GTN-GCN: Real-Time Traffic Forecasting Using Graph Convolutional Network and Transformer by Sadia Naj Jinia, Sumaiya Binte Azad, Rima Akter, Taivan Reza Dipto, Md. Khaliluzzaman

“…The DTM dynamically updates graph structures based on real-time traffic conditions, while GATs focus on identifying critical spatial relationships. GRUs efficiently capture temporal dependencies, and the transformer model captures long-term sequential patterns, providing a comprehensive framework for real-time traffic forecasting. …”
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Spatiotemporal Forecasting of Solar and Wind Energy Production: A Robust Deep Learning Model with Attention Framework by Md. Shadman Abid, Razzaqul Ahshan, Mohammed Al-Abri, Rashid Al Abri

“…Numerical findings demonstrate that the proposed model surpasses other methods by successfully integrating spatial and temporal characteristics.…”
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Statistical analyzes and anomalies of precipitation in cold period in order to understand the effect of climate change on different regions of Iran (1951-2010) by elham yarahmadi, mostafa karampoor, hooshang ghaemi, mohammad moradi, behrouz nasiri

“…Studies show, except on the shores of the Caspian Sea, there is little change between autumn and winter patterns. The average rainfall of the southern shores of the Caspian Sea has decreased to the west and east. in other areas of the country, the spatial and temporal variations of rainfall in the autumn are very highand from the north to the south, the mean decreases and the coefficient of variation and skewness increase. …”
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Optimizing physical education schedules for long-term health benefits by Liang Tan, Qin Chen, Jianwei Wu, Mingbang Li, Tianyu Liu

“…The developed DL model integrates convolutional neural network (CNN) layers to capture spatial features and long short-term memory (LSTM) layers to extract temporal patterns from demographic and activity-related variables. …”
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Deciphering city-level residential AMI data: An unsupervised data mining framework and case study by Han Li, Miguel Heleno, Kaiyu Sun, Wanni Zhang, Luis Rodriguez Garcia, Tianzhen Hong

“…This paper presents a comprehensive data-mining framework for analyzing Advanced Metering Infrastructures data at multiple temporal and spatial scales, beneficial for building owners, operators, and utility companies. …”
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Graph-Attention Diffusion for Enhanced Multivariate Time-Series Anomaly Detection by Vadim Lanko, Ilya Makarov

“…In this article, we propose a novel reconstruction-based approach that enhances normal pattern learning through data masking and leverages diffusion models to capture both temporal and spatial interrelations via graph-attention layers. …”
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Spatiotemporal assessment of ecological quality and driving mechanisms in the Beijing metropolitan area by Aibo Jin, Hui Li, Xiangrong Wang, Ziyao Wang

“…This study investigates the spatial–temporal evolution of ecological quality within the Beijing Metropolitan Area (BMA) from 2000 to 2020 and proposes a comprehensive assessment framework integrating machine learning techniques and spatial heterogeneity analyses. …”
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Developing an early warning land degradation indicator based on geostatistical analysis of Ecosystem Functional Types dynamics by Cristina Domingo-Marimon, Małgorzata Jenerowicz-Sanikowska, Lluís Pesquer, Marek Ruciński, Michał Krupiński, Edyta Woźniak, Anna Foks-Ryznar, Mohammad Abdul Quader

“…Firstly, EFA analysis characterized vegetation productivity and seasonality, revealing temporal trends and spatial patterns of change. Secondly, EFTs served as indicators of change levels. …”
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Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

“…Our framework incorporates dimension alignment strategies and attention mechanisms to capture temporal–spatial complementarity between acoustic feeding signals and visual behavioral patterns. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…The study employs Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to capture complex spatial and temporal patterns, enabling more accurate and timely drought forecasting compared to traditional approaches. …”
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Prediction of land cover changes in an Urban City of Bangladesh using artificial neural network-based cellular automata by Tania Yeasmin, Sourav Karmaker, Md Shafiqul Islam, Irteja Hasan, Saifur Rahman, Mahmudul Hasan

