Search results for: very high resolution (VHR) satellite imagery

Authors: Qiuyu Chen, Bin Long, Junxi Yang

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Located in the southwest of the "roof of the world", Tibet is the origin center of Tibetan Culture.Lhasa, Shigatse and Gyantse are three famous historical and cultural cities in Tibet. They have always been prominent political, economic and cultural cities, and have accumulated the unique aesthetic orientation and value consciousness of Tibet's urban construction. "Archetype" usually refers to the theoretical origin of things, which is the collective unconscious precipitation. The archetype theory fundamentally explores the dialectical relationship between image expression, original form and behavior mode. By abstracting and describing typical phenomena or imagery of the archetype object can observe the essence of objects, explore ways in which object phenomena arise. Applying archetype theory to the field of urban planning helps to gain insight, evaluation, and restructuring of the complex and ever-changing internal structural units of cities. According to existing field investigations, it has been found that Dzong, Temple, Linka and traditional residential systems are important structural units that constitute the urban space of Lhasa, Shigatse and Gyantse. This article applies the thinking method of archetype theory, starting from the imagery expression of urban spatial pattern, using technologies such as ArcGIS, Depthmap, and Computer Vision to descriptively identify the spatial representation and plane relationship of three cities through remote sensing images and historical maps. Based on historical records, the spatial characteristics of cities in different historical periods are interpreted in a hierarchical manner, attempting to clarify the origin of the formation and evolution of urban pattern imagery from the perspectives of geopolitical environment, social structure, religious theory, etc, and expose the growth laws and key driving forces of cities. The research results can provide technical and material support for important behaviors such as urban restoration, spatial intervention, and promoting transformation in the region.

Keywords: archetype theory, urban spatial imagery, original form and pattern, behavioral driving force, Tibet

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Authors: Andrey Kupriyanov

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In recent years, much attention has been paid to the problems of ionospheric disturbances and their influence on the signals of global navigation satellite systems (GNSS) around the world. This is due to the increase in solar activity, the expansion of the scope of GNSS, the emergence of new satellite systems, the introduction of new frequencies and many others. The influence of the Earth's ionosphere on the propagation of radio signals is an important factor in many applied fields of science and technology. The paper considers the application of the method of transionospheric sounding using measurements from signals from Global Navigation Satellite Systems to determine the TEC distribution and scintillations of the ionospheric layers. To calculate these parameters, the International Reference Ionosphere (IRI) model of the ionosphere, refined in the local area, is used. The organization of operational monitoring of ionospheric parameters is analyzed using several NovAtel GPStation6 base stations. It allows performing primary processing of GNSS measurement data, calculating TEC and fixing scintillation moments, modeling the ionosphere using the obtained data, storing data and performing ionospheric correction in measurements. As a result of the study, it was proved that the use of the transionospheric sounding method for reconstructing the altitude distribution of electron concentration in different altitude range and would provide operational information about the ionosphere, which is necessary for solving a number of practical problems in the field of many applications. Also, the use of multi-frequency multisystem GNSS equipment and special software will allow achieving the specified accuracy and volume of measurements.

Keywords: global navigation satellite systems (GNSS), GPstation6, international reference ionosphere (IRI), ionosphere, scintillations, total electron content (TEC)

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Authors: I. Shuro

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The crystal structure of Tin Sulfide prepared by certain chemical methods is investigated using High-Resolution Transmission Electron Microscopy (HRTEM), Scanning Electron Microscopy (SEM), and X-ray diffraction (XRD) methods. An anomalous HRTEM Fast Fourier Transform (FFT) exhibited a central scatter of diffraction spots, which is surrounded by secondary clusters of spots arranged in a hexagonal pattern around the central cluster was observed. FFT analysis has revealed a long lattice parameter and mostly viewed along a hexagonal axis where there many columns of atoms slightly displaced from one another. This FFT analysis has revealed that the metal sulfide has a long-range order interwoven chain of atoms in its crystal structure. The observed crystalline structure is inconsistent with commonly observed FFT patterns of chemically synthesized Tin Sulfide nanocrystals and thin films. SEM analysis showed the morphology of a myriad of multi-shaped crystals ranging from hexagonal, cubic, and spherical micro to nanostructured crystals. This study also investigates the presence of quasi-crystals as reflected by the presence of mixed local symmetries.

