Search results for: satellite mapping

Authors: Armand Okende, Benjamin Beaumont

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Introduction: Deforestation is a change in the structure and composition of flora and fauna, which leads to a loss of biodiversity, production of goods and services and an increase in fires. It concerns vast territories in tropical zones particularly; this is the case of the territory of Bolobo in the current province of Maï- Ndombe in the Democratic Republic of Congo. Indeed, through this study between 2001 and 2018, we believe that it was important to show and analyze quantitatively the important forests changes and analyze quantitatively. It’s the overall objective of this study because, in this area, we are witnessing significant deforestation. Methodology: Mapping and quantification are the methodological approaches that we have put forward to assess the deforestation or forest changes through satellite images or raster layers. These satellites data from Global Forest Watch are integrated into the GIS software (GRASS GIS and Quantum GIS) to represent the loss of forest cover that has occurred and the various changes recorded (e.g., forest gain) in the territory of Bolobo. Results: The results obtained show, in terms of quantifying deforestation for the periods 2001-2006, 2007-2012 and 2013-2018, the loss of forest area in hectares each year. The different change maps produced during different study periods mentioned above show that the loss of forest areas is gradually increasing. Conclusion: With this study, knowledge of forest management and protection is a challenge to ensure good management of forest resources. To do this, it is wise to carry out more studies that would optimize the monitoring of forests to guarantee the ecological and economic functions they provide in the Congo Basin, particularly in the Democratic Republic of Congo. In addition, the cartographic approach, coupled with the geographic information system and remote sensing proposed by Global Forest Watch using raster layers, provides interesting information to explain the loss of forest areas.

Keywords: deforestation, loss year, forest change, remote sensing, drivers of deforestation

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Authors: Abida Haddouche, Ahmed Chrif Toubal

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The Neogene basin of the Eastern Mitidja, object of the study area, represents potential water resources and especially groundwater reserves. This water is an important economic; this resource is highly sensitive which need protection and preservation. Unfortunately, these waters are exposed to various forms of pollution, whether from urban, agricultural, industrial or merely accidental. This pollution is a permanent risk of limiting resource. In this context, the work aims to evaluate the intrinsic vulnerability of the aquifer to protect and preserve the quality of this resource. It will focus on the disposal of water and land managers a cartographic document accessible to locate the areas where the water has a high vulnerability. Vulnerability mapping of the Easter Mitidja quaternary aquifer is performed by applying three methods (DRASTIC, DRIST, and GOD). Comparison and validation results show that the DRASTIC method is the most suitable method for aquifer vulnerability of the study area.

Keywords: Aquifer of Mitidja, DRASTIC method, geographic information system (GIS), vulnerability mapping

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Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

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Authors: Hong Mengdi, Li Jianan, Ji Fei, Chen Aiting, Wang Qian

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Objective: To overcome the communication barriers that audiologists encounter during cochlear implant mapping, particularly the challenge of eliciting subjective feedback from recipients regarding electrical stimulation, and to enhance the capabilities of existing technologies, we teamed up with software engineers to design an interactive approach for patient-audiologist communication. This approach employs a tablet (PAD) as the interface for a communication and feedback system between patients and audiologists during the mapping process, known as the Cochlear Implant Mapping Assistance System. Methods: Capitalizing on the touchscreen functionality of the PAD, the recipients' subjective feedback during cochlear implant mapping is instantly transmitted to the audiologist's mapping computer. The system acts as a platform for auditory assessment instruments, facilitating immediate evaluation of recipients' post-mapping hearing and speech discrimination capabilities. Furthermore, the system is designed to augment the visual reinforcement audiometry (VRA) process. The system consists of six modules, including three testing projects: loudness testing, hearing threshold testing, and loudness balance testing; two assessment projects: warble tone testing and digit speech testing; and one VRA animation project. It also incorporates speech-to-text and text input display functions tailored to accommodate speech communication difficulties in hearing-impaired individuals, with pre-installed common exchange content between audiologists and recipients. Audiologists can input sentences by selecting options. The system supports switching between Chinese and English versions, suitable for audiologists and recipients who use English, facilitating international application of the system. Results: The Cochlear Implant Mapping Assistance System has been in use for over a year in the Auditory Implant Center of the Department of Otology and Neurotology, Medical Center of Otology and Head & Neck Surgery, Chinese PLA General Hospital, with more than 300 recipients using this mapping system. Currently, the system operates stably, with both audiologists and recipients providing positive feedback, indicating a significant improvement over previous methods. It is particularly well-received by pediatric recipients, significantly enhancing the work efficiency of audiologists and improving the feedback efficiency and accuracy of recipients. The system enhances the comprehensibility for cochlear implant recipients, improves wearing comfort and user experience, facilitates cochlear implant auditory mapping, and increases the collection of previously challenging-to-obtain data during the existing assisted mapping process, such as loudness testing data, electrical stimulation testing data, warble tone testing data, loudness balance testing data, digit speech testing data, and visual reinforcement audiometry testing data. Real-time data recording improves the accuracy of assisted mapping. The interface design is meticulously crafted to accommodate patients of varying ages and cognitive abilities, featuring an intuitive design that allows for effortless, guidance-free use by patients.

