Search results for: spatial and temporal resolution

Authors: Man Guo, Wenyong Tan

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By combining spatial syntax with data obtained from field visits, this paper interprets the internal relationship between spatial morphology and spatial cognition in Lidukou Village. By comparing the obtained data, it is recognized that the spatial integration degree of Lidukou Village is positively correlated with the spatial cognitive intention of local villagers. The part with a higher spatial cognitive degree within the village is distributed along the axis mainly composed of Shuxiang Road. And the accessibility of historical relics is weak, and there is no systematic relationship between them. Aiming at the morphological problem of Lidukou Village, optimization strategies have been proposed from multiple perspectives, such as optimizing spatial mechanisms and shaping spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: (Ted) Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup

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This research details a coverage measure for evaluating the effectiveness of observer node placements in a spatial bipartite network. This coverage measure can be used to optimize the configuration of stationary or mobile spatially oriented observer nodes, or a hybrid of the two, over time in order to fully utilize their capabilities. To demonstrate the practical application of this approach, we construct a SpatioTemporal Bipartite Network (STBN) using real-time crime center (RTCC) camera nodes and NOPD calls for service (CFS) event nodes from New Orleans, La (NOLA). We use the coverage measure to identify optimal placements for moving mobile RTCC camera vans to improve coverage of vulnerable areas based on temporal patterns.

Keywords: coverage measure, mobile node dynamics, Monte Carlo simulation, observer nodes, observable nodes, spatiotemporal bipartite knowledge graph, temporal spatial analysis

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Authors: Yaner Yan, Ning Li, Yajun Qiao, Shuqing An

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Although most studies have focused on assessing and mapping terrestrial ecosystem services, there is still a knowledge gap on coastal ecosystem services and an urgent need to assess them. Lau (2013) clearly defined five types of costal ecosystem services: carbon sequestration, shoreline protection, fish nursery, biodiversity, and water quality. While high-resolution remote sensing can provide the more direct, spatially estimates of biophysical parameters, such as species distribution relating to biodiversity service, and Fluorescence information derived from remote sensing direct relate to photosynthesis, availing in estimation of carbon sequestration and the response to environmental changes in coastal wetland. Here, we review the capabilities of high-resolution and fluorescence remote sesing for describing biodiversity, vegetation condition, ecological processes and highlight how these prodicts may contribute to costal ecosystem service assessment. In so doing, we anticipate rapid progress to combine the high-resolution and fluorescence remote sesing to estimate the spatial pattern of costal ecosystem services.

Keywords: ecosystem services, high resolution, remote sensing, chlorophyll fluorescence

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Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag

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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.

Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling

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Authors: Y. Zheng, M. Busi, A. F. Pedersen, M. A. Beltran, C. Gundlach

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X-ray phase contrast imaging has shown to yield a better contrast compared to conventional attenuation X-ray imaging, especially for soft tissues in the medical imaging energy range. This can potentially lead to better diagnosis for patients. However, phase contrast imaging has mainly been performed using highly brilliant Synchrotron radiation, as it requires high coherence X-rays. Many research teams have demonstrated that it is also feasible using a laboratory source, bringing it one step closer to clinical use. Nevertheless, the requirement of fine gratings and high precision stepping motors when using a laboratory source prevents it from being widely used. Recently, a random phase object has been proposed as an analyzer. This method requires a much less robust experimental setup. However, previous studies were done using a particular X-ray source (liquid-metal jet micro-focus source) or high precision motors for stepping. We have been working on a much simpler setup with just small modification of a commercial bench-top micro-CT (computed tomography) scanner, by introducing a piece of sandpaper as the phase analyzer in front of the X-ray source. However, it needs a suitable algorithm for speckle tracking and 3D reconstructions. The precision and sensitivity of speckle tracking algorithm determine the resolution of the system, while the 3D reconstruction algorithm will affect the minimum number of projections required, thus limiting the temporal resolution. As phase contrast imaging methods usually require much longer exposure time than traditional absorption based X-ray imaging technologies, a dynamic phase contrast micro-CT with a high temporal resolution is particularly challenging. Different reconstruction methods, including neural network based techniques, will be evaluated in this project to increase the temporal resolution of the phase contrast micro-CT. A Monte Carlo ray tracing simulation (McXtrace) was used to generate a large dataset to train the neural network, in order to address the issue that neural networks require large amount of training data to get high-quality reconstructions.