“…This study was conducted to evaluate temporal and spatial changes in Land Use and Land Cover (LULC) for the years 1980, 2000, and 2020 and predict future LULC changes. …”
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Landsat Time Series Reconstruction Using a Closed-Form Continuous Neural Network in the Canadian Prairies Region by Masoud Babadi Ataabadi, Darren Pouliot, Dongmei Chen, Temitope Seun Oluwadare

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Decreasing soil erosion in South China with uncertainties driven by NDVI estimates by Xinqing Lu, Yulian Liang, Tongtiegang Zhao, Xudong Zhu, Zhangcai Qin

“…However, significant discrepancies persist among existing estimates of soil erosion, calling for further evaluation of long-term trends in its magnitude and spatial–temporal dynamics. …”
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City-level emergy metabolism accounts for China’s 281 cities from 2000 to 2020 by Miaohan Tang, Gengyuan Liu, Jingke Hong, Weier Liu, Chao Zhong, Dan Wang, Yuli Shan

“…However, there exists no city-level urban emergy metabolism dataset in China that can support detailed spatial-temporal analysis. In this study, we present a city-level urban emergy metabolism dataset of China’s 281 cities between 2000 and 2020. …”
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A spatiotemporal graph wavelet neural network for traffic flow prediction by Linjie Zhang, Jianfeng Ma

“…Furthermore, we dig the location and time patterns to evaluate the temporal dependence and the spatial proximity correlation. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…The feature map fusion attention mechanism mines the correlation between action features from each channel, assigning higher weights to more relevant features and thereby enhancing the discriminative power of the extracted action representation. A temporal convolution network captures temporal dependencies within the extracted action features, distinguishing between actions with similar spatial characteristics but distinct temporal patterns. …”
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Phenological metrics of the grassland vegetation of Rio Grande do Sul, Brazil by Andreise Moreira, Denise C. Fontana, Tatiana M. Kuplich, Laurindo A. Guasselli

“…ABSTRACT Considering that plant phenology studies allow establishing relationships between phenological patterns of vegetation and changes caused by climate variability, the aim of this study was to obtain phenological metrics for the predominant grassland typologies in Rio Grande do Sul State, Brazil (latitudes 27º 05’ and 33º 45’ S and longitudes 49° 43’ and 57º 39’ W) and to evaluate the spatial-temporal distribution pattern of these metrics under the influence of the subtropical climate variability. …”
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Spatiotemporal Correlation Analysis for the Incidence of Esophageal and Gastric Cancer From 2010 to 2019: Ecological Study by Zixuan Cui, Chen Suo, Yidan Zhao, Shuo Wang, Ming Zhao, Ruilin Chen, Linyao Lu, Tiejun Zhang, Xingdong Chen

“…We classified different risk areas based on the risk ratio (RR) of the 2 cancers in various countries to the global, and the correlation between their RR was evaluated using Pearson correlation coefficient. Temporal trends were quantified by calculating the average annual percent change (AAPC), and the correlation between the temporal trends of both cancers was evaluated using Pearson correlation coefficients. …”
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Geomagnetic Field Based Indoor Landmark Classification Using Deep Learning by Bimal Bhattarai, Rohan Kumar Yadav, Hui-Seon Gang, Jae-Young Pyun

“…We present long short-term memory DRNNs for spatial/temporal sequence learning of magnetic patterns and evaluate their positioning performance on our testbed datasets. …”
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Muscles Activity in the elderly with Balance Impairments in walking under Dual tasks by Elaheh Azadian, Hamidreza Taheri Torbati, Alireza saberi Kakhki

“…  Conclusions: Based on the results, it can be argued that walking under a dual task can change spatial-temporal parameters and muscle activity in gait pattern in the elderly with balance impairment. …”
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