Keywords: audiologist, subjective feedback, mapping, cochlear implant

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

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The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

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Authors: Chieh-Fu Chang, Wan-Hsin Hsieh

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We have proposed a novel scheme— iterative word-extension (IWE) to enhance the cliff effect of Reed-Solomon codes regarding the error performance at a specific Eb/N0. The scheme can be readily extended to block codes and the important properties of IWE are further investigated here. In order to select proper block codes specifying the desired cliff Eb/N0, the associated features of IWE are explored. These properties and features grant IWE ability to enhance security regarding the received Eb/N0 in physical layer so that IWE scheme can cooperate with the traditional presentation layer approach — cryptography, to meet the secure requirements in diverse applications. The features and feasibility of IWE scheme in satellite communication are finally discussed.

Keywords: security, IWE, cliff effect, space communications

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Authors: Masood Beheshtirad

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Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed.

Keywords: landslide, mapping, multiple model, regression

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Authors: Cristian Matti, Valerie Fowles, Eva Enyedi, Piotr Pogorzelski

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The system mapping process can be defined as a knowledge service where a team of facilitators, experts and practitioners facilitate a guided conversation, enable the exchange of information and support an iterative curation process. System mapping processes rely on science-based tools to introduce and simplify a variety of components and concepts of socio-technical systems through metaphors while facilitating an interactive dialogue process to enable the design of co-created maps. System maps work then as “artifacts” to provide information and focus the conversation into specific areas around the defined challenge and related decision-making process. Knowledge management facilitates the curation of that data gathered during the system mapping sessions through practices of documentation and subsequent knowledge co-production for which common practices from data science are applied to identify new patterns, hidden insights, recurrent loops and unexpected elements. This study presents empirical evidence on the application of these techniques to explore mechanisms by which visual tools provide guiding principles to portray system components, key variables and types of data through the lens of climate change. In addition, data science facilitates the structuring of elements that allow the analysis of layers of information through affinity and clustering analysis and, therefore, develop simple indicators for supporting the decision-making process. This paper addresses methodological and empirical elements on the horizontal learning process that integrate system mapping through visual tools, interpretation, cognitive transformation and analysis. The process is designed to introduce practitioners to simple iterative and inclusive processes that create actionable knowledge and enable a shared understanding of the system in which they are embedded.

