Latest Spatiotemporal Data Mining Research Papers

The newest Spatiotemporal Data Mining papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Spatiotemporal Data Mining so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• A Dataset and Model for Imputing Water Surface Elevation on a Large and Extremely Sparse Spatiotemporal Graph
  Ruben Cartuyvels, Karim Douch, Gabriele Bertoli, Mounia El Baz et al. · arXiv · Sep 10, 2026

  Continuous monitoring of water surface elevation across river networks is critical for flood forecasting, water resource management, and understanding the global water cycle. Yet, the scarcity of in situ gauges across much of the globe cons…

• Spatio-temporal crime prediction and hotspot analysis in Addis Ababa, Ethiopia: a machine learning and geospatial approach
  Esubalew Mulugeta Engda, Ziyen Achamyeleh Mekonnen, Tsegaye Tadesse, Mohammed Adem et al. · Cogent Social Sciences · Sep 9, 2026

  Urban crime remains a major challenge in rapidly expanding cities, affecting public safety, economic development, and social stability. Yet crime prediction research remains concentrated in Western cities with strong data infrastructures, l…

• Spatiotemporal Dynamics and Nonlinear Associations of Eco-Environmental Quality in Mining Areas Using MRSEI and an Object-Based XGBoost-SHAP Framework
  Ting Li, Chaokui Li, Ping Zhang, Yan Mao et al. · Remote Sensing · Sep 9, 2026

  Long-term mining activities can cause complex ecological and environmental problems, including mineral surface exposure, dust-related disturbance, and vegetation degradation, while conventional ecological indices may not fully characterize …

• Hydrochemistry and modeling nitrate concentration in farmland groundwater under different hydrological seasons by integrating hybrid quantum-classical ML, virtual sample generation and AlphaEarth Foundation
  Junjie Xu, Xin Wei, Yilei Yu, Lihu Yang et al. · Hydrology and earth system ... · Sep 8, 2026

  Abstract. Precise seasonal prediction of groundwater nitrate concentrations in intensive agricultural areas faces challenges such as data sparsity, strong spatiotemporal heterogeneity, and complex hydro-biogeochemical processes. To address …

• Spatiotemporal analysis and visualization system design for moving objects based on trajectory data mining
  Xiaodong Ye · Discover Artificial Intelli... · Sep 7, 2026

  Analysis of moving objects is a significant problem in various areas like transportation. However, it has low computational efficiency as well as low accuracy. In order to improve this problem, this study proposed a moving object spatiotemp…

• DCB‐Net: A hybrid depthwise CNN‐BiLSTM approach for fine‐grained imagined speech decoding using EEG signals
  Roopa Golchha, Mridu Sahu, Narendra D. Londhe · ETRI Journal · Sep 6, 2026

  Abstract Imagined speech decoding from phonemes remains challenging owing to low signal‐to‐noise ratios, pronounced inter‐trial variability, and subtle spatiotemporal dynamics embedded in neural signals. In this study, DCB‐Net, a hybrid Dep…

• Lightweight Transformer-based knowledge distillation framework for high-dimensional spatiotemporal radiomics in breast cancer risk prediction
  Haofan Huang, Han Zhou, Kaibin Huang, Jie Yang et al. · Visual Computing for Indust... · Sep 3, 2026

  Abstract Breast cancer exhibits significant spatiotemporal heterogeneity. Traditional radiomics approaches usually rely on low-temporal-resolution imaging and discrete image phases, failing to capture the rapid and continuous kinetic evolut…

• LoRA-TSD: Tangent-Space Spectral Descent for LoRA via Muon-Style Updates
  Dmitrii Andriianov, Andrey Veprikov, Aleksandr Beznosikov · arXiv · Sep 2, 2026

  Low-rank adaptation (LoRA) is the standard way to fine-tune large models, yet when its two factors are trained independently, the update ignores the geometry of the low-rank weight change it induces. We introduce LoRA-TSD, an optimizer that…

• Spatiotemporally Hierarchical Regulation of Zinc Anode Interface via a Multifunctional Additive for High‐Durability Aqueous Zinc‐Ion Batteries
  Ruixuan Bai, Yao Tong, Chongjun Liu, Miaowen Han et al. · Advanced Functional Materials · Aug 31, 2026

  ABSTRACT The practical deployment of aqueous zinc‐ion batteries is severely hindered by spatiotemporally complex interfacial instabilities at the zinc anode, which cannot be sufficiently addressed by conventional single‐function additives. …

• Benchmark-grounded self-supervised contrastive learning for AMI-based distribution grid monitoring
  Ling Zhang, Bowei Yang, Xingsi Ke, Hong Zhao et al. · Frontiers in Artificial Int... · Aug 31, 2026