Keywords: micro-ct, neural networks, reconstruction, speckle-based x-ray phase contrast

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Authors: M. Dagim Yoseph, M. K. Savage, A. D. Jolly, C. J. Ebinger

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Whakaari/White Island has been the most active New Zealand volcano in the 21st century, producing small phreatic and phreatomagmatic eruptions, which are hard to predict. The most recent eruption occurred in 2019, tragically claiming the lives of 22 individuals and causing numerous injuries. We employed shear-wave splitting analyses to investigate variations in anisotropy between 2018 and 2020, during quiescence, unrest, and the eruption. We examined spatial and temporal variations in 3499 shear-wave splitting and 2656 V_p/V_s ratio measurements. Comparing shear-wave splitting parameters from similar earthquake paths across different times indicates that the observed temporal changes are unlikely to result from variations in earthquake paths through media with spatial variability. Instead, these changes may stem from variations in anisotropy over time, likely caused by changes in crack alignment due to stress or varying fluid content.

Keywords: background seismic waves, fast orientations, seismic anisotropy, V_p/V_s ratio

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Authors: Elizabeth M. Annoni, Elena G. Tolkacheva

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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that is a known prognostic marker for stroke, heart failure and death. Reentrant mechanisms of rotor formation, which are stable electrical sources of cardiac excitation, are believed to cause AF. No existing commercial mapping systems have been demonstrated to consistently and accurately predict rotor locations outside of the pulmonary veins in patients with persistent AF. There is a clear need for robust spatio-temporal techniques that can consistently identify rotors using unique characteristics of the electrical recordings at the pivot point that can be applied to clinical intracardiac mapping. Recently, we have developed four new signal analysis approaches – Shannon entropy (SE), Kurtosis (Kt), multi-scale frequency (MSF), and multi-scale entropy (MSE) – to identify the pivot points of rotors. These proposed techniques utilize different cardiac signal characteristics (other than local activation) to uncover the intrinsic complexity of the electrical activity in the rotors, which are not taken into account in current mapping methods. We validated these techniques using high-resolution optical mapping experiments in which direct visualization and identification of rotors in ex-vivo Langendorff-perfused hearts were possible. Episodes of ventricular tachycardia (VT) were induced using burst pacing, and two examples of rotors were used showing 3-sec episodes of a single stationary rotor and figure-8 reentry with one rotor being stationary and one meandering. Movies were captured at a rate of 600 frames per second for 3 sec. with 64x64 pixel resolution. These optical mapping movies were used to evaluate the performance and robustness of SE, Kt, MSF and MSE techniques with respect to the following clinical limitations: different time of recordings, different spatial resolution, and the presence of meandering rotors. To quantitatively compare the results, SE, Kt, MSF and MSE techniques were compared to the “true” rotor(s) identified using the phase map. Accuracy was calculated for each approach as the duration of the time series and spatial resolution were reduced. The time series duration was decreased from its original length of 3 sec, down to 2, 1, and 0.5 sec. The spatial resolution of the original VT episodes was decreased from 64x64 pixels to 32x32, 16x16, and 8x8 pixels by uniformly removing pixels from the optical mapping video.. Our results demonstrate that Kt, MSF and MSE were able to accurately identify the pivot point of the rotor under all three clinical limitations. The MSE approach demonstrated the best overall performance, but Kt was the best in identifying the pivot point of the meandering rotor. Artifacts mildly affect the performance of Kt, MSF and MSE techniques, but had a strong negative impact of the performance of SE. The results of our study motivate further validation of SE, Kt, MSF and MSE techniques using intra-atrial electrograms from paroxysmal and persistent AF patients to see if these approaches can identify pivot points in a clinical setting. More accurate rotor localization could significantly increase the efficacy of catheter ablation to treat AF, resulting in a higher success rate for single procedures.