Keywords: indicators, knowledge management, system mapping, visual tools

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Authors: Juan Cuesta

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Satellite observation is a fundamental component of air pollution monitoring systems, such as the large-scale Copernicus Programme. Next-generation satellite sensors, in orbit or programmed in the future, offer great potential to observe major air pollutants, such as tropospheric ozone, with unprecedented spatial and temporal coverage. However, satellite approaches developed for remote sensing of tropospheric ozone are based solely on measurements from a single instrument in a specific spectral range, either thermal infrared or ultraviolet. These methods offer sensitivity to tropospheric ozone located at the lowest at 3 or 4 km altitude above the surface, thus limiting their applications for ozone pollution analysis. Indeed, no current observation of a single spectral domain provides enough information to accurately measure ozone in the atmospheric boundary layer. To overcome this limitation, we have developed a multispectral synergism approach, called "IASI+GOME2", at the Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA) laboratory. This method is based on the synergy of thermal infrared and ultraviolet observations of respectively the Infrared Atmospheric Sounding Interferometer (IASI) and the Global Ozone Monitoring Experiment-2 (GOME-2) sensors embedded in MetOp satellites that have been in orbit since 2007. IASI+GOME2 allowed the first satellite observation of ozone plumes located between the surface and 3 km of altitude (what we call the lowermost troposphere), as it offers significant sensitivity in this layer. This represents a major advance for the observation of ozone in the lowermost troposphere and its application to air quality analysis. The ozone abundance derived by IASI+GOME2 shows a good agreement with respect to independent observations of ozone based on ozone sondes (a low mean bias, a linear correlation larger than 0.8 and a mean precision of about 16 %) around the world during all seasons. Using IASI+GOME2, lowermost tropospheric ozone pollution plumes are quantified both in terms of concentrations and also in the amounts of ozone photo-chemically produced along transport and also enabling the characterization of the ozone pollution, such as what occurred during the lockdowns linked to the COVID-19 pandemic. The current paper will show the IASI+GOME2 multispectral approach to observe the lowermost tropospheric ozone from space and an overview of several applications on different continents and at a global scale.

Keywords: ozone pollution, multispectral synergism, satellite, air quality

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Authors: Rizky Oktaviana

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The main purpose of studying lies in improving students’ understanding. Teachers usually use written test to measure students’ understanding about learning material especially mathematical learning material. This common method actually has a lack point, such that in mathematics content, written test only show procedural steps to solve mathematical problems. Therefore, teachers unable to see whether students actually understand about mathematical concepts and the relation between concepts or not. One of the best tools to observe students’ understanding about the mathematical concepts is concept map. The goal of this research is to describe junior high school students understanding about mathematical concepts through Concept Maps based on the difference of mathematical ability. There were three steps in this research; the first step was choosing the research subjects by giving mathematical ability test to students. The subjects of this research are three students with difference mathematical ability, high, intermediate and low mathematical ability. The second step was giving concept mapping training to the chosen subjects. The last step was giving concept mapping task about the function to the subjects. Nodes which are the representation of concepts of function were provided in concept mapping task. The subjects had to use the nodes in concept mapping. Based on data analysis, the result of this research shows that subject with high mathematical ability has formal understanding, due to that subject could see the connection between concepts of function and arranged the concepts become concept map with valid hierarchy. Subject with intermediate mathematical ability has relational understanding, because subject could arranged all the given concepts and gave appropriate label between concepts though it did not represent the connection specifically yet. Whereas subject with low mathematical ability has poor understanding about function, it can be seen from the concept map which is only used few of the given concepts because subject could not see the connection between concepts. All subjects have instrumental understanding for the relation between linear function concept, quadratic function concept and domain, co domain, range.

Keywords: concept map, concept mapping, mathematical concepts, understanding

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: Siddhartha Khare, Nitish Kr Boro, Omm Animesh Mishra

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Recent food price hikes may signal the end of an era of predictable global grain crop plenty due to climate change, population expansion, and dietary changes. Food consumption will treble in 20 years, requiring enormous production expenditures. Climate and the atmosphere changed owing to rainfall and seasonal cycles in the past decade. India's tropical agricultural relies on evapotranspiration and monsoons. In places with limited resources, the global environmental change affects agricultural productivity and farmers' capacity to adjust to changing moisture patterns. Motivated by these difficulties, satellite remote sensing might be combined with near-surface imaging data (smartphones, UAVs, and PhenoCams) to enable phenological monitoring and fast evaluations of field-level consequences of extreme weather events on smallholder agriculture output. To accomplish this technique, we must digitally map all communities agricultural boundaries and crop kinds. With the improvement of satellite remote sensing technologies, a geo-referenced database may be created for rural Indian agriculture fields. Using AI, we can design digital agricultural solutions for individual farms. Main objective is to Geo-enable each farm along with their seasonal crop information by combining Artificial Intelligence (AI) with satellite and near-surface data and then prepare long term crop monitoring through in-depth field analysis and scanning of fields with satellite derived vegetation indices. We developed an AI based algorithm to understand the timelapse based growth of vegetation using PhenoCam or Smartphone based images. We developed an android platform where user can collect images of their fields based on the android application. These images will be sent to our local server, and then further AI based processing will be done at our server. We are creating digital boundaries of individual farms and connecting these farms with our smart phone application to collect information about farmers and their crops in each season. We are extracting satellite-based information for each farm from Google earth engine APIs and merging this data with our data of tested crops from our app according to their farm’s locations and create a database which will provide the data of quality of crops from their location.