  Introduction Self-supervised contrastive learning is effective for time-series representation learning, but its deployment in industrial environments remains challenging because of spatiotemporal heterogeneity, domain-specific noise, and la…

• Cognitive UAV-driven agro-surveillance framework for predicting crop stress–induced yield loss using spatio-temporal learning and adaptive irrigation control
  S. Selvakumar, D. Venugopal · Scientific Reports · Aug 29, 2026

  Precision agriculture is becoming more and more of a challenge that requires the use of intelligent systems that are able to predict stress and prevent yield loss before it is too late. Traditional methods of agricultural surveillance are p…

• The Evolution of Spatiotemporal Hotspot Prediction in Public Health: Emerging Paradigms from Spatial Epidemiology to GeoAI and Foundation Models
  Godwin Tetteh Wayoe, Godson Teye Apaflo, Solomon Doe Adjaottor · International Journal of In... · Aug 29, 2026

  Spatiotemporal hotspot prediction has become essential for proactive public health surveillance and intervention. Over several decades, analytical approaches in this field have evolved from classical spatial epidemiology through Bayesian mo…

• Spatial correlation network structure and influencing factors of agricultural ecological efficiency under carbon constraints in China
  Yuanyuan Xiong, Xiaofu Chen, Huijuan Du, Shuqing Xie et al. · Scientific Reports · Aug 29, 2026

  Agricultural ecological efficiency (AEE) is essential for coordinating agricultural development with carbon reduction and ecological sustainability. This study evaluates the spatiotemporal evolution of AEE in 31 provincial-level units in Ch…

• Multi-horizon Student Performance Prediction Using Spatio-temporal Models
  Ghalia Mdaghri-Alaoui, Ilhame Khabbachi, Abdelhamid Zouhair, El-Mokhtar En-Naimi · International journal of in... · Aug 29, 2026

  Predicting academic outcomes early remains a fundamental challenge in learning analytics, particularly when the goal is to identify at-risk students before it is too late to intervene.We introduce a multi-horizon forecasting framework lever…

• A closer-to-brain heterosynaptic learning rule for spatiotemporal spike pattern detection with low-resolution synapse
  Shunta Furuichi, T Kohno · Neuromorphic Computing and ... · Aug 28, 2026

  Abstract The brain is believed to process information efficiently in a different manner from deep learning-based artificial intelligence (AI). Brain-like next-generation AI is gaining attention owing to its potential to perform human-like, …

• Spatial inequalities and contextual correlates of methylphenidate dispensing in Jiangsu Province, China
  Yao Sun, Miao Lu, Yong Zhang, Jin Xu et al. · Frontiers in Pharmacology · Aug 26, 2026

  Introduction Understanding geographic inequalities in psychotropic medication dispensing is important for improving health equity and informing place‐based pharmaceutical management. This study characterized the spatiotemporal distribution …

• Analysis of Drivers of Urban Land-Use Types in Mining Areas Based on Remote Sensing Imagery and Projections of Future Scenarios: A Case Study of Jungar Banner
  Shuo Liu, Lei Chen · Land · Aug 26, 2026

  The evolution of land-use types in mining cities is critical for balancing resource exploitation and ecological sustainability. Taking Jungar Banner as a case study, this study uses remote sensing imagery and auxiliary data (2010–2025) to e…

• A study on the spatiotemporal differences and influencing factors of carbon finance development in Western China
  Liujuan Yu, Qiqing Zhou, Wen Gao · Digital Economy and Sustain... · Aug 25, 2026

  Abstract Against the backdrop of global climate change and China’s “Dual Carbon” goals, carbon finance has emerged as an important market-based instrument for achieving coordinated carbon emission reduction and sustainable economic developm…

• Measuring Enterprise Digital Readiness in Manufacturing: Multi-Dimensional Index Construction, Structural Heterogeneity, and Longitudinal Spatiotemporal Evolution
  Guilei Tan, Rozaini Rosli · Economics and Public Policy · Aug 24, 2026

  Accurately quantifying enterprise digital capability is fundamental to evaluating industrial modernization, yet conventional empirical inquiries predominantly rely on single-dimensional proxy variables or unweighted keyword counts, failing …

• Spatiotemporal Expression of ARRDC5 in Mammalian Spermatogenesis
  LeeLa D. Robinson, Jon M. Oatley · Andrology · Aug 23, 2026

  BACKGROUND: Spermiogenesis is the final phase of sperm development during which haploid round spermatids transform into specialized spermatozoa and occurs across distinct stages of sperm production in the seminiferous epithelium. Abnormalit…

