for individuals and nations. In this context, the number of satellite constellation projects is growing drastically worldwide and is a next-generation challenge of the New Space industry. So far, existing satellite constellations have been using radio frequencies (RF) for satellite-to-ground communications, inter-satellite communications, and feeder link communication. However, RF has several limitations, such as limited bandwidth and low protection level. To address these limitations, space optical communication will be the new trend, addressing both very high-speed and secured encrypted communication. Fast Steering Mirrors (FSM) are key components used in optical communication as well as space imagery and for a large field of functions such as Point Ahead Mechanisms (PAM), Raster Scanning, Beam Steering Mirrors (BSM), Fine Pointing Mechanisms (FPM) and Line of Sight stabilization (LOS). The main challenges of space FSM development for optical communication are to propose both a technology and a supply chain relevant for high quantities New Space approach, which requires secured connectivity for high-speed internet, Earth planet observation and monitoring, and mobility applications. CTEC proposes a mini-FSM technology offering a stroke of +/-6 mrad and a resonant frequency of 1700 Hz, with a mass of 50 gr. This FSM mechanism is a good candidate for giant constellations and all applications on board NanoSats and CubeSats, featuring a very high level of miniaturization and optimized for New Space high quantities cost efficiency. The use of piezo actuators offers a high resonance frequency for optimal control, with almost zero power consumption in step and stay pointing, and with very high-reliability figures > 0,995 demonstrated over years of recurrent manufacturing for Optronics applications at CTEC.

Keywords: fast steering mirror, feeder link, line of sight stabilization, optical communication, pointing ahead mechanism, raster scan

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Authors: Lamees Nasser, Yago Diez, Robert Martí, Joan Martí, Ibrahim Sadek

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Automated 3D breast ultrasound (ABUS) screening is a novel modality in medical imaging because of its common characteristics shared with other ultrasound modalities in addition to the three orthogonal planes (i.e., axial, sagittal, and coronal) that are useful in analysis of tumors. In the literature, few automatic approaches exist for typical tasks such as segmentation or registration. In this work, we deal with two problems concerning ABUS images: nipple and rib detection. Nipple and ribs are the most visible and salient features in ABUS images. Determining the nipple position plays a key role in some applications for example evaluation of registration results or lesion follow-up. We present a nipple detection algorithm based on color and shape of the nipple, besides an automatic approach to detect the ribs. In point of fact, rib detection is considered as one of the main stages in chest wall segmentation. This approach consists of four steps. First, images are normalized in order to minimize the intensity variability for a given set of regions within the same image or a set of images. Second, the normalized images are smoothed by using anisotropic diffusion filter. Next, the ribs are detected in each slice by analyzing the eigenvalues of the 3D Hessian matrix. Finally, a breast mask and a probability map of regions detected as ribs are used to remove false positives (FP). Qualitative and quantitative evaluation obtained from a total of 22 cases is performed. For all cases, the average and standard deviation of the root mean square error (RMSE) between manually annotated points placed on the rib surface and detected points on rib borders are 15.1188 mm and 14.7184 mm respectively.

Keywords: Automated 3D Breast Ultrasound, Eigenvalues of Hessian matrix, Nipple detection, Rib detection

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Authors: Perumalla Naveen Kumar

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Global Positioning System (GPS) is used for civilian and military user positioning applications. The accuracy of GPS is degrading mainly because of ionospheric error. It is very important to analyze the effects of ionosphere on the performance of satellite systems especially in the low latitude regions. These variations depend on the Total Electron Content (TEC) in the ionosphere. To investigate the variations in the atmosphere, a mini satellite known as YOUTHSAT is launched by India. This is the outcome of the collaboration between India and USSR. One of the YOUTHSAT Indian payload is RaBIT (Radio Beacon for Ionospheric Tomography). In this paper, YOUTHSAT RaBIT payload data for the three typical days of 2011 are considered. The analysis is carried out for four Indian stations. The variations of Slant TEC, elevation angle and azimuth angles are analyzed with respect to local time. The obtained results are encouraging.