Keywords: artificial intelligence, satellite remote sensing, crop monitoring, android and web application

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Authors: Sefa Aksu, Ünal Kızıl

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For this study, a town based soil database created in Gümüşçay District of Biga Town, Çanakkale, Turkey. Crop and livestock production are major activities in the district. Nutrient management is mainly based on commercial fertilizer application ignoring the livestock manure. Within the boundaries of district, 122 soil sampling points determined over the satellite image. Soil samples collected from the determined points with the help of handheld Global Positioning System. Labeled samples were sent to a commercial laboratory to determine 11 soil parameters including salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium, iron, manganese, copper and zinc. Based on the test results soil maps for mentioned parameters were developed using remote sensing, GIS, and geostatistical analysis. In this study we developed a GIS database that will be used for soil nutrient management. Methods were explained and soil maps and their interpretations were summarized in the study.

Keywords: geostatistics, GIS, nutrient management, soil mapping

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Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

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The modeling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high-resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve denser and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high-resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D models, environment, matching, pleiades

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Authors: Techale B., Hongxu Dong, Mihrete Getinet, Aregash Gabizew, Andrew H. Paterson, Kassahun Bantte

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The genetic architecture of drought tolerance is expected to involve multiple loci that are unlikely to all segregate for alternative alleles in a single bi-parental population. Therefore, the identification of quantitative trait loci (QTL) that are expressed in diverse genetic backgrounds of multiple bi-parental populations provides evidence about both background-specific and common genetic variants. The purpose of this study was to map QTL related to drought tolerance using three connected mapping populations of different genetic backgrounds to gain insight into the genomic landscape of this important trait in elite Ethiopian germplasm. The three bi-parental populations, each with 207 F₂:₃ lines, were evaluated using an alpha lattice design with two replications under two moisture stress environments. Drought tolerance related traits were analyzed separately for each population using composite interval mapping, finding a total of 105 QTLs. All the QTLs identified from individual populations were projected on a combined consensus map, comprising a total of 25 meta QTLs for seven traits. The consensus map allowed us to deduce locations of a larger number of markers than possible in any individual map, providing a reference for genetic studies in different genetic backgrounds. The mQTL identified in this study could be used for marker-assisted breeding programs in sorghum after validation. Only one trait, reduced leaf senescence, showed a striking bias of allele distribution, indicating substantial standing variation among present varieties that might be employed in improving drought tolerance of Ethiopian and other sorghums.

Keywords: Drought tolerance , Mapping populations, Meta QTL, QTL mapping, Sorghum

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Authors: Joo-Heon Lee, Seo-Yeon Park, Chanyang Sur, Ho-Won Jang

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Satellite-based remote sensing technique has been widely used in the area of drought and environmental monitoring to overcome the weakness of in-situ based monitoring. There are many advantages of remote sensing for drought watch in terms of data accessibility, monitoring resolution and types of available hydro-meteorological data including environmental areas. This study was focused on the applicability of drought monitoring based on satellite imageries by applying to the historical drought events, which had a huge impact on meteorological, agricultural, and hydrological drought. Satellite-based drought indices, the Standardized Precipitation Index (SPI) using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM); Vegetation Health Index (VHI) using MODIS based Land Surface Temperature (LST), and Normalized Difference Vegetation Index (NDVI); and Scaled Drought Condition Index (SDCI) were evaluated to assess its capability to analyze the complex topography of the Korean peninsula. While the VHI was accurate when capturing moderate drought conditions in agricultural drought-damaged areas, the SDCI was relatively well monitored in hydrological drought-damaged areas. In addition, this study found correlations among various drought indices and applicability using Receiver Operating Characteristic (ROC) method, which will expand our understanding of the relationships between hydro-meteorological variables and drought events at global scale. The results of this research are expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-damaged areas.

