spatial modeling
Recently Published Documents


TOTAL DOCUMENTS

973
(FIVE YEARS 311)

H-INDEX

47
(FIVE YEARS 8)

2022 ◽  
Vol 14 (1) ◽  
pp. 574
Author(s):  
Emiliia Iakovleva ◽  
Margarita Belova ◽  
Amilcar Soares ◽  
Anton Rassõlkin

This paper examines the possibility of the spatial modelling of the Earth’s natural pulsed-electromagnetic-field measured values, which form a closed profile without the data inside. This geophysical method allows us to map active tectonic movement which breaches the integrity of pipes. During the experiment, 4.5 km of profiles were measured in the Admiralteysky district of St. Petersburg, Russia. Regular electromotive force (EMF) values and anomalous EMF values were obtained, ranging from 0 to 900 µV and above 900 µV, respectively. The anomalous values are associated with tectonic faults in the bedrock. The data obtained are characterized by complex spatial anisotropy associated with the development of two groups of tectonic faults of different orientations. The authors have considered the problems of the spatial modeling of the data obtained. The main problems, the solutions to which should allow the obtaining of adequate models, have been identified. Based on the analysis of the measurement results, geological features of the studied areas, as well as variography, the following possible solutions were proposed: changing the measurement technique; dividing the data array according to the main directions of anisotropy; the need to introduce additional correction coefficients. The problem revealed in this article requires further research on the basis of the obtained results, which will reduce the cost and timing of such studies, and, as a result, give an opportunity to take into account active tectonic disturbances during the construction and scheduled maintenance of underground utilities, which is especially important within the framework of the concept of sustainable development.


2021 ◽  
Author(s):  
Paul C. Rivera

It is important to plan for potential tsunamis during the marine spatial planning process so that land uses may be modified or defensive infrastructure may be erected. Tsunami vortices had been observed during the occurrence and propagation of tsunami waves. Actual observations during the March 2011 Japan tsunami and the Indian Ocean tsunami of December 2004 showed the formation of vortices which lasted for several hours. The Palu tsunami of September 2018 in Indonesia also showed the formation of a tsunami vortex whose centre was photographed by a pilot and appeared as a deep hole in the ocean. Several vortices with various sizes lasted for several hours after the quake and they also generated a loud roar as the giant waves inundated low-lying coastal areas. This essay attempts to describe the development of a model that can explain the formation of tsunami vortices.


2021 ◽  
pp. 1-23
Author(s):  
Mahdi Panahi ◽  
Peyman Yariyan ◽  
Fatemeh Rezaie ◽  
Sung Won Kim ◽  
Alireza Sharifi ◽  
...  

2021 ◽  
Vol 14 (2) ◽  
pp. 158-169
Author(s):  
Aswi Aswi ◽  
Andi Mauliyana ◽  
Muhammad Arif Tiro ◽  
Muhammad Nadjib Bustan

The Covid-19 has exploded in the world since late 2019. South Sulawesi Province has the highest number of Covid-19 cases outside Java Island in Indonesia. This paper aims to determine the most suitable Bayesian spatial conditional autoregressive (CAR) localised models in modeling the relative risk (RR) of Covid-19 in South Sulawesi Province, Indonesia. Bayesian spatial CAR localised models with different hyperpriors were performed adopting a Poisson distribution for the confirmed Covid-19 counts to examine the grouping of Covid-19 cases. All confirmed cases of Covid-19 (19 March 2020-18 February 2021) for each district were included. Overall, Bayesian CAR localised model with G = 5 with a hyperprior IG (1, 0.1) is the preferred model to estimate the RR based on the two criteria used. Makassar and Toraja Utara have the highest and the lowest RR, respectively. The group formed in the localised model is influenced by the magnitude of the mean and variance in the count data between areas. Using suitable Bayesian spatial CAR localised models enables the identification of high-risk areas of Covid-19 cases. This localised model could be applied in other case studies.


Sign in / Sign up

Export Citation Format

Share Document