Keywords: fast fourier transform, high resolution transmission electron microscopy, tin sulfide, crystalline structure

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Authors: A. Nguyen, K. Nguyen, J. Jackson, E. Manlapig

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With the recent advancement in core imaging systems, a large volume of high resolution drill core images can now be collected rapidly. This paper presents a method for rapid prediction of ore-specific breakage parameters from high resolution mineral classified core images. The aim is to allow for a rapid assessment of the variability in ore hardness within a mineral deposit with reduced amount of physical breakage tests. This method sees its application primarily in project evaluation phase, where proper evaluation of the variability in ore hardness of the orebody normally requires prolong and costly metallurgical test work program. Applying this image-based texture analysis method on mineral classified core images, the ores are classified according to their textural characteristics. A small number of physical tests are performed to produce a dataset used for developing the relationship between texture classes and measured ore hardness. The paper also presents a case study in which this method has been applied on core samples from a copper porphyry deposit to predict the ore-specific breakage A*b parameter, obtained from JKRBT tests.

Keywords: geometallurgy, hyperspectral drill core imaging, process simulation, texture analysis

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Authors: Iman Nezamzadeh, Ali Faghih, Behnam Oveisi

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In order to reduce earthquake hazards in urban areas, it is necessary to perform comprehensive studies to understand the dynamics of the active faults and identify potentially high risk areas. The fault slip-rates in Late Quaternary sediment are critical indicators of seismic hazard and also provide valuable data to recognize young crustal deformations. To measure slip-rates accurately, is needed to displacement of geomorphic markers and ages of quaternary sediment samples of alluvial deposit that deformed by movements on fault. In this study we produced information about Intermediate term slip rate of Sabzpushan Fault Zone (SPF) within the central part of the Zagros Mountains of Iran using OSL dating technique to make better analysis of seismic hazard and seismic risk reduction for Shiraz city. For this purpose identifiable geomorphic fluvial surfaces help us to provide a reference frame to determine differential or absolute horizontal and vertical deformation. Optically stimulated luminescence (OSL) is an alternative and independent method of determining the burial age of mineral grains in Quaternary sediments. Field observation and satellite imagery show geomorphic markers that deformed horizontally along the Sabzpoushan Fault. Here, drag folds is forming because of evaporites material of Miocen Formation. We estimate 2.8±0.5 mm/yr (mm/y) horizontal slip rate along the Sabzpushan fault zone, where ongoing deformation is involve with drug folding. The Soltan synclinal structure, close to the Sabzpushan fault, shows slight uplift rate due to active core-extrousion.

Keywords: slip rate, active tectonics, OSL, geomorphic markers, Sabzpushan Fault Zone, Zagros, Iran

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Authors: Michael Regev, Shai Essel, Alexander Katz-Demyanetz

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Magnesium alloys are characterized by good physical properties: They exhibit high strength, are lightweight and have good damping absorption and good thermal and electrical conductivity. Amorphous magnesium alloys, moreover, exhibit higher strength, hardness and a large elastic domain in addition to having excellent corrosion resistance. These above-mentioned advantages make magnesium based metallic glasses attractive for industrial use. Among the various existing magnesium alloys, Mg₆₅Cu₂₅Y₁₀ alloy is known to be one of the best glass formers. In the current study, Mg₆₅Cu₂₅Y₁₀ ribbons were produced by melt spinning, their microstructure was investigated in its as-cast condition, after pressing under 0.5 GPa for 5 minutes under different temperatures - RT, 500C, 1000C, 1500C and 2000C - and after five minute exposure to the above temperatures without pressing. The microstructure was characterized by means of X-ray Diffraction (XRD), Differential Scanning Calorimetry (DSC), High Resolution Scanning Electron Microscope (HRSEM) and High Resolution Transmission Electron Microscopy (HRTEM). XRD and DSC studies showed that the as-cast material had an amorphous character and that the material crystallized during exposure to temperature with or without applying stress. HRTEM revealed that the as-cast Mg65Cu25Y10, although known to be one of the best glass formers, is nano-crystalline rather than amorphous. The current study casts light on the question what an amorphous alloy is and whether there is any clear borderline between amorphous and nano-crystalline alloys.