Keywords: Atrial Fibrillation, Optical Mapping, Signal Processing, Rotors

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Authors: Zhenming Wang, Jun Zhu, Yuchen Yang, Ning Zhao

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In the present paper, an alternative framework is proposed to construct a class of finite difference multi-resolution nested weighted essentially non-oscillatory (WENO) schemes with an increasingly higher order of accuracy for solving inviscid Euler equations. These WENO schemes firstly obtain a set of reconstruction polynomials by a hierarchy of nested central spatial stencils, and then recursively achieve a higher order approximation through the lower-order precision WENO schemes. The linear weights of such WENO schemes can be set as any positive numbers with a requirement that their sum equals one and they will not pollute the optimal order of accuracy in smooth regions and could simultaneously suppress spurious oscillations near discontinuities. Numerical results obtained indicate that these alternative finite-difference multi-resolution nested WENO schemes with different accuracies are very robust with low dissipation and use as few reconstruction stencils as possible while maintaining the same efficiency, achieving the high-resolution property without any equivalent multi-resolution representation. Besides, its finite volume form is easier to implement in unstructured grids.

Keywords: finite-difference, WENO schemes, high order, inviscid Euler equations, multi-resolution

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Authors: Shu Tao

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Based on a global fuel consumption data product (PKU-FUEL-2007) compiled recently and a series of databases for emission factors of various sources, global emission inventories of a number of greenhouse gases and air pollutants, including CO2, CO, SO2, NOx, primary particulate matter (total, PM 10, and PM 2.5), black carbon, organic carbon, mercury, volatile organic carbons, and polycyclic aromatic hydrocarbons, from combustion sources have been developed. The inventories feather high spatial and sectorial resolutions. The spatial resolution of the inventories are 0.1 by 0.1 degree, based on a sub-national disaggregation approach to reduce spatial bias due to uneven distribution of per person fuel consumption within countries. The finely resolved inventories provide critical information for chemical transport modeling and exposure modeling. Emissions from more than 60 sources in energy, industry, agriculture, residential, transportation, and wildfire sectors were quantified in this study. With the detailed sectorial information, the inventories become an important tool for policy makers. For residential sector, a set of models were developed to simulate temporal variation of fuel consumption, consequently pollutant emissions. The models can be used to characterize seasonal as well as inter-annual variations in the emissions in history and to predict future changes. The models can even be used to quantify net change of fuel consumption and pollutant emissions due to climate change. The inventories has been used for model ambient air quality, population exposure, and even health effects. A few examples of the applications are discussed.

Keywords: air pollutants, combustion, emission inventory, sectorial information

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Authors: Bikramjit Goswami, Manoranjan Kalita

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Active microwave remote sensing is useful in remote sensing applications in cloud-covered regions in the world. Because of high spatial resolution, the spatial variations of land cover can be monitored in greater detail using synthetic aperture radar (SAR). Inundation is studied using the SAR images obtained from Sentinel-1A in both VH and VV polarizations in the present experimental study. The temporal variation of the SAR scattering coefficient values for the area gives a good indication of flood and its boundary. The study area is the district of Morigaon in the state of Assam in India. The period of flood monitoring study is the monsoon season of the year 2017, during which high flood occurred in the state of Assam. The variation of microwave scattering value shows a distinctive indication of flood from the non-flooded period. Frequent monitoring of flood in a large area (10 km x 10 km) using passive microwave sensing and pin-pointing the actual flooded portions (5 m x 5 m) within the flooded area using active microwave sensing, can be a highly useful combination, as revealed by the present experimental results.