Keywords: Global Positioning System (GPS), Total Electron Content (TEC), YOUTHSAT, Radio Beacon for Ionospheric Tomography (RaBIT)

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Cherifi Mehdi, Lahdir Mourad, Ameur Soltane

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Image compression is the heart of several multimedia techniques. It is used to reduce the number of bits required to represent an image. Meteosat Second Generation (MSG) satellite allows the acquisition of 12 image files every 15 minutes and that results in a large databases sizes. In this paper, a novel image compression method based on the arithmetic coding with the sorted Run Length Coding (SRLC) for MSG images is proposed. The SRLC allows us to find the occurrence of the consecutive pixels of the original image to create a sorted run. The arithmetic coding allows the encoding of the sorted data of the previous stage to retrieve a unique code word that represents a binary code stream in the sorted order to boost the compression ratio. Through this article, we show that our method can perform the best results concerning compression ratio and bit rate unlike the method based on the Run Length Coding (RLC) and the arithmetic coding. Evaluation criteria like the compression ratio and the bit rate allow the confirmation of the efficiency of our method of image compression.

Keywords: image compression, arithmetic coding, Run Length Coding, RLC, Sorted Run Length Coding, SRLC, Meteosat Second Generation, MSG

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Authors: Sandeep Thakur, Ismail Mondal, Phani Bhusan Ghosh, Papita Das, Tarun Kumar De

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Sundarbans Reserve forest of India has been undergoing major transformations in the recent past owing to population pressure and related changes. This has brought about major changes in the spatial landscape of the region especially in the western parts. This study attempts to assess the impacts of the Landcover changes on the mangrove habitats. Time series imageries of Landsat were used to analyze the Normalized Differential Vegetation Index (NDVI) patterns over the western parts of Indian Sundarbans forest in order to assess the heath of the mangroves in the region. The images were subjected to Land use Land cover (LULC) classification using sub-pixel classification techniques in ERDAS Imagine software and the changes were mapped. The spatial proliferation of aquaculture farms during the study period was also mapped. A multivariate regression analysis was carried out between the obtained NDVI values and the LULC classes. Similarly, the observed meteorological data sets (time series rainfall and minimum and maximum temperature) were also statistically correlated for regression. The study demonstrated the application of NDVI in assessing the environmental status of mangroves as the relationship between the changes in the environmental variables and the remote sensing based indices felicitate an efficient evaluation of environmental variables, which can be used in the coastal zone monitoring and development processes.

Keywords: aquaculture farms, LULC, Mangrove, NDVI

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Ibrahim Isa Ali (Pantami), Abdu Jaafaru Bambale, Abimbola Alale, Danjuma Ibrahim Ndihgihdah, Muhammad Alkali, Adamu Idris Umar, Moshood Kareem, Samson Olufunmilayo Abodunrin, Muhammad Dokko Zubairu

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The National Digital Economy Policy and Strategy, NDEPS document developed by Nigeria’s Federal Ministry of Communications & Digital Economy (FMoCDE) is anchored on 8 pillars for the acceleration of the National Digital Economy for a Digital Nigeria. NIGCOMSAT-1R and the planned HTS communication Satellite are critical assets for supporting the pillars in the drive for sustainable growth and development. This paper discusses on the gains and contribution of the strategy as a solid infrastructure. The paper also highlights these assets’ contribution as platform for Indigenous Content Development & Adoption, Digital Literacy & Skills, and Digital Services Development & Promotion.

