Modeling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data Using FRK by Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Noel Cressie

“…FRK is an R package for spatial and spatio-temporal modeling and prediction with very large data sets that, to date, has only supported linear process models and Gaussian data models. …”
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Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares by Zhongqian Hu, Zezong Chen, Chen Zhao, Xi Chen

“…Coherent S-band radar is a remote sensing observation device with high spatial-temporal resolution and can be used to achieve deterministic sea wave reconstruction and prediction (DSWRP) technology. …”
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Spatial Modeling of Unemployment Rate in Counties of Iran Based on Population and Housing Census Data by Hamed Seifi, Abdollah Jalilian, Azad Khanzadi

“…In these data, the economically active population and the number of unemployed, aged 15 years old or above are categorized by gender and different levels of education in Iran counties. The aim pursued during this research is the spatial modeling of the number of unemployed in counties of Iran, based on gender and education as covariates. …”
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Profiling user segments and spatial clusters of EV uptake through multi-method modeling by Bailing Zhang, Jing Kang

“…However, most existing approaches treat EV adoption as a homogeneous process or rely on fixed-rule models that overlook spatial clustering. This study implements a multi-method approach that combines probabilistic modeling and geospatial analysis to classify and profile EV and conventional vehicle (CV) users. …”
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Thermal dose feedback control systems applied to magnetic nanoparticle hyperthermia by Yash Sharad Lad, Shreeniket Pawar, Nageshwar Arepally, Hayden Carlton, Constantinos Hadjipanayis, Robert Ivkov, Ma’Moun Abu-Ayyad, Anilchandra Attaluri

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A Study of Tool Wear Prediction Based on Digital Twins by LIU Minghao, MAO Xinhui, XIA Wei, YUE Caixu, LIU Xianli

“…This model can deeply extract spatial features and dynamic temporal features, significantly improving prediction accuracy compared to conventional models. …”
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E-scooter's Availability and Social Equity in Minneapolis, MN: A Spatial Modeling Approach by Ahmad Ilderim Tokey

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LEPROSY CASE MODELING IN EAST JAVA USING SPATIAL REGRESSION WITH QUEEN CONTIGUITY WEIGHTING by Toha Saifudin, Marisa Rifada, Karina Rubita Makhbubah, Devira Thania Ramadhanty

“…Among the regression models tested, the spatial error regression model proved most effective, showing an R-Square value of 67.14% and an AIC of 213.023. …”
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From Field to Model: Determining EROSION 3D Model Parameters for the Emerging Biomass Plant <i>Silphium perfoliatum</i> L. to Predict Effects on Water Erosion Processes by Tobias Koch, Peter Aartsma, Detlef Deumlich, Peter Chifflard, Kerstin Panten

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Relative importance of temporal and location features in predicting smoking events by Han Yang, Hang Yu, Michael Kotlyar, Sheena R. Dufresne, Serguei V. S. Pakhomov

“…This study examined the predictive value of temporal and spatial features available from smartphones. …”
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Few-shot hotel industry site selection prediction method based on meta learning algorithms and transportation accessibility by Na Li, Huaishi Wu

“…First, the initial location prediction results are obtained through the meta-model. …”
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Prediction for Various Drought Classes Using Spatiotemporal Categorical Sequences by Rizwan Niaz, Mohammed M. A. Almazah, Xiang Zhang, Ijaz Hussain, Muhammad Faisal

“…Drought frequently spreads across large spatial and time scales and is more complicated than other natural disasters that can damage economic and other natural resources worldwide. …”
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A flexible framework for local-level estimation of the effective reproductive number in geographic regions with sparse data by Md Sakhawat Hossain, Ravi Goyal, Natasha K. Martin, Victor DeGruttola, Mohammad Mihrab Chowdhury, Christopher McMahan, Lior Rennert

“…Methods To overcome this challenge, we propose a two-step approach that incorporates existing $$\:{R}_{t}$$ estimation procedures (EpiEstim, EpiFilter, EpiNow2) using data from geographic regions with sufficient data (step 1), into a covariate-adjusted Bayesian Integrated Nested Laplace Approximation (INLA) spatial model to predict $$\:{R}_{t}$$ in regions with sparse or missing data (step 2). …”
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Brain systems for probabilistic and dynamic prediction: computational specificity and integration. by Jill X O'Reilly, Saad Jbabdi, Matthew F S Rushworth, Timothy E J Behrens

“…We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. …”
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Satellite-Based Prediction of Water Turbidity Using Surface Reflectance and Field Spectral Data in a Dynamic Tropical Lake by Elsa Pereyra-Laguna, Valeria Ojeda-Castillo, Enrique J. Herrera-López, Jorge del Real-Olvera, Leonel Hernández-Mena, Ramiro Vallejo-Rodríguez, Jesús Díaz

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An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction by Zhiguo Xiao, Qi Shen, Changgen Li, Dongni Li, Qian Liu

“…To address these limitations, we propose an adaptive spatiotemporal dynamic graph convolutional network (AST-DGCN) for traffic prediction. Under the encoder-decoder architecture, the proposed model leverages node embedding techniques to extract high-dimensional features, generating time-evolving adaptive graphs through self-attention mechanisms. …”
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Spatiotemporal Dynamics and Potential Distribution Prediction of <i>Spartina alterniflora</i> Invasion in Bohai Bay Based on Sentinel Time-Series Data and MaxEnt Modeling by Qi Wang, Guoli Cui, Haojie Liu, Xiao Huang, Xiangming Xiao, Ming Wang, Mingming Jia, Dehua Mao, Xiaoyan Li, Yihua Xiao, Huiying Li

“…This study employed multi-temporal Sentinel-1/2 imagery (2016–2022) to map and predict the spread of <i>S. alterniflora</i> in Bohai Bay. …”
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Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis. by Nicola A Wardrop, Peter M Atkinson, Peter W Gething, Eric M Fèvre, Kim Picozzi, Abbas S L Kakembo, Susan C Welburn

“…Here we extend this study to account for spatial autocorrelation, incorporate uncertainty in input data and model parameters and undertake predictive mapping for risk of high HAT prevalence in future.…”
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Modified STARIMA model for space-time data by Laura Šaltytė

“… In this paper we propose spatial time series model. ARIMA model class is considered for each location. …”
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Evaluation of Eurasian Snow Cover Fraction Prediction Based on BCC-CSM1.1m by Cheng Fei, Li Qiaoping, Shen Xinyong, Liu Yanju, Wang Jing

“…The model ability to predict Eurasian snow cover fraction (SCF) is evaluated by using the hindcast data during 1984-2019 from the Beijing Climate Center (BCC) Climate Prediction System version 2 (CPSv2), developed based on Climate System Model BCC-CSM1.1m. …”
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