Keywords: active remote sensing, flood monitoring, microwave remote sensing, synthetic aperture radar

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Authors: Nguyen Tien Thanh, Günter Meon

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Precipitation plays a key role in water cycle, defining the local climatic conditions and in ecosystem. It is also an important input parameter for water resources management and hydrologic models. With spatial continuous data, a certainty of discharge predictions or other environmental factors is unquestionably better than without. This is, however, not always willingly available to acquire for a small basin, especially for coastal region in Vietnam due to a low network of meteorological stations (30 stations) on long coast of 3260 km2. Furthermore, available gridded precipitation datasets are not fine enough when applying to hydrologic models. Under conditions of global warming, an application of spatial interpolation methods is a crucial for the climate change impact studies to obtain the spatial continuous data. In recent research projects, although some methods can perform better than others do, no methods draw the best results for all cases. The objective of this paper therefore, is to investigate different spatial interpolation methods for daily precipitation over a small basin (approximately 400 km2) located in coastal region, Southern Vietnam and find out the most efficient interpolation method on this catchment. The five different interpolation methods consisting of cressman, ordinary kriging, regression kriging, dual kriging and inverse distance weighting have been applied to identify the best method for the area of study on the spatio-temporal scale (daily, 10 km x 10 km). A 30-year precipitation database was created and merged into available gridded datasets. Finally, observed changes in constructed precipitation were performed. The results demonstrate that the method of ordinary kriging interpolation is an effective approach to analyze the daily precipitation. The mixed trends of increasing and decreasing monthly, seasonal and annual precipitation have documented at significant levels.

Keywords: interpolation, precipitation, trend, vietnam

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Authors: Hanyu Wang, Guangdong Wang

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County-level areas serve as vital spatial units for advancing new urbanization and implementing the principles of low-carbon development, representing critical regions where conflicts between the two are pronounced. Using the 142 county-level units in the Chengdu-Chongqing city clusters as a case study, a coupled coordination model is employed to investigate the coupled coordination relationship and its spatiotemporal evolution between county-level new urbanization and low-carbon development levels. Results indicate that (1) from 2005 to 2020, the overall levels of new urbanization and low-carbon development in the Chengdu-Chongqing city clusters showed an upward trend but with significant regional disparities. The new urbanization level exhibited a spatial differentiation pattern of "high in the suburban areas, low in the distant suburbs, and some counties standing out." The temporal change in low-carbon development levels was not pronounced, yet spatial disparities were notable. (2) The overall coupling coordination degree between new urbanization and low-carbon development is transitioning from barely coordinated to moderately coordinated. The lag in new urbanization levels serves as a primary factor constraining the coordinated development of most counties. (3) Based on the temporal evolution of development states, all county units can be categorized into four types: coordinated demonstration areas, synergistic improvement areas, low-carbon transformation areas, and development lag areas. The research findings offer crucial reference points for spatial planning and the formulation of low-carbon development policies.

Keywords: county units, coupling coordination, low-carbon development, new urbanization

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Authors: Krzysztof Malczewski

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Magnetic Resonance Imaging (MRI) reconstruction algorithm using compressed sensing is presented in this paper. It is exhibited that the offered approach improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were conventionally assumed necessary. Magnetic Resonance Imaging (MRI) is a fundamental medical imaging method struggles with an inherently slow data acquisition process. The use of CS to MRI has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the objective is to combine super-resolution image enhancement algorithm with CS framework benefits to achieve high resolution MR output image. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. The presented algorithm considers the cardiac and respiratory movements.

Keywords: super-resolution, MRI, compressed sensing, sparse-sense, image enhancement

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

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22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: drinking water reservoir, multivariate analysis, physico-chemical parameters, water quality

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Authors: Leng Jian-Wei, Wang Lai-Jun, Li Ye