Keywords: FMoCDE, HTS, NDEPS, nigcomsat!R, pillars

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: Tewele Gebretsadkan Haile

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Mountain terrains are essential to regional water resources by regulating hydrological processes that use downstream water supplies. Nevertheless, limited observed earth data in complex topography poses challenges for water resources regulation. That's why satellite product is implemented in this study. This study evaluates hydrological processes on mountain catchment of Gumera, Ethiopia using HBV-light model with satellite precipitation products (CHIRPS) for the temporal scale of 1996 to 2010 and area coverage of 1289 km2. The catchment is characterized by cultivation dominant and elevation ranges from 1788 to 3606 m above sea level. Three meteorological stations have been used for downscaling of the satellite data and one stream flow for calibration and validation. The result shows total annual water balance showed that precipitation 1410 mm, simulated 828 mm surface runoff compared to 1042 mm observed stream flow with actual evapotranspiration estimate 586mm and 1495mm potential evapotranspiration. The temperature range is 9°C in winter to 21°C. The catchment contributes 74% as quack runoff to the total runoff and 26% as lower groundwater storage, which sustains stream flow during low periods. The model uncertainty was measured using different metrics such as coefficient of determination, model efficiency, efficiency for log(Q) and flow weighted efficiency 0.76, 0.74, 0.66 and 0.70 respectively. The research result highlights that HBV model captures the mountain hydrology simulation and the result indicates quack runoff due to the traditional agricultural system, slope factor of the topography and adaptation measure for water resource management is recommended.

Keywords: mountain hydrology, CHIRPS, Gumera, HBV model

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Authors: Tewele Gebretsadkan Haile

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Mountain terrains are essential to regional water resources by regulating hydrological processes that use downstream water supplies. Nevertheless, limited observed earth data in complex topography poses challenges for water resources regulation. That's why satellite product is implemented in this study. This study evaluates hydrological processes on mountain catchment of Gumera, Ethiopia using HBV-light model with satellite precipitation products (CHIRPS) for the temporal scale of 1996 to 2010 and area coverage of 1289 km2. The catchment is characterized by cultivation dominant and elevation ranges from 1788 to 3606 m above sea level. Three meteorological stations have been used for downscaling of the satellite data and one stream flow for calibration and validation. The result shows total annual water balance showed that precipitation 1410 mm, simulated 828 mm surface runoff compared to 1042 mm observed stream flow with actual evapotranspiration estimate 586mm and 1495mm potential evapotranspiration. The temperature range is 9°C in winter to 21°C. The catchment contributes 74% as quack runoff to the total runoff and 26% as lower groundwater storage, which sustains stream flow during low periods. The model uncertainty was measured using different metrics such as coefficient of determination, model efficiency, efficiency for log(Q) and flow weighted efficiency 0.76, 0.74, 0.66 and 0.70 respectively. The research result highlights that HBV model captures the mountain hydrology simulation and the result indicates quack runoff due to the traditional agricultural system, slope factor of the topography and adaptation measure for water resource management is recommended.

Keywords: mountain hydrology, CHIRPS, HBV model, Gumera

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

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Authors: Nisar Ahmed Memon

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A new medical image watermarking scheme delivering high embedding capacity is presented in this paper. Integer Wavelet Transform (IWT), Companding technique and adaptive thresholding are used in this scheme. The proposed scheme implants, recovers the hidden information and restores the input image to its pristine state at the receiving end. Magnetic Resonance Imaging (MRI) images are used for experimental purposes. The scheme first segment the MRI medical image into non-overlapping blocks and then inserts watermark into wavelet coefficients having a high frequency of each block. The scheme uses block-based watermarking adopting iterative optimization of threshold for companding in order to avoid the histogram pre and post processing. Results show that proposed scheme performs better than other reversible medical image watermarking schemes available in literature for MRI medical images.

Keywords: adaptive thresholding, companding technique, data authentication, reversible watermarking

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Authors: Blessing Mavhuru, Nthaduleni Nethengwe, Hector Chikoore, Onyango Beneah Daniel Odhiambo

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The main objective of this study was to classify land use/cover and how it has changed in Nzhelele Valley Limpopo Province, South Africa. The study aimed to identify and analyse the types of land use/cover in the years 2005, 2010, and 2015 with a view to assess the impact on soil erosion over time. Using GIS, the changes within land use/cover were assessed through the classification of satellite images. The study area was classified into four major land cover/use classes, which are vegetation, gravel road, built up land and agricultural fields. Over the period 2005-2015 the resultant land use/cover demonstrated (i) a significant increase (12%) for vegetation cover, (ii) a significant decrease in agriculture (16%) land use/cover, (iii) increase in built-up land (1%), as well as (iv) an increase in gravel roads (3%). This study envisages assisting policy makers in decision making on land use management for Nzhelele Valley.