Keywords: drought monitoring, moderate resolution imaging spectroradiometer (MODIS), remote sensing, receiver operating characteristic (ROC)

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Authors: Poonam Yadav, Dong Bok Lee

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Raman spectroscopy was used for characterization of multi-wall carbon nanotube (MWNT) and Polycarbonate/multi-wall carbon nanotube (PC/MWNT) based fibers with 0.55% and 0.75% of MWNT (PC/MWNT55 and PC/MWNT75). PC/MWNT55 and PC/MWNT75 fibers was prepared by melt spinning device using nanocomposites made by two different route, viz., solvent casting and melt extrusion. Fibers prepared from melt extruded nanocomposites showed smooth and uniform morphology as compared to solvent casting based nanocomposites. The Raman mapping confirmed that the melt extruded based nanocomposites had better dispersion of MWNT in Polycarbonate (PC) than solvent casting carbon nanotube.

Keywords: dispersion, melt extrusion, multi-wall carbon nanotube, mapping

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: K. C. R. Perera, B. M. Hapuwatte

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This paper presents an effective method to divide panels for mesh-less methods of source, vortex and doublet panel methods. In this research study the physical domain of air-foils were transformed into computational domain of a circle using conformal mapping technique of Joukowsky transformation. Then the circle is divided into panels of equal length and the co-ordinates were remapped into physical domain of the air-foil. With this method the leading edge and the trailing edge of the air-foil is panelled with a high density of panels and the rest of the body is panelled with low density of panels. The high density of panels in the leading edge and the trailing edge will increase the accuracy of the solutions obtained from panel methods where the fluid flow at the leading and trailing edges are complex.

Keywords: conformal mapping, Joukowsky transformation, physical domain, computational domain

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Authors: Rafia Hassan, Ali Rizwan, Sadaf Farhan, Bushra Sabir

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The purpose of this study is to compare the conventional crop monitoring system with the satellite based crop monitoring system in Pakistan. This study is conducted for SUPARCO (Space and Upper Atmosphere Research Commission). The study focused on the wheat crop, as it is the main cash crop of Pakistan and province of Punjab. This study will answer the following: Which system is better in terms of cost, time and man power? The man power calculated for Punjab CRS is: 1,418 personnel and for SUPARCO: 26 personnel. The total cost calculated for SUPARCO is almost 13.35 million and CRS is 47.705 million. The man hours calculated for CRS (Crop Reporting Service) are 1,543,200 hrs (136 days) and man hours for SUPARCO are 8, 320hrs (40 days). It means that SUPARCO workers finish their work 96 days earlier than CRS workers. The results show that the satellite based crop monitoring system is efficient in terms of manpower, cost and time as compared to the conventional system, and also generates early crop forecasts and estimations. The research instruments used included: Interviews, physical visits, group discussions, questionnaires, study of reports and work flows. A total of 93 employees were selected using Yamane’s formula for data collection, which is done with the help questionnaires and interviews. Comparative graphing is used for the analysis of data to formulate the results of the research. The research findings also demonstrate that although conventional methods have a strong impact still in Pakistan (for crop monitoring) but it is the time to bring a change through technology, so that our agriculture will also be developed along modern lines.

Keywords: area frame, crop reporting service, CRS, sample frame, SRS/GIS, satellite remote sensing/ geographic information system

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Authors: Manjit Singha, Sandeep Singh Sandhu, A. S. Shahi

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Stellite 6 is cobalt based superalloy used for protective coatings. It is used to improve the wear performance of stainless steel engineering components subjected to harsh environmental conditions. This paper reports the high temperature wear analysis of satellite 6 cladded on AISI 304 L substrate using SMAW process. Bead on plate experiment was carried out by varying current and electrode manipulation techniques to optimize the dilution and hardness. 80 Amp current and weaving technique was found to be the optimum set of parameters for overlaying which were further used for multipass multilayer cladding on two plates of AISI 304 L substrate. On the first plate, seven layers seven passes of stellite 6 was overlaid which was used in as cladded form and the second plate was overlaid with five layers five passes of satellite 6 with further TIG remelting. The wear performance was examined for normal temperature environmental condition and harsh temperature environmental condition. The satellite 6 coating with TIG remelting was found to be better in both the conditions even with lesser metal deposition due to its finer grain structure.

Keywords: surfacing, stellite 6, dilution, overlay, SMAW, high-temperature frictional wear, micro-structure, micro-hardness

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Authors: Henok Mezemr Besfat, Haftom Gebreslassie Gebregwergs

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wireless network is one of the most important mediums of transmission of information from one device to another devices. Wireless communication has a broad range of applications, including mobile communications through cell phones and satellites, Internet of Things (IoT) connecting several devices, wireless sensor networks for traffic management and environmental monitoring, satellite communication for weather forecasting and TV without requiring any cable or wire or other electronic conductors, by using electromagnetic waves like IR, RF, satellite, etc. This paper summarizes different wireless network technologies, applications of different wireless technologies and different types of wireless networks. Generally, wireless technology will further enhance operations and experiences across sectors with continued innovation. This paper suggests different strategies that can improve wireless networks and technologies.

Keywords: wireless senser, wireless technology, wireless network, internet of things

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Authors: Zahra Emami, Mohammad Ebrahim Khamseh, Nahid Hashemi Madani, Iman Kermani

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The aim of the study was to map scientific research on adrenal gland diseases in the Middle East countries through the Web of Science database using scientometric analysis. Data were analyzed with Excel software; and HistCite was used for mapping of the scientific texts. In this study, from a total of 268 retrieved records, 1125 authors from 328 institutions published their texts in 138 journals. Among 17 Middle East countries, Turkey ranked first with 164 documents (61.19%), Israel ranked second with 47 documents (15.53%) and Iran came in the third place with 26 documents. Most of the publications (185 documents, 69.2%) were articles. Among the universities of the Middle East, Istanbul University had the highest science production rate (9.7%). The Journal of Clinical Endocrinology & Metabolism had the highest TGCS (243 citations). In the scientific mapping, 7 clusters were formed based on TLCS (Total Local Citation Score) & TGCS (Total Global Citation Score). considering the study results, establishment of scientific connections and collaboration with other countries and use of publications on adrenal gland diseases from high ranking universities can help in the development of this field and promote the medical practice in this regard. Moreover, investigation of the formed clusters in relation to Congenital Hyperplasia and puberty related disorders can be research priorities for investigators.

Keywords: mapping, scientific research, adrenal gland diseases, scientometric

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Authors: Bassem Nassar, Wessam Hussein, Medhat Mokhtar

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The crucial concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems in order to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important in order to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the aforementioned problem coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions and the results shows that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: space telemetry monitoring, multivariate analysis, PCA algorithm, space operations

Procedia PDF Downloads 415

Authors: Bruno D. Souza, Gerson G. Cunha, Michael O. Ferreira, Roberto Rosenhaim, Robson C. Santos, Sergio O. Santos

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Devices and applications that use satellite-based positioning are becoming more popular day-by-day. Thus, evolution and improvement in this technology are mandatory. Accordingly, satellite georeferenced systems need to accomplish the same evolution rhythm. Either GPS (Global Positioning System) or its similar Russian GLONASS (Global Navigation Satellite System) are system samples that offer us powerful tools to plot coordinates on the earth surface. The development of this research aims the study of several aspects related to use of GPS and GLONASS technologies, given its application and collected data improvement during geodetic data acquisition. So, both relevant theoretic and practical aspects are considered. In this context, at the theoretical part, the main systems' characteristics are shown, observing its similarities and differences. At the practical part, a series of experiences are performed and obtained data packages are compared in order to demonstrate equivalence or differences among them. The evaluation methodology targets both quantitative and qualitative analysis provided by GPS and GPS/GLONASS receptors. Meanwhile, a specific collected data storage system was developed to better compare and analyze them (SisGeo - Georeferenced Research Comparison Support System).