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In order to measure and analyze the transportation situation within the counties of Shaanxi province over a certain period of time and to promote the province's future transportation planning and development, this paper proposes a reasonable layout plan and compares model rationality. The study uses entropy weight method to measure the transportation advantages of 107 counties in Shaanxi province from three dimensions: road network density, trunk line influence and location advantage in 2013 and 2021, and applies spatial autocorrelation analysis method to analyze the spatial layout and development trend of county-level transportation, and conducts ordinary least square (OLS)regression on transportation impact factors and other influencing factors. The paper also compares the regression fitting degree of the Geographically weighted regression(GWR) model and the OLS model. The results show that spatially, the transportation advantages of Shaanxi province generally show a decreasing trend from the Weihe Plain to the surrounding areas and mainly exhibit high-high clustering phenomenon. Temporally, transportation advantages show an overall upward trend, and the phenomenon of spatial imbalance gradually decreases. People's travel demands have changed to some extent, and the demand for rapid transportation has increased overall. The GWR model regression fitting degree of transportation advantages is 0.74, which is higher than the OLS regression model's fitting degree of 0.64. Based on the evolution of transportation advantages, it is predicted that this trend will continue for a period of time in the future. To improve the transportation advantages of Shaanxi province increasing the layout of rapid transportation can effectively enhance the transportation advantages of Shaanxi province. When analyzing spatial heterogeneity, geographic factors should be considered to establish a more reliable model

Keywords: traffic dominance, GWR model, spatial autocorrelation analysis, temporal and spatial evolution

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Authors: Sun fang, Zhang Wenxin

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This paper establishes an evaluation index system for spatio-temporal patterns of urbanization, with the county as research unit. We use the Entropy Weight method, coefficient variance, the Theil index and ESDA-GIS to analyze spatial patterns and evolutionary characteristics of New-Type Urbanization in the Central Plains Economic Region (CPER) between 2000 and 2011. Results show that economic benefit, non-agricultural employment level and level of market development are the most important factors influencing the level of New-Type Urbanization in the CPER; overall regional differences in New-Type Urbanization have declined while spatial correlations have increased from 2000 to 2011. The overall spatial pattern has changed little, however; differences between the western and eastern areas of the CPER are clear, and the pattern of a strong west and weak east did not change significantly over the study period. Areas with high levels of New-Type Urbanization were mostly distributed along the Beijing-Guangzhou and LongHai Railways on both sides, a new influx of urbanization was tightly clustered around ZhengZhou in the Central Henan Urban Agglomeration, but this trend was found to be weakening slightly. The level of New-Type Urbanization in municipal districts was found to be much higher than it was in the county generally. Provincial borders experienced a lower rate of growth and a lower level of New-Type Urbanization than did any other areas, consistently forming clusters of cold spots and sub-cold spots. The analysis confirms that historical development, location, and diffusion effects of urban agglomeration are the main drivers of changes in New-Type Urbanization patterns in CPER.

Keywords: new-type urbanization, spatial pattern, central plains economic region, spatial evolution

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Authors: Guangtong Xu, Yi He

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Like most historic and cultural cities in China, the historic urban area of Jingmen city is facing a typical spatial problem of fragmentation and fuzzification. This study focuses on exploring a method for evaluating the existing values of historic urban area based on spatial prototype, a concept introduced into urban morphology from 'Archetype' in architectural typology. As the spatial elements and built-up relationship of historic city, spatial prototype has habitual structural characteristics and formal modulus. It is the inherent logic and order rules behind the scattered historic environment, providing a clue to understand the spatial characteristics and a basis for guiding the construction and conservation in historic urban areas. Three criteria, the resolution of historical elements, the completeness of historical structure and the renewal potential of associated land, were selected to construct the integrated assessment system. These three dimensions are linked to the spatial prototype and its constituent elements, as well as the transformation relationship in ancient and present day. The results showed that historic urban areas have changed from a holistic city to different existing types dominated by their historic structure elements. It is necessary to improve the pertinence of planning strategies and develop diversified management measures in the conservation scope of historic urban area. Moreover, a constructive-conservation strategy should be put forward to enhance the integrity of historic urban area based on the trace of spatial prototype and evaluation results.

