Fuel detection in forest environments training deep learners with smartphone imagery by F. Pirotti, F. Pirotti, A. Carmelo, E. Kutchartt, E. Kutchartt, E. Kutchartt

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The Process of Smartening Road Traffic Management Systems Using Open-Source Solutions: Simulating Traffic Flow, Volume, Speed and Its Impact on Road Safety in a Digital Twin Platfo... by R. Saki, A. Toomanian, N. Neysani Samany, A. Rajabifard

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Virtual Reality for Immersive Visualisation of Turkish Cultural Heritages by T. P. Kersten, G. Büyüksalih

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Assessment of economic well-being in South Africa based on remote sensing transfer learning by L. Wang, L. Wang, T. Long, T. Long, E. Adam

“…However, comprehensive and spatially clear data on environmental conditions and socio-economic well-being remain scarce, preventing a thorough analysis of intersecting inequalities. …”
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AGBD: A Global-scale Biomass Dataset by G. Sialelli, T. Peters, J. D. Wegner, K. Schindler

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Urban Change Detection in Tirana, Albania (2000–2025) Using Remote Sensing and Open Geospatial Data by L. Haxhiu, B. Aliaj

“…Urban change is assessed and modeled using the MOLUSCE plugin in QGIS, which enables both quantification and prediction of land use transformations based on historical trends and infrastructure development. …”
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Uncertainty Estimation for Photogrammetric Point Clouds of UAV Imagery by D. Huang, D. Huang, D. Huang, R. Qin, R. Qin, R. Qin, R. Qin

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Large-scale Thematic Mapping of Volcanic Domes in Armenia Based on Ultra-high Resolution Data by A. Ponomareva, A. Medvedev, A. Medvedev

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Spatio-temporal characterization of precipitation in the Middle and Lower Paraguay Basin based on satellite products and weather station data by R. Villalba, R. Villalba, A. Ferral, J. Baéz, J. Kurita, V. H. Gauto, J. C. Bertoni

“…The validation between the precipitation data obtained from the Giovanni platform and conventional weather station data, through correlation and linear regression analysis, revealed a strong and statistically significant relationship, indicating that the satellite model is suitable for predicting precipitation, although not perfect. …”
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Prioritizing perturbation-responsive gene patterns using interpretable deep learning by Yan Cui, Zhiyuan Yuan

“…Its spatially-informed modeling ensures scalability to large spatial datasets, and we further decouple spatial and non-spatial components to enhance interpretability. …”
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Autoencoder-Driven Fiducial Landmark Identification in 3D Brain MRI for Neuroimaging Alignment by G. Deepali, H. Anitha, B. P. Swathi, M. V. Suhas

“…The method integrates a structured preprocessing pipeline, including intensity normalization, spatial resampling, and noise reduction, to ensure data consistency. …”
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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

“…Spatially, three out of five datasets indicated a consistent reduction in erosion intensity, while two AVHRR datasets showed an initial decline followed by a resurgence over the past decade. …”
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Mapping the mHealth Nexus: A Semantic Analysis of mHealth Scholars’ Research Propensities Following an Interdisciplinary Training Institute by Junpeng Ren, Jinwen Luo, Yingshi Huang, Vivek Shetty, Minjeong Jeon

“…We develop a hybrid analytical framework combining large language model (LLM) embeddings, Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction, and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) clustering to construct a semantic research landscape containing 329 micro-topics aggregated into 14 domains. …”
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Comparative evaluation of spatiotemporal methods for effective dengue cluster detection with a case study of national surveillance data in Thailand by Chawarat Rotejanaprasert, Kawin Chinpong, Andrew B. Lawson, Richard J. Maude

“…Evaluation metrics included accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Bayesian models and FlexScan emerged as top performers, demonstrating superior accuracy and sensitivity. …”
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Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting by Vandana Singh, Sudip Kumar Sahana, Vandana Bhattacharjee

“…For capturing the temporal aspect, predictive graph modeling for road network traffic at particular time stamps is performed. …”
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Remote sensing-based detection of brown spot needle blight: a comprehensive review, and future directions by Swati Singh, Lana L. Narine, Janna R. Willoughby, Lori G. Eckhardt

“…However, studies on other needle diseases demonstrated the effectiveness of multisource RS techniques for symptom detection, spatial mapping, and severity assessment. Advancements in machine learning (ML) and deep learning (DL) have further improved RS capabilities for automated disease classification and predictive modeling in forest health monitoring. …”
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Infrastructure Lifