Evaluation of Spatio‐Temporal Characteristics of Different Zenith Tropospheric Delay Models in Antarctica

Radio Science ◽  
2020 ◽  
Vol 55 (5) ◽  
Author(s):  
Fei Li ◽  
Qingchuan Zhang ◽  
Shengkai Zhang ◽  
Jintao Lei ◽  
Wenhao Li
Keyword(s):  
Tropospheric Delay ◽  
Temporal Characteristics ◽  
Zenith Tropospheric Delay ◽  
Delay Models ◽  
Spatio Temporal

scholarly journals GEODESY, CARTOGRAPHY, AND AERIAL PHOTOGRAPHY

2021 ◽  
Vol 93,2021 (93) ◽  
pp. 48-58
Author(s):  
Bohdan Palianytsia ◽  
◽  
Bohdan Kladochnyi ◽  
Oksana Palianytsia ◽  
◽  
...  
Keyword(s):  
Initial Step ◽  
3D Models ◽  
Practical Significance ◽  
Tropospheric Delay ◽  
Detailed Model ◽  
Component Distribution ◽  
Zenith Tropospheric Delay ◽  
Moment Distribution ◽  
Graphic Editor ◽  
Spatio Temporal

The purpose of this work is to build 3D models of components of zenith tropospheric delay (ZTD) according to the surface measurements of meteorological values obtained at 100 points, which is almost evenly distributed throughout Ukraine. Method. Saastamoinen formulas calculated dry and wet components of the zenith tropospheric delay. According to the obtained results, the fields of dry and wet components of tropospheric delay were compiled, the fields of their change were constructed using a different number of studied points. Also, with the help of a graphic editor, 3D models of the magnitude one-moment distribution of dry and wet components of the zenith tropospheric delay for the territory of Ukraine were built. Results. Built 3D models of ZTD components; constructed zenith tropospheric delay fields for the territory of Ukraine; a comparison of the distribution of delay components for the specified area and its change during the day are the results of this work. It is established that the dry component becomes more important in the southern and central territory of Ukraine, where the observation points are lower in height and where there is a higher atmospheric pressure, which dominates in the calculation of this component. Accordingly, the wet component is also higher in the southern part of Ukraine, but this is due to higher relative humidity. As a result of the compaction of the network to 100 points, more accurate models of component distribution were obtained, which allowed Ukraine to assess in more detail the value of tropospheric delay for the territory of Ukraine. Further compaction of the network for the territory of Ukraine did not lead to the expected increase in the accuracy of tropospheric delay, as the location of meteorological stations in the country is not uniform enough, and some values of meteorological magnitudes are obtained not by direct measurements but by interpolation. It is necessary to compact the model with reliable meteorological measurements evenly and to control the calculation of components by integrating according to the aerological soundings carried out at individual points to obtain a more detailed model. Scientific novelty and practical significance. The scientific novelty is to build 3D models of tropospheric delay components for the territory of Ukraine at a certain point in time. The practical significance of the performed research is that they can be used as an initial step to build a Spatio-temporal model of tropospheric delay, reflecting the spatial changes of the delay in real-time for a particular area.

Taking a Deep Dive Into The Batteryless Internet of Things With Shepherd

2021 ◽  
Vol 24 (3) ◽  
pp. 5-8
Author(s):  
Kai Geissdoerfer ◽  
Mikołaj Chwalisz ◽  
Marco Zimmerling
Keyword(s):  
Energy Storage ◽  
Internet Of Things ◽  
Sensor Nodes ◽  
Energy Availability ◽  
Deep Dive ◽  
Temporal Fluctuations ◽  
Temporal Characteristics ◽  
Challenges And Opportunities ◽  
Spatio Temporal

Collaboration of batteryless devices is essential to their success in replacing traditional battery-based systems. Without significant energy storage, spatio-temporal fluctuations of ambient energy availability become critical for the correct functioning of these systems. We present Shepherd, a testbed for the batteryless Internet of Things (IoT) that can record and reproduce spatio-temporal characteristics of real energy environments to obtain insights into the challenges and opportunities of operating groups of batteryless sensor nodes.

scholarly journals Regional Zenith Tropospheric Delay Modeling Based on Least Squares Support Vector Machine Using GNSS and ERA5 Data