Keywords: constructive conservation, existing value, historic urban area, spatial prototype

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Authors: Kazım Kaba, Erdem Erdi, M. Akif Erdoğan, H. Mustafa Kandırmaz

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Rainfall is crucial data source for very different discipline such as agriculture, hydrology and climate. Therefore rain rate should be known well both spatial and temporal for any area. Rainfall is measured by using rain-gauge at meteorological ground stations traditionally for many years. At the present time, rainfall products are acquired from radar and satellite images with a temporal and spatial continuity. In this study, we investigated the accuracy of these rainfall data according to rain-gauge data. For this purpose, we used Adana-Hatay radar hourly total precipitation product (RN1) and Meteosat convective rainfall rate (CRR) product over Seyhan plain. We calculated daily rainfall values from RN1 and CRR hourly precipitation products. We used the data of rainy days of four stations located within range of the radar from October 2013 to November 2015. In the study, we examined two rainfall data over Seyhan plain and the correlation between the rain-gauge data and two raster rainfall data was observed lowly.

Keywords: meteosat, radar, rainfall, rain-gauge, Turkey

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Authors: Nidhal Azawi

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Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

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Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

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Authors: Armin Rahimi

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The Gravity Recovery and Climate Experiment (GRACE) has been a very successful project in determining math redistribution within the Earth system. Large deformations caused by earthquakes are in the high frequency band. Unfortunately, GRACE is only capable to provide reliable estimate at the low-to-medium frequency band for the gravitational changes. In this study, we computed the gravity changes after the 2012 Mw8.6 Indian Ocean earthquake off-Sumatra using the GRACE Level-2 monthly spherical harmonic (SH) solutions released by the University of Texas Center for Space Research (UTCSR). Moreover, we calculated gravity changes using different fault models derived from teleseismic data. The model predictions showed non-negligible discrepancies in gravity changes. However, after removing high-frequency signals, using Gaussian filtering 350 km commensurable GRACE spatial resolution, the discrepancies vanished, and the spatial patterns of total gravity changes predicted from all slip models became similar at the spatial resolution attainable by GRACE observations, and predicted-gravity changes were consistent with the GRACE-detected gravity changes. Nevertheless, the fault models, in which give different slip amplitudes, proportionally lead to different amplitude in the predicted gravity changes.

Keywords: undersea earthquake, GRACE observation, gravity change, dislocation model, slip distribution

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Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

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Authors: Varsha Hemant Patil, Swati A. Bhavsar, Abolee H. Patil

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Image quality assessment plays an important role in image evaluation. This paper aims to present an investigation of classic techniques in use for image quality assessment, especially for super-resolution imaging. Researchers have contributed a lot towards the development of super-resolution imaging techniques. However, not much attention is paid to the development of metrics for testing the performance of developed techniques. In this paper, the study report of existing image quality measures is given. The paper classifies reviewed approaches according to functionality and suitability for super-resolution imaging. Probable modifications and improvements of these to suit super-resolution imaging are presented. The prime goal of the paper is to provide a comprehensive reference source for researchers working towards super-resolution imaging and suggest a better framework for measuring the performance of super-resolution imaging techniques.

Keywords: interpolation, MSE, PSNR, SSIM, super resolution

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Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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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: Said Ettaieb, Kamel Hamrouni, Su Ruan

Abstract:

This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

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Authors: Mirvat Shamseddine, Issam Lakkis

Abstract:

We present an efficient, three-dimensional parallel multi-scale Direct Simulation Monte Carlo (DSMC) algorithm for the simulation of unsteady rarefied gas flows in micro/nanosystems. The algorithm employs a novel spatiotemporal adaptivity scheme. The scheme performs a fully dynamic multi-level grid adaption based on the gradients of flow macro-parameters and an automatic temporal adaptation. The computational domain consists of a hierarchical octree-based Cartesian grid representation of the flow domain and a triangular mesh for the solid object surfaces. The hybrid mesh, combined with the spatiotemporal adaptivity scheme, allows for increased flexibility and efficient data management, rendering the framework suitable for efficient particle-tracing and dynamic grid refinement and coarsening. The parallel algorithm is optimized to run DSMC simulations of strongly unsteady, non-equilibrium flows over multiple cores. The presented method is validated by comparing with benchmark studies and then employed to improve the design of micro-scale hotwire thermal sensors in rarefied gas flows.