Keywords: land use, land cover, change, soil erosion

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Authors: Erkam Arslantas

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Heat pipes one of the thermal control elements are used in communication satellites. A selection of the heat pipes of satellite thermal design will be emphasized how important and effective it is. In this article, manufacturing and performance control tests of heat pipes are reviewed from the current literature. The heat pipe is expected to function efficiently during all missions of the spacecraft from Beginning of Life (BOL) to End of Life (EOL). There are many parameters that are evaluated in manufacturing and performance control tests of the heat pipes which are used in satellites. These parameters are pressure design, leakage, noncondensable gas level (N.C.G), sine vibration, shock and static load capabilities, aging, bending, proof, final test etc. These parameters will be explained separately for the heat pipes in this review article and young researches working on the thermal control system of Geosynchronous Satellites systems can find easily related information in this article.

Keywords: communication satellite, heat pipe, performance test, thermal control

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

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Growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC) and Image Fidelity (IF) over the previous techniques.

Keywords: fractal image, information hiding, Mandelbrot et fractal, steganography

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Authors: Nasir A. Al-Geelani, Zulkurnain Abdul-Malek, M. Afendi M. Piah

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This research paper investigation is carried out in the laboratory on single units of transmission line glass insulator characterized by different thermal images, which aimed to find out the age of the insulators. The tests were carried out on virgin and aged insulators using the thermography scan. Various samples having different periods of aging 20, 15, and 5 years from a 132 kV transmission line which have exhibited a different degree of corrosion. The second group of insulator samples was relatively mild aged insulators, while the third group was lightly aged; finally, the fourth group was the brand new insulators. The results revealed a strong correlation between the aging and the thermal images captured by the infrared camera. This technique can be used to monitor the aging of high voltage insulators as a precaution to avoid disaster.

Keywords: glass insulator, infrared camera, corona diacharge, transmission lines, thermograpy, surface discharge

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Authors: Rubab Ammad, Abdelgadir Abuelgasim

Abstract:

UAE typically lies in one of the aridest regions of the world and is thus home to geologic features common to such climatic conditions including vast open deserts, sand dunes, saline soils, inland Sabkha and coastal Sabkha. Sabkha are characteristic salt flats formed in arid environment due to deposition and precipitation of salt and silt over sand surface because of low laying water table and rates of evaporation exceeding rates of precipitation. The study area, which comprises of western UAE, is heavily concentrated with inland Sabkha. Remote sensing is conventionally used to study the soil salinity of agriculturally degraded lands but not so broadly for Sabkha. The focus of this study was to identify these highly saline Sabkha areas on remotely sensed data, using salinity indices. The existing salinity indices in the literature have been designed for agricultural soils and they have not frequently used the spectral response of short-wave infra-red (SWIR1 and SWIR2) parts of electromagnetic spectrum. Using Landsat 8 OLI data and field ground truthing, this study formulated indices utilizing NIR-SWIR parts of spectrum and compared the results with existing salinity indices. Most indices depict reasonably good relationship between salinity and spectral index up until a certain value of salinity after which the reflectance reaches a saturation point. This saturation point varies with index. However, the study findings suggest a role of incorporating near infra-red and short-wave infra-red in salinity index with a potential of showing a positive relationship between salinity and reflectance up to a higher salinity value, compared to rest.