Keywords: satellites, systems, applications, experiments, receivers

Procedia PDF Downloads 254

Authors: A. Cilek, S. Berberoglu, A. Akin Tanriover, C. Donmez

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Wetlands are the areas which have important effects and functions on protecting human life, adjust to nature, and biological variety, besides being potential exploitation sources. Observing the changes in these sensitive areas is important to study for data collecting and correct planning for the future. Remote sensing and Geographic Information System are being increasingly used for environmental studies such as biotope mapping and habitat monitoring. Akyatan Lagoon, one of the most important wetlands in Turkey, has been facing serious threats from agricultural applications in recent years. In this study, seasonal and temporal monitoring in wetlands system are determined by using remotely sensed data and Geographic Information Systems (GIS) between 1985 and 2015. The research method is based on classifying and mapping biotopes in the study area. The natural biotope types were determined as coastal sand dunes, salt marshes, river beds, coastal woods, lakes, lagoons.

Keywords: biotope mapping, GIS, remote sensing, wetlands

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Authors: Shahriar Ghammamy, Mehrnoosh Saboony

Abstract:

Purpose: To evaluate the spectral specification (IR-XRD and SEM) of nano-ciprofloxacin that prepared by up-down method (satellite mill). Methods: the ciprofloxacin was minimized to nano-scale with satellite mill and its characterization evaluated by Infrared spectroscopy, XRD diffraction and semi electron microscope (SEM). Expectation enhances the antibacterial property of nano-ciprofloxacin in comparison to ciprofloxacin. IR spectrum of nano-ciprofloxacin compared with spectrum of ciprofloxacin, and both of them were almost agreement with a difference: the peaks in spectrum of nano-ciprofloxacin were sharper than peaks in spectrum of ciprofloxacin. X-Ray powder diffraction analysis of nano-ciprofloxacin shows the diameter of particles equal to 90.9nm. (on the basis of Scherer Equation). SEM image shows the global shape for nano-ciprofloxacin.

Keywords: antibiotic, ciprofloxacin, nano, IR, XRD, SEM

Procedia PDF Downloads 514

Authors: Shahriar Ghammamy, Mehrnoosh Saboony

Abstract:

Purpose: to evaluate the spectral specification(IR-XRD and SEM) of nano ciprofloxacin that prepared by up-down method (satellite mill). Methods: the ciprofloxacin was minimized to nano-scale with satellite mill and it,s characterization evaluated by Infrared spectroscopy, XRD diffraction and semi electron microscope (SEM). Expectation: to enhance the antibacterial property of nano ciprofloxacin in comparison to ciprofloxacin.IR spectrum of nano ciprofloxacin compared with spectrum of ciprofloxacin, and both of them were almost agreement with a difference: the peaks in spectrum of nano ciprofloxacin was sharper than peaks in spectrum of ciprofloxacin. X-Ray powder diffraction analysis of nano ciprofloxacin showes the diameter of particles equal to 90.9 nm (on the basis of scherrer equation). SEM image showes the global shape for nano ciprofloxacin.

Keywords: antibiotic, ciprofloxacin, nano, IR, XRD, SEM

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Authors: Rezvan Khavari

Abstract:

The Zagros fold-thrust belt in SW Iran is a part of the Alpine-Himalayan system which consists of a variety of structures with different sizes or geometries. The study area is Chamshir Dam, which is located on the Zohreh River, 20 km southeast of Gachsaran City (southwest Iran). The satellite images are valuable means available to geologists for locating geological or geomorphological features expressing regional fault or fracture systems, therefore, the satellite images were used for structural analysis of the Chamshir dam area. As well, using the DEM and geological maps, 3D Models of the area have been constructed. Then, based on these models, all the acquired fracture traces data were integrated in Geographic Information System (GIS) environment by using Arc GIS software. Based on field investigation and DEM model, main structures in the area consist of Cham Shir syncline and two fault sets, the main thrust faults with NW-SE direction and small normal faults in NE-SW direction. There are three joint sets in the study area, both of them (J1 and J3) are the main large fractures around the Chamshir dam. These fractures indeed consist with the normal faults in NE-SW direction. The third joint set in NW-SE is normal to the others. In general, according to topography, geomorphology and structural geology evidences, Chamshir dam has a potential for sliding in some parts of Gachsaran formation.

Keywords: DEM, chamshir dam, zohreh river, satellite images

Procedia PDF Downloads 481