• Research on the spatiotemporal evolution characteristics of NDVI in Shendong mining area based on GEE long-time series remote sensing images
  Zhenhua Wu, Fei Wang, Jie Fang · Scientific Reports · Aug 23, 2026

  Using long-time series remote sensing images to study the spatio-temporal variation characteristics of surface vegetation in mining areas and evaluate the impact of coal development on vegetation coverage has important practical value for e…

• Llm-assisted physics-guided spatiotemporal graph learning for power meteorological disaster evolution
  Shuanglong Jin, Shenbing Hua, Xiaolin Liu, Zongpeng Song et al. · Discover Artificial Intelli... · Aug 22, 2026

  Extreme meteorological events—such as winter cold waves, ice accretion, and typhoons—are increasingly becoming primary triggers that threaten the safe and stable operation of power systems. Their disaster-causing processes exhibit strong sp…

• Spatiotemporal distribution and evolution mechanisms of land subsidence in areas with combined coal mining and groundwater extraction
  Shengtong Di, Ke Li, Ruirui Dong, Qian Zhang et al. · Scientific Reports · Aug 22, 2026

  Land subsidence in areas with combined coal mining and groundwater extraction is characterized by multi-source induction, multi-field coupling, and multi-stage transfer, making its formation and evolution mechanisms particularly complex. Ta…

• Trustworthy Spatio-Temporal Graph Learning for Urban Event Forecasting: A Systematic Survey of Explainability, Fairness, and Their Intersection
  Joy Onyeje Amafonye, Aliyu Suleiman Muhammed, Yusuf Salisu Ibrahim, Austin Olom Ogar · FUDMA Journal of Sciences · Aug 22, 2026

  Spatio-temporal graph neural networks (STGNNs) are widely used for urban event forecasting, including traffic prediction, crime hotspot estimation, air-quality monitoring, and epidemic surveillance. However, their adoption in public governa…

• Analysis of atmospheric air pollutants (CO, NO2, and SO2), through Sentinel-5P images in google earth engine, apurimac region, period 2020–2023
  Walquer Huacani Calsin, Hernán Yari, Edgar Vilca, German Espinoza et al. · Frontiers in Remote Sensing · Aug 21, 2026

  Atmospheric pollution associated with carbon monoxide (CO), nitrogen dioxide (NO 2 ), and sulfur dioxide (SO 2 ) represents an important environmental and public health concern in Andean regions influenced by urban growth, transportation, a…

• CFSR: A tactics-formation coupling recognition framework based on efficient spatio-temporal modelling
  Jing Zhu, Zixuan Zhong, Fengjie Wu, Bangzheng Yin et al. · Journal of King Saud Univer... · Aug 20, 2026

  Abstract Volleyball tactical analysis depends on match statistics, yet how specific formations shape offensive execution remains underexplored. In this paper, we introduce CFSR, motivated by the observation that coaching practice and comput…

• Spatiotemporal evolution of innovation collaboration networks in China’s AI medical device industry: implications for public health governance
  Feng Hu, Huijie Yang, Junyu Cheng, Zhijie Huang et al. · Frontiers in Public Health · Aug 19, 2026

  Artificial intelligence (AI) medical devices have become an important technological foundation for enhancing healthcare system resilience and promoting the equitable allocation of medical innovation resources. However, limited attention has…

• Spatiotemporal evolution and driving factors of vegetation EVI in Xinjiang under different geographic subregions
  Naiming Zhang, Donghuan Chen, Jian Zheng, Liang Cheng et al. · Scientific Reports · Aug 19, 2026

  Xinjiang is a typical arid region. Exploring its vegetation dynamics can deepen our understanding of vegetation evolution in arid zones and provide a scientific basis for formulating targeted vegetation conservation policies for such region…

• Metabarcoding analysis of microbial communities in transition zone ponds along the dead sea shoreline
  Tareq Alhindi, Mustafa Al Kuisi, Mamoon Al‑Rshaidat, Randa Albdaiwi et al. · Scientific Reports · Aug 19, 2026

  The rapid recession of the Dead Sea generates novel extreme aquatic environments, necessitating a comprehensive assessment of their spatiotemporal ecological dynamics and unexplored biodiversity. Consequently, this study investigates the mi…

• On the Fragility of Self-Improving Agents: Variance, Task Order, and Underspecification
  Qinyuan Ye, Yu Li, Yada Pruksachatkun, Jiaxin Zhang et al. · arXiv · Aug 18, 2026

  Memory-based self-improving agents--those that learn from an online stream of tasks and improve over time by maintaining a textual memory bank--have shown great promise in recent literature. However, the reliability aspects of these methods…