Keywords: Sabkha, salinity index, saline soils, Landsat 8, SWIR1, SWIR2, UAE desert

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Authors: Juliana Bom-Tempo

Abstract:

The proposed composition occurs between images, performances, clinics and philosophies. For this enterprise we depart for what is not known beforehand, so with a question as a compass: "would it be in the creation, production and implementation of images in a performance a 'when' for the event of a poetic clinic?” In light of this, there are, in order to think a 'when' of the event of a poetic clinic, images in performances created, produced and executed in partnerships with the author of this text. Faced with this composition, we built four indicators to find spatiotemporal coordinates that would spot that "when", namely: risk zones; the mobilizations of the signs; the figuring of the flesh and an education of the affections. We dealt with the images in performances; Crútero; Flesh; Karyogamy and the risk of abortion; Egg white; Egg-mouth; Islands, threads, words ... germs; Egg-Mouth-Debris, taken as case studies, by engendering risks areas to promote individuations, which never actualize thoroughly, thus always something of pre-individual and also individuating a environment; by mobilizing the signs territorialized by the ordinary, causing them to vary the language and the words of order dictated by the everyday in other compositions of sense, other machinations; by generating a figure of flesh, disarranging the bodies, isolating them in the production of a ground force that causes the body to leak out and undo the functionalities of the organs; and, finally, by producing an education of affections, by placing the perceptions in becoming and disconnecting the visible in the production of small deserts that call for the creation of a people yet to come. The performance is processed as a problematizing of the images fixed by the ordinary, producing gestures that precipitate the individuation of images in performance, strange to the configurations that gather bodies and spaces in what we call common. Lawrence proposes to think of "people" who continually use umbrellas to protect themselves from chaos. These have the function of wrapping up the chaos in visions that create houses, forms and stabilities; they paint a sky at the bottom of the umbrella, where people march and die. A chaos, where people live and wither. Pierce the umbrella for a desire of chaos; a poet puts himself as an enemy of the convention, to be able to have an image of chaos and a little sun that burns his skin. The images in performances presented, thereby, were moving in search for the power of producing a spatio-temporal "when" putting the territories in risk areas, mobilizing the signs that format the day-to-day, opening the bodies to a disorganization and the production of an education of affections for the event of a poetic clinic.

Keywords: Experimentations , Images in Performances, Poetic Clinic, Risk

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Authors: Ruslan Salmurzauli, Sabir Nurtazin, Buho Hoshino, Niels Thevs, A. B. Yeszhanov, Aiman Imentai

Abstract:

This article presents the results of a research on the transformation of the diverse ecosystems of the Ili delta during the period 1979-2014 based on the analysis of the hydrological regime dynamics, weather conditions and satellite images. Conclusions have been drawn on the decisive importance of the water runoff of the Ili River in the negative changes and environmental degradation in delta areas over the past forty-five years. The increase of water consumption in the Chinese and Kazakhstan parts of the Ili-Balkhash basin caused desiccation and desertification of many hydromorphic delta ecosystems and the reduction of water flow into Lake Balkhash. We demonstrate that a significant reduction of watering of the delta areas could drastically accelerate the aridization and degradation of the hydromorphic ecosystems. Under runoff decrease, a transformation process of the delta ecosystems begins from the head part and gradually spread northward to the periphery of the delta. The desertification is most clearly expressed in the central and western parts of the delta areas.

Keywords: Ili-Balkhash basin, Ili river delta, runoff, hydrological regime, transformation of ecosystems, remote sensing

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Authors: Adnan H. M. Al-Helali, Hamza A. Ali

Abstract:

The growth of censorship and pervasive monitoring on the Internet, Steganography arises as a new means of achieving secret communication. Steganography is the art and science of embedding information within electronic media used by common applications and systems. Generally, hiding information of multimedia within images will change some of their properties that may introduce few degradation or unusual characteristics. This paper presents a new image steganography approach for hiding information of multimedia (images, text, and audio) using generated Mandelbrot Fractal image as a cover. The proposed technique has been extensively tested with different images. The results show that the method is a very secure means of hiding and retrieving steganographic information. Experimental results demonstrate that an effective improvement in the values of the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Normalized Cross Correlation (NCC), and Image Fidelity (IF) over the pervious techniques.

Keywords: fractal image, information hiding, Mandelbrot set fractal, steganography

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Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

Abstract:

System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

Procedia PDF Downloads 84