Keywords: DSMC, oct-tree hierarchical grid, ray tracing, spatial-temporal adaptivity scheme, unsteady rarefied gas flows

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Authors: Lazhar Belkhiri, Ammar Tiri, Lotfi Mouni, Fatma Elhadj Lakouas

Abstract:

This study evaluates the surface water quality in the Kebir Rhumel Basin by analyzing hydrochemical parameters. To assess spatial and temporal variations in water quality, we applied the Water Quality Index (WQI), Mann-Kendall (MK) trend analysis, and hierarchical cluster analysis (HCA). Monthly measurements of eleven hydrochemical parameters were collected across eight stations from January 2016 to December 2020. Calcium and sulfate emerged as the dominant cation and anion, respectively. WQI analysis indicated a high incidence of poor water quality at stations Ain Smara (AS), Beni Haroune (BH), Grarem (GR), and Sidi Khalifa (SK), where 89.5%, 90.6%, 78.2%, and 62.7% of samples, respectively, fell into this category. The MK trend analysis revealed a significant upward trend in WQI at Oued Boumerzoug (ON) and SK stations, signaling temporal deterioration in these areas. HCA grouped the dataset into three clusters, covering approximately 22%, 30%, and 48% of the months, respectively. Within these clusters, specific stations exhibited elevated WQI values: GR and ON in the first cluster, OB and SK in the second, and AS, BH, El Milia (EM), and Hammam Grouz (HG) in the third. Furthermore, approximately 38%, 41%, and 38% of samples in clusters one, two, and three, respectively, were classified as having poor water quality. These findings provide essential insights for policymakers in formulating strategies to restore and manage surface water quality in the region.

Keywords: surface water quality, water quality index (WQI), Mann-Kendall Trend Analysis, hierarchical cluster analysis (HCA), spatial-temporal distribution, Kebir Rhumel Basin

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Authors: Hiroyuki Aoki

Abstract:

The physical properties of polymer materials are dependent on the conformation and molecular motion of a polymer chain. Therefore, the structure and dynamic behavior of the single polymer chain have been the most important concerns in the field of polymer physics. However, it has been impossible to directly observe the conformation of the single polymer chain in a bulk medium. In the current work, the novel techniques to study the conformation and dynamics of a single polymer chain are proposed. Since a fluorescence method is extremely sensitive, the fluorescence microscopy enables the direct detection of a single molecule. However, the structure of the polymer chain as large as 100 nm cannot be resolved by conventional fluorescence methods because of the diffraction limit of light. In order to observe the single chains, we developed the labeling method of polymer materials with a photo-switchable dye and the super-resolution microscopy. The real-space conformational analysis of single polymer chains with the spatial resolution of 15-20 nm was achieved. The super-resolution microscopy enables us to obtain the three-dimensional coordinates; therefore, we succeeded the conformational analysis in three dimensions. The direct observation by the nanometric optical microscopy would reveal the detailed information on the molecular processes in the various polymer systems.

Keywords: polymer materials, single molecule, super-resolution techniques, conformation

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Authors: Man Guo

Abstract:

This paper delves into the intricate interplay between spatial morphology and spatial cognition in Lidukou Village, utilizing a combined approach of spatial syntax and field data. Through a comparative analysis of the gathered data, it emerges that the spatial integration level of Lidukou Village exhibits a direct positive correlation with the spatial cognitive preferences of its inhabitants. Specifically, the areas within the village that exhibit a higher degree of spatial cognition are predominantly distributed along the axis primarily defined by Shuxiang Road. However, the accessibility to historical relics remains limited, lacking a coherent systemic relationship. To address the morphological challenges faced by Lidukou Village, this study proposes optimization strategies that encompass diverse perspectives, including the refinement of spatial mechanisms and the shaping of strategic spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

Procedia PDF Downloads 42