Towards a global spatial machine learning model for seasonal groundwater level predictions in Germany by S. Kunz, A. Schulz, M. Wetzel, M. Nölscher, T. Chiaburu, F. Biessmann, S. Broda

“…Global ML architectures enable predictions across numerous monitoring wells concurrently using a single model, allowing predictions over a broad range of hydrogeological and meteorological conditions and simplifying model management. …”
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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 recommends the integration of GIS-based predictive modelling into urban geography education, contributing to research knowledge by offering an innovative, data-driven approach that enhances spatial literacy, informs sustainable urban planning, and empowers students with real-world analytical skills for addressing future urban challenges.…”
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Ruxolitinib-dependent reduction of seizure load and duration is accompanied by spatial memory improvement in the rat pilocarpine model of temporal lobe epilepsy by Andrew Carrel, Eleonora Napoli, Kathryn Hixson, Jessica Carlsen, Yasmin Cruz Del Angel, Dana Strode, Nicolas Busquet, Vijay Kumar, Michael F. Wempe, Shelley J. Russek, Amy R. Brooks-Kayal

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Applying Machine Learning Algorithms for Spatial Modeling of Flood Susceptibility Prediction over São Paulo Sub-Region by Temitope Seun Oluwadare, Marina Pannunzio Ribeiro, Dongmei Chen, Masoud Babadi Ataabadi, Saba Hosseini Tabesh, Abiodun Esau Daomi

Subjects: “…flood spatial modeling…”
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Rainfall-induced Landslide Susceptibility Prediction Considering Spatial Heterogeneity by ZHANG Xingfu, JIANG Yuanjun, ABI Erdi

“…DEC-Based Clustering: The DEC model predicted higher landslide densities in high- and very-high-susceptibility zones by capturing spatial heterogeneity. …”
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Bifurcation Branch in a Spatial Heterogeneous Predator–Prey Model with a Nonlinear Growth Rate for the Predator by Lei Kong

“…A strongly coupled predator–prey model in a spatially heterogeneous environment with a Holling type-II functional response and a nonlinear growth rate for the predator is considered. …”
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A Predictive Spatial Model to Quantify the Risk of Air-Travel-Associated Dengue Importation into the United States and Europe by Lauren M. Gardner, David Fajardo, S. Travis Waller, Ophelia Wang, Sahotra Sarkar

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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…In order to better apply the stacking model to the prediction of new infectious diseases, we applied the prediction model based on the COVID-19 dataset to the prediction of the number of AIDS and pulmonary tuberculosis (PTB) cases, and verified the wide applicability of our model in the prediction of infectious diseases.…”
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Testing the Applicability and Transferability of Data-Driven Geospatial Models for Predicting Soil Erosion in Vineyards by Tünde Takáts, László Pásztor, Mátyás Árvai, Gáspár Albert, János Mészáros

“…Predictions used spatially exhaustive, auxiliary, and environmental covariables. …”
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Urban Signalized Intersection Traffic State Prediction: A Spatial–Temporal Graph Model Integrating the Cell Transmission Model and Transformer by Anran Li, Zhenlin Xu, Wenhao Li, Yanyan Chen, Yuyan Pan

“…In this framework, cells are modeled as nodes in a directed graph, with dynamic connections representing variations in signal phases, thereby embedding spatial relationships and signal information within dynamic graphs. …”
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The impact of digital economy on energy conservation and emission reduction: Evidence from prefecture-level cities in China by Cheng Zhang, Yirui Zhang, Hua Zhang, Jiaying You, Xinke Lv, Xinyu Cheng

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Predict the carcinogenicity of compounds with SGCN by Wei Ruobing, He Jiafeng, Qiu Xiaofang, Liu Qi

“…In this paper, 341 kinds of experimental data were obtained, and the spatial atom feature combined with the spatial graph convolutional network(SGCN) was used to establish a model that could predict the carcinogenicity of compounds. …”
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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…In comparative analyses, the proposed network significantly outperforms prevailing trajectory prediction models across multiple dimensions. In this paper, we propose a new deep learning network, and apply it to the real-world engineering challenge of spatial target trajectory prediction in the air traffic management domain.…”
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Vit-Traj: A Spatial–Temporal Coupling Vehicle Trajectory Prediction Model Based on Vision Transformer by Rongjun Cheng, Xudong An, Yuanzi Xu

“…In recent years, data-driven vehicle trajectory prediction models have become a significant research focus, and various spatial–temporal neural network models, based on spatial–temporal data, have been proposed. …”
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Spatial-temporal deep learning model based on Similarity Principle for dock shared bicycles ridership prediction by Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang

“…The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. …”
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An AI-based gravitrap surveillance for spatial interaction analysis in predicting aedes risk by Hsiang-Yu Yuan, Pei-Sheng Lin, Wei-Liang Liu, Tzai-Hung Wen, Yu-Chun Lu, Chun-Hong Chen, Li‑Wei Chen

“…Information from neighboring villages is incorporated into the model to enhance precision of risk prediction. Results The proposed AI gravitrap index integrates the auto-Markov and disease mapping models to enhance sensitivity in risk prediction for Aedes densities. …”
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Prediction of the Spatial Distribution of Petrophysical Properties of Sediment Formations Using Multidimensional Splines by V. V. Lapkovsky, V. A. Kontorovich, K. I. Kanakova, S. E. Ponomareva, B. V. Lunev

“…A small number of direct measurements or their extremely uneven distribution leads to significant model errors. This article explores the possibility of using multidimensional approximation and regression splines, both considering spatially referenced direct observation data and using well log curves statistically linked to the modeled variables. …”
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OceanLSTM: xLSTM with spatial attention for salt spray formation and migration prediction in marine hot-humid environments by Chuan Chen, Ganxin Jie, Jun Wang, Shouhe Wang, Xiaonong Xu

Subjects: “…salt spray prediction…”
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Hydrodynamics Model Identification and Model-Based Control Application of a New Type of AUV by Lunyang Lin, Yuxiang Chen, Hong Xiong, Chunliang Yu, Hong Zhu, Yiyang Xing, Guodong Zheng

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Integrated framework for assessment and spatial prediction of humus layer properties of forest soils by Felix Thomas, Carina Becker, Rainer Petzold, Karsten Schmidt, Thomas Scholten, Ulrike Werban

“…We tested the developed framework in a case study on a forest site in Saxony, investigating C/N ratio, pH value, cation exchange capacity and base saturation. Random Forest model calibration for spatial prediction achieved R2 > 0.9 for all investigated humus layer properties. …”
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