2021 ◽  
Vol 13 (5) ◽  
pp. 1004
Author(s):  
Song Li ◽  
Tianhe Xu ◽  
Nan Jiang ◽  
Honglei Yang ◽  
Shuaimin Wang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Least Squares ◽  
High Efficiency ◽  
Rapid Development ◽  
Support Vector ◽  
Tropospheric Delay ◽  
Improvement Rate ◽  
Zenith Tropospheric Delay ◽  
Background Data ◽  
Mean Square Errors

The meteorological reanalysis data has been widely applied to derive zenith tropospheric delay (ZTD) with a high spatial and temporal resolution. With the rapid development of artificial intelligence, machine learning also begins as a high-efficiency tool to be employed in modeling and predicting ZTD. In this paper, we develop three new regional ZTD models based on the least squares support vector machine (LSSVM), using both the International GNSS Service (IGS)-ZTD products and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data over Europe throughout 2018. Among them, the ERA5 data is extended to ERA5S-ZTD and ERA5P-ZTD as the background data by the model method and integral method, respectively. Depending on different background data, three schemes are designed to construct ZTD models based on the LSSVM algorithm, including the without background data, with the ERA5S-ZTD, and with the ERA5P-ZTD. To investigate the advantage and feasibility of the proposed ZTD models, we evaluate the accuracy of two background data and three schemes by segmental comparison with the IGS-ZTD of 85 IGS stations in Europe. The results show that the overall average Root Mean Square Errors (RMSE) value of all sites is 30.1 mm for the ERA5S-ZTD, and 10.7 mm for the ERA5P-ZTD. The overall average RMSE is 25.8 mm, 22.9 mm, and 9 mm for the three schemes, respectively. Moreover, the overall improvement rate is 19.1% and 1.6% for the ZTD model with ERA5S-ZTD and ERA5P-ZTD, respectively. In order to explore the reason of the lower improvement for the ZTD model with ERA5P-ZTD, the loop verification is performed by estimating the ZTD values of each available IGS station. In actuality, the monthly improvement rate of estimated ZTD is positive for most stations, and the biggest improvement rate can even reach about 40%. The negative rate mainly comes from specific stations, these stations are located on the edge of the region, near the coast, as well as the lower similarity between the individual verified station and training stations.

scholarly journals Epidemiological and spatio-temporal characteristics of COVID-19 in Rwanda

2021 ◽  
pp. 100058
Author(s):  
Theos Dieudonne Benimana ◽  
Naae Lee ◽  
Seungpil Jung ◽  
Woojoo Lee ◽  
Seung-sik Hwang
Keyword(s):  
Temporal Characteristics ◽  
Spatio Temporal

scholarly journals Spatio-Temporal Characteristics and Obstacle Factors of the Urban-Rural Integration of China’s Shrinking Cities in the Context of Sustainable Development

2021 ◽  
Vol 13 (8) ◽  
pp. 4203
Author(s):  
Bin Du ◽  
Ying Wang ◽  
Jiaxin He ◽  
Wai Li ◽  
Xiaohong Chen
Keyword(s):  
Sustainable Development ◽  
Economic Efficiency ◽  
Formation Mechanisms ◽  
Shrinking Cities ◽  
The Sustainable Development ◽  
Factors Affecting ◽  
Temporal Characteristics ◽  
The North ◽  
Urban Rural ◽  
Spatio Temporal

Based on the fundamental concept of sustainable development, this study empirically analyzes the spatio-temporal characteristics, formation mechanisms and obstacle factors of the urban-rural integration of shrinking cities in China, from 2008 to 2018. The conclusions are as follows: the overall level of the urban-rural integration of shrinking cities in China is low; the internal differences of urban-rural integration are also small, and the changes are slow. Next, the space difference is high in the east and low in the west, high in the south and low in the north. Moreover, differences exist among different levels of urban agglomerations. Urban economic efficiency, urban resources and environment, urban social equity and rural economic efficiency are the main factors affecting the urban-rural integration of shrinking cities in China. Urban and rural economic efficiency are the two most prominent shortcomings that restrict the urban-rural integration of shrinking cities. The spatial resistance mode of each city is more than the two-system resistance; the main resistance of shrinking cities with a higher level of urban-rural integration also comes from the non-economic field. This study expands the research scope that up till now has ignored the discussion of urban-rural issues in the research of shrinking cities at home and abroad, and provides practical guidance for the sustainable development of shrinking cities in China.

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