Keywords: metallic glass, magnesium, melt spinning, amorphous alloys

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Authors: Neda Orak, Mostafa Zarei

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Environmental assessment is an important session in environment management. Since various methods and techniques have been produces and implemented. Remote sensing (RS) is widely used in many scientific and research fields such as geology, cartography, geography, agriculture, forestry, land use planning, environment, etc. It can show earth surface objects cyclical changes. Also, it can show earth phenomena limits on basis of electromagnetic reflectance changes and deviations records. The research has been done on mangrove forests assessment by RS techniques. Mangrove forests quantitative analysis in Basatin and Bidkhoon estuaries was the aim of this research. It has been done by Landsat satellite images from 1975- 2013 and match to ground control points. This part of mangroves are the last distribution in northern hemisphere. It can provide a good background to improve better management on this important ecosystem. Landsat has provided valuable images to earth changes detection to researchers. This research has used MSS, TM, +ETM, OLI sensors from 1975, 1990, 2000, 2003-2013. Changes had been studied after essential corrections such as fix errors, bands combination, georeferencing on 2012 images as basic image, by maximum likelihood and IPVI Index. It was done by supervised classification. 2004 google earth image and ground points by GPS (2010-2012) was used to compare satellite images obtained changes. Results showed mangrove area in bidkhoon was 1119072 m2 by GPS and 1231200 m2 by maximum likelihood supervised classification and 1317600 m2 by IPVI in 2012. Basatin areas is respectively: 466644 m2, 88200 m2, 63000 m2. Final results show forests have been declined naturally. It is due to human activities in Basatin. The defect was offset by planting in many years. Although the trend has been declining in recent years again. So, it mentioned satellite images have high ability to estimation all environmental processes. This research showed high correlation between images and indexes such as IPVI and NDVI with ground control points.

Keywords: IPVI index, Landsat sensor, maximum likelihood supervised classification, Nayband National Park

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

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The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: Michał Maksimczuk, Łukasz Kaczmarek, Tomasz Wejrzanowski

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This study concerns high-resolution X-ray computed microtomography (µCT) and ultrasonic pulse analysis of Cambrian sandstones from a borehole located in the Baltic Sea Coast of northern Poland. µCT and ultrasonic technique are non-destructive methods commonly used to determine the internal structure of reservoir rock sample. The spatial resolution of the µCT images obtained was 27 µm, which enabled the author to create accurate 3-D visualizations of structure geometry and to calculate the ratio of pores volume to the total sample volume. A copper X-ray source filter was used to reduce image artifacts. Furthermore, samples Young’s modulus and Poisson ratio were obtained with use of ultrasonic pulse technique. µCT and ultrasonic pulse technique provide complex information which can be used for explorations and characterization of reservoir rocks.

