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Yufeng Wang, Xue Chen and Feng Xue
Spatial epidemiology investigates the patterns and determinants of health outcomes over both space and time. Within this field, Bayesian spatiotemporal models have gained popularity due to their capacity to incorporate spatial and temporal dependencies, ...
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Tao Zhou, Bo Huang, Xiaoqian Liu, Guangqin He, Qiang Gou, Zhihui Huang and Cheng Xie
Large-scale population flow reshapes the economic landscape and is affected by unbalanced urban development. The exploration of migration patterns and their determinants is therefore crucial to reveal unbalanced urban development. However, low-resolution...
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Dmitry Pavlyuk
Transfer learning is a modern concept that focuses on the application of ideas, models, and algorithms, developed in one applied area, for solving a similar problem in another area. In this paper, we identify links between methodologies in two fields: vi...
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Die Zhang, Yong Ge, Xilin Wu, Haiyan Liu, Wenbin Zhang and Shengjie Lai
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accurac...
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Long Ho, Duy Tan Pham, Wout Van Echelpoel, Leacky Muchene, Ziv Shkedy, Andres Alvarado, Juan Espinoza-Palacios, Maria Arevalo-Durazno, Olivier Thas and Peter Goethals
Dissolved oxygen is an essential controlling factor in the performance of facultative and maturation ponds since both take many advantages of algal photosynthetic oxygenation. The rate of this photosynthesis strongly depends on the time during the day an...
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Long Ho, Duy Tan Pham, Wout Van Echelpoel, Leacky Muchene, Ziv Shkedy, Andres Alvarado, Juan Espinoza-Palacios, Maria Arevalo-Durazno, Olivier Thas and Peter Goethals
Dissolved oxygen is an essential controlling factor in the performance of facultative and maturation ponds since both take many advantages of algal photosynthetic oxygenation. The rate of this photosynthesis strongly depends on the time during the day an...
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Minghao Liu, Qingxi Luo, Jianxiang Wang, Lingbo Sun, Tingting Xu and Enming Wang
Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth?s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining...
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Taghreed Alghamdi, Khalid Elgazzar and Taysseer Sharaf
Hierarchical Bayesian models (HBM) are powerful tools that can be used for spatiotemporal analysis. The hierarchy feature associated with Bayesian modeling enhances the accuracy and precision of spatiotemporal predictions. This paper leverages the hierar...
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Wen Tian, Yining Zhang, Ying Zhang, Haiyan Chen and Weidong Liu
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was co...
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Juanjuan Feng, Jia Li, Wenjie Zhong, Junhui Wu, Zhiqiang Li, Lingshuai Kong and Lei Guo
Arctic sea ice prediction is of great practical significance in facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice ...
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Chao Fan, Xiang Que, Zhe Wang and Xiaogang Ma
The urban heat island (UHI) effect is an important topic for many cities across the globe. Previous studies, however, have mostly focused on UHI changes along either the spatial or temporal dimension. A simultaneous evaluation of the spatial and temporal...
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Navid Moradpoor, Mohsen Najarchi and Seyed Mohammad Mirhoseini Hezave
Ilam province is located in the southwest of Iran, and the primary motivation for this research is to study different dimensions of rainfall fluctuations in the Ilam province. This study is of great importance for the management of the environment in ter...
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Piotr A. Werner, Malgorzata Kesik-Brodacka, Karolina Nowak, Robert Olszewski, Mariusz Kaleta and David T. Liebers
This article describes an original methodology for integrating global SIR-like epidemic models with spatial interaction models, which enables the forecasting of COVID-19 dynamics in Poland through time and space. Mobility level, estimated by the regional...
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Alysha van Duynhoven and Suzana Dragicevic
An open problem impeding the use of deep learning (DL) models for forecasting land cover (LC) changes is their bias toward persistent cells. By providing sample weights for model training, LC changes can be allocated greater influence in adjustments to m...
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Purwanto Purwanto, Sugeng Utaya, Budi Handoyo, Syamsul Bachri, Ike Sari Astuti, Kresno Sastro Bangun Utomo and Yulius Eka Aldianto
In this research, we analyzed COVID-19 distribution patterns based on hotspots and space?time cubes (STC) in East Java, Indonesia. The data were collected based on the East Java COVID-19 Radar report results from a four-month period, namely March, April,...
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Pengyuan Wang, Xiao Huang, Joseph Mango, Di Zhang, Dong Xu and Xiang Li
Studying population prediction under micro-spatiotemporal granularity is of great significance for modern and refined urban traffic management and emergency response to disasters. Existing population studies are mostly based on census and statistical yea...
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Qingyong Zhang, Lingfeng Zhou, Yixin Su, Huiwen Xia and Bingrong Xu
Considering the spatial and temporal correlation of traffic flow data is essential to improve the accuracy of traffic flow prediction. This paper proposes a traffic flow prediction model named Dual Spatial Convolution Gated Recurrent Unit (DSC-GRU). In p...
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Mingyang Du, Xuefeng Li, Mei-Po Kwan, Jingzong Yang and Qiyang Liu
Understanding the spatiotemporal variation of high-efficiency ride-hailing orders (HROs) is helpful for transportation network companies (TNCs) to balance the income of drivers through reasonable order dispatch, and to alleviate the imbalance between sup...
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Hiyaw Hatiya Ware, Tarekegn Dejen Mengistu, Bisrat Ayalew Yifru, Sun Woo Chang and Il-Moon Chung
Recharge is a crucial section of water balance for both surface and subsurface models in water resource assessment. However, quantifying its spatiotemporal distribution at a regional scale poses a significant challenge. Empirical and numerical modeling a...
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Yue Zhang, Zimo Zhou, Jesse Van Griensven Thé, Simon X. Yang and Bahram Gharabaghi
Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance...
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