Spatial epidemiology of Tabanus (Diptera: Tabanidae) vectors of Trypanosoma by Roberta Marques, Daniel Jiménez-García, Luis E. Escobar, Tiago Kütter Krolow, Rodrigo Ferreira Krüger

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mNSF: multi-sample non-negative spatial factorization by Yi Wang, Kyla Woyshner, Chaichontat Sriworarat, Genevieve Stein-O’Brien, Loyal A. Goff, Kasper D. Hansen

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A novel surrogate model with deep learning for predicting spacial-temporal pressure in coalbed methane reservoirs by Yukun Dong, Xiaodong Zhang, Jiyuan Zhang, Kuankuan Wu, Shuaiwei Liu

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Flood Classification and Improved Loss Function by Combining Deep Learning Models to Improve Water Level Prediction in a Small Mountain Watershed by Rukai Wang, Ximin Yuan, Fuchang Tian, Minghui Liu, Xiujie Wang, Xiaobin Li, Minrui Wu

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Buzzing towards Resilience: Investigating the Spatial Alignment of the Desert Pallid Bee, <i>Centris pallida</i>, and Its Host Plants in Response to Climate Change by Terese Maxine P. Cruz, Stephen L. Buchmann, Kathleen L. Prudic

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Spatial interpolation of health and demographic variables: Predicting malaria indicators with and without covariates. by Camille Morlighem, Chibuzor Christopher Nnanatu, Corentin Visée, Atoumane Fall, Catherine Linard

“…Overall, socioeconomic indicators were generally better predicted by covariate-based models (e.g., random forest and Bayesian models), while methods using spatial autocorrelation alone (e.g., thin plate splines) performed better for variables with heterogeneous spatial structure, such as ethnicity and malaria prevention indicators. …”
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Graphormer Boosted: Molecular Property Prediction With Enhanced Graph Spatial and Edge Encodings by Sarah A. Fadlallah, Francesc Serratosa, Carme Julia

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MDA-MIM: a radar echo map prediction model integrating multi-scale feature fusion and dual attention mechanism by HU Qiang, GAO Yating, YIN Binli, QU Lianen

“…To better capture the non-stationary characteristics of radar echo data, a self-attention mechanism was introduced into the non-stationary module of the MIM model, dynamically adjusting the weights of different time steps and spatial positions. …”
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Predicting large-scale spatial patterns of marine meiofauna: implications for environmental monitoring by Fabiane Gallucci, Gustavo Fonseca, Danilo C Vieira, Luciana Erika Yaginuma, Paula Foltran Gheller, Simone Brito, Thais Navajas Corbisier

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Investigating Durban’s Morphological Dynamics and Spatial Prediction Techniques for Urban Geography Pedagogy by Tolulope Ayodeji Olatoye, Raymond Nkwenti Fru

“…This study highlighted the transformative potential of geospatial analysis and spatial prediction techniques in using the dynamic morphology of Durban Metropolis as a model for fostering innovative, data-driven learning experiences. …”
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Predicting large-scale spatial patterns of marine meiofauna: implications for environmental monitoring by Fabiane Gallucci, Gustavo Fonseca, Danilo C Vieira, Luciana Erika Yaginuma, Paula Foltran Gheller, Simone Brito, Thais Navajas Corbisier

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A Spatially Informed Machine Learning Method for Predicting Sound Field Uncertainty by Xiangmei Chen, Chao Li, Haibin Wang, Yupeng Tai, Jun Wang, Cyrille Migniot

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Modelling the Current and Future Pollutant Emission from Non-Road Machinery: A Case Study in Shanghai by Rui Chen, Xuerui Yang, Lei Xi, Huajun Zhen, Guangli Xiu

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Predicting communities with high tuberculosis case-finding efficiency to optimise resource allocation in Pakistan: comparing the performance of a negative binomial spatial lag model with a Bayesian machine-learning model by Hasan Tahir, Frank Cobelens, Christina Mergenthaler, Mirjam I Bakker, Tanveer Ahmed, Jake D Mathewson, Daniella Brals, Abdullah Latif, Stephanie Lako, Andreas Werle van der Merwe, Matthys Potgieter, Vincent Meurrens, Zia Samad, Ente Rood

“…A predictive negative binomial regression (NBR) model was created, and the presence of spatial autocorrelation was examined to account for spatial dependencies in the outcome variable. …”
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Late-Life Alcohol Exposure Does Not Exacerbate Age-Dependent Reductions in Mouse Spatial Memory and Brain TFEB Activity by Hao Chen, Kaitlyn Hinz, Chen Zhang, Yssa Rodriguez, Sha Neisha Williams, Mengwei Niu, Xiaowen Ma, Xiaojuan Chao, Alexandria L. Frazier, Kenneth E. McCarson, Xiaowan Wang, Zheyun Peng, Wanqing Liu, Hong-Min Ni, Jianhua Zhang, Russell H. Swerdlow, Wen-Xing Ding

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Exploring and Modeling the Spatial Variability of Soil Erosion in Tana Basin, Northwestern Ethiopia by Derege Tsegaye Meshesha, Anteneh Wubet Belay, Gizachew Ayalew Tiruneh, Enyew Adgo, Tiringo Yilak Alemayehu, M. Chandrakala, José Miguel Reichert

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Modeling Foreground Spatial Variations in 21 cm Gaussian Process Component Separation by Kangning Diao, Richard D. P. Grumitt, Yi Mao

“…Further improvements to the HGP model will require more physically-motivated modeling of foreground spatial variations. …”
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CALFUSE-KAN: A Multi-Scale Feature Fusion Network for Aircraft Trajectory Prediction by Yalan Zhang, Ruxin Sun, Fang Liu, Yongchao Wei

Subjects: “…Trajectory prediction…”
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Solar and Wind 24 H Sequenced Prediction Using L-Transform Component and Deep LSTM Learning in Representation of Spatial Pattern Correlation by Ladislav Zjavka

“…Spatiotemporal correlations between meteo-inputs and wind–solar outputs in an optimal regional scale are crucial for developing robust models, reliable in mid-term prediction time horizons. …”
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Spatial Modeling of Douglas‐Fir Plantations in Italy After 120 Years of Experimentation by Maurizio Marchi, Martina Cocozza, Gabriele Bucci, Paolo Iovieno

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