Keywords: elastic parameters, linear absorption coefficient, northern Poland, tight gas

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: D. Courault, L. Hossard, V. Demarez, E. Ndikumana, D. Ho Tong Minh, N. Baghdadi, F. Ruget

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In the global change context, efficient management of the available resources has become one of the most important topics, particularly for sustainable crop development. Timely assessment with high precision is crucial for water resource and pest management. Rice cultivated in Southern France in the Camargue region must face a challenge, reduction of the soil salinity by flooding and at the same time reduce the number of herbicides impacting negatively the environment. This context has lead farmers to diversify crop rotation and their agricultural practices. The objective of this study was to evaluate this crop diversity both in crop systems and in agricultural practices applied to rice paddy in order to quantify the impact on the environment and on the crop production. The proposed method is based on the combined use of crop models and multispectral data acquired from the recent Sentinel 2 satellite sensors launched by the European Space Agency (ESA) within the homework of the Copernicus program. More than 40 images at fine spatial resolution (10m in the optical range) were processed for 2016 and 2017 (with a revisit time of 5 days) to map crop types using random forest method and to estimate biophysical variables (LAI) retrieved by inversion of the PROSAIL canopy radiative transfer model. Thanks to the high revisit time of Sentinel 2 data, it was possible to monitor the soil labor before flooding and the second sowing made by some farmers to better control weeds. The temporal trajectories of remote sensing data were analyzed for various rice cultivars for defining the main parameters describing the phenological stages useful to calibrate two crop models (STICS and SAFY). Results were compared to surveys conducted with 10 farms. A large variability of LAI has been observed at farm scale (up to 2-3m²/m²) which induced a significant variability in the yields simulated (up to 2 ton/ha). Observations on more than 300 fields have also been collected on land use. Various maps were elaborated, land use, LAI, flooding and sowing, and harvest dates. All these maps allow proposing a new typology to classify these paddy crop systems. Key phenological dates can be estimated from inverse procedures and were validated against ground surveys. The proposed approach allowed to compare the years and to detect anomalies. The methods proposed here can be applied at different crops in various contexts and confirm the potential of remote sensing acquired at fine resolution such as the Sentinel2 system for agriculture applications and environment monitoring. This study was supported by the French national center of spatial studies (CNES, funded by the TOSCA).

Keywords: agricultural practices, remote sensing, rice, yield

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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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: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo

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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.

Keywords: digital terrain models, hydrology tools, strahler method, stream classification

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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: S. Zhuiykov, Zh. Hai, H. Xu, C. Xue

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Unique and distinctive properties could be obtained on such two-dimensional (2D) semiconductor as tungsten trioxide (WO₃) when the reduction from multi-layer to one fundamental layer thickness takes place. This transition without damaging single-layer on a large spatial resolution remained elusive until the atomic layer deposition (ALD) technique was utilized. Here we report the ALD-enabled atomic-layer-precision development of a single layer WO₃ with thickness of 0.77±0.07 nm on a large spatial resolution by using (^tBuN)₂W(NMe₂)₂ as tungsten precursor and H₂O as oxygen precursor, without affecting the underlying SiO₂/Si substrate. Versatility of ALD is in tuning recipe in order to achieve the complete WO₃ with desired number of WO₃ layers including monolayer. Governed by self-limiting surface reactions, the ALD-enabled approach is versatile, scalable and applicable for a broader range of 2D semiconductors and various device applications.

Keywords: Atomic Layer Deposition (ALD), tungsten oxide, WO₃, two-dimensional semiconductors, single fundamental layer

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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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: Sundara Subramanian Karuppasamy, Che Hua Yang

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In this work, the laser ultrasound technique has been used for analyzing and imaging the inner defects in metal blocks. To detect the defects in blocks, traditionally the researchers used piezoelectric transducers for the generation and reception of ultrasonic signals. These transducers can be configured into the sparse and phased array. But these two configurations have their drawbacks including the requirement of many transducers, time-consuming calculations, limited bandwidth, and provide confined image resolution. Here, we focus on the non-contact method for generating and receiving the ultrasound to examine the inner defects in aluminum blocks. A Q-switched pulsed laser has been used for the generation and the reception is done by using Laser Doppler Vibrometer (LDV). Based on the Doppler effect, LDV provides a rapid and high spatial resolution way for sensing ultrasonic waves. From the LDV, a series of scanning points are selected which serves as the phased array elements. The side-drilled hole of 10 mm diameter with a depth of 25 mm has been introduced and the defect is interrogated by the linear array of scanning points obtained from the LDV. With the aid of the Synthetic Aperture Focusing Technique (SAFT) algorithm, based on the time-shifting principle the inspected images are generated from the A-scan data acquired from the 1-D linear phased array elements. Thus the defect can be precisely detected with good resolution.

Keywords: laser ultrasonics, linear phased array, nondestructive testing, synthetic aperture focusing technique, ultrasonic imaging

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Authors: Zahid Khalil, Saad Ul Haque, Asif Khan

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Decision making about identifying suitable sites for any project by considering different parameters is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30-meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pairwise comparison method, also known as Analytical Hierarchy Process (AHP) is taken into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision-making about suitable sites analysis for small dams using geospatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

Keywords: Remote sensing, GIS, AHP, RWH

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Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

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Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

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Authors: Jeff Dickie

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This research paper combined grounded coding and research questions with the objective to investigate conflict resolution in the classroom. The students’ answers concerning teaching were coded according to phrasal meanings which revealed concepts. These concept codes then became input data into theoretical frameworks. The investigation indicated two conflicts: whether the information was valid and whether to make the study effort which was discussed as perceptions of teacher’s competence in helping to learn. The relevant factors in helping to learn were predominately emotional. These factors were important in the negotiation process to develop relationships. Information validity seemed to be the motivator to begin and participate effectively with the learning process. In effect, confidence in the learning negotiation process with the focus towards relationship building with the subject matter seemed to be the motivator to make the study effort.

Keywords: coding, confidence, competence, conflict resolution, risk, trust, relationship building

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Authors: Ibrahim Ercan, Mustafa Arikan

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In recent years, alternative dispute resolution methods have attracted the attention of many country’s legislators. Instead of solving the disputes by litigation, putting the end to a dispute by parties themselves is more important for the preservation of social peace. Therefore, alternative dispute resolution methods (ADR) have been discussed more intensively in Turkey as well as the whole world. After these discussions, Mediation Act was adopted on 07.06.2012 and entered into force on 21.06.2013. According to the Mediation Act, it is only possible to mediate issues arising from the private law. Also, it is not compulsory to go to mediation in Turkish law, it is optional. Therefore, the parties are completely free to choose mediation method in dispute resolution. Mediators need to be a lawyer with experience in five years. Therefore, it is not possible to be a mediator who is not lawyers. Beyond five years of experience, getting education and success in exams about especially body language and psychology is also very important to be a mediator. If the parties compromise as a result of mediation, a document is issued. This document will also have the ability to exercising availability under certain circumstances. Thus, the parties will not need to apply to the court again. On the contrary, they will find the opportunity to execute this document, so they can regain their debts. However, the Mediation Act has entered into force in a period of nearly two years of history; it is possible to say that the interest in mediation is not at the expected level. Therefore, making mediation mandatory for some disputes has been discussed recently. At this point, once the mediation becomes mandatory and good results follows it, this institution will be able to find a serious interest in Turkey. Otherwise, if the results will not be satisfying, the mediation method will be removed.

Keywords: alternative dispute resolution methods, mediation act, mediation, mediator, mediation in Turkey

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Authors: Tahir Saleem, Mohammad Usman, Nadeem Khan

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GPS signals are used for navigation and positioning purposes by a diverse set of users. However, this project intends to utilize the reflected GPS L5 signals for location of target in a region of interest by generating an image that highlights the positions of targets in the area of interest. The principle of bi-static radar is used to detect the targets or any movement or changes. The idea is confirmed by the results obtained during MATLAB simulations. A matched filter based technique is employed in the signal processing to improve the system resolution. The simulation is carried out under different conditions with moving receiver and targets. Noise and attenuation is also induced and atmospheric conditions that affect the direct and reflected GPS signals have been simulated to generate a more practical scenario. A realistic GPS L5 signal has been simulated, the simulation results verify that the detection and imaging of targets is possible by employing reflected GPS using L5 signals and matched filter processing technique with acceptable spatial resolution.

Keywords: GPS, L5 Signal, SAR, spatial resolution

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Authors: Chul Park, Youngseok Kim, Sangsik Choi

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This study developed an electric jig for underwater structure inspection in order to solve the problem of the application of side scan sonar to underwater inspection, and analyzed correlations of empirical data in order to enhance sonar data resolution. For the application of tow-typed sonar to underwater structure inspection, an electric jig was developed. In fact, it was difficult to inspect a cross-section at the time of inspection with tow-typed equipment. With the development of the electric jig for underwater structure inspection, it was possible to shorten an inspection time over 20%, compared to conventional tow-typed side scan sonar, and to inspect a proper cross-section through accurate angle control. The indoor test conducted to enhance sonar data resolution proved that a water depth, the distance from an underwater structure, and a filming angle influenced a resolution and data quality. Based on the data accumulated through field experience, multiple regression analysis was conducted on correlations between three variables. As a result, the relational equation of sonar operation according to a water depth was drawn.

Keywords: underwater structure, SONAR, safety inspection, resolution

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Authors: Barbora Chmelova, Radek Sachl

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Gangliosides are amphipathic membrane lipids. Due to the composition of bulky oligosaccharide chains containing one or more sialic acids linked to the hydrophobic ceramide base, gangliosides are classified among glycosphingolipids. This unique structure induces a high self-aggregating tendency of gangliosides and, therefore, the formation of nanoscopic clusters called nanodomains. Gangliosides are preferentially present in an extracellular membrane leaflet of all human tissues and thus have an impact on a huge number of biological processes, such as intercellular communication, cell signalling, membrane trafficking, and regulation of receptor activity. Defects in their metabolism, impairment of proper ganglioside function, or changes in their organization lead to serious health conditions such as Alzheimer´s and Parkinson´s diseases, autoimmune diseases, tumour growth, etc. This work mainly focuses on ganglioside organization into nanodomains and their dynamics within the plasma membrane. Current research investigates static ganglioside nanodomains characterization; nevertheless, the information about their diffusion is missing. In our study, fluorescence correlation spectroscopy is implemented together with stimulated emission depletion (STED-FCS), which combines the diffraction-unlimited spatial resolution with high temporal resolution. By comparison of the experiments performed on model vesicles containing 4 % of either GM1, GM2, or GM3 and Monte Carlo simulations of diffusion on the plasma membrane, the description of ganglioside clustering, diffusion of nanodomains, and even diffusion of ganglioside molecules inside investigated nanodomains are described.

Keywords: gangliosides, nanodomains, STED-FCS, flourescence microscopy, membrane diffusion

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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: Chander Shekhar Kohli

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In the field of international relations, countries have been experiencing distinct nature of conflicts. But, in the case of Association of Southeast Asian Nations (ASEAN) for a long time, the members have witnessed conflicts, small and large. These conflicts, as a result, have given catastrophic outcomes, such as killings and destroying properties. For the resolution of such conflicts, nonetheless, efforts likewise have been made, simultaneously, in terms of establishing peace and security. In this background, the ASEAN presents a significant example as before it had faced several wars, like Vietnam War, Cambodia conflicts, and so on. This research paper, therefore, strives to examine the ASEAN as a case with the help of both primary and secondary sources. It likewise will be dealt with how changing norms and identity building facilitate the ASEAN countries to deal with their conflicts both internal and external. This paper also will discuss how internal developments within countries affect conflict resolution process as each member of ASEAN is guided by its national interest. It is then argued that conflict resolution in the ASEAN is moving from its existing power-based solution to norms and identity-based solution as member countries have become more dependent on other countries. The research, therefore, is concluded by saying that the conflicts could only be resolved through building norms and common identities, which of course are recognized crucial mechanisms among the ASEAN countries with some exceptions.

Keywords: ASEAN, conflict resolution, norms and identities, peace and security

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

Procedia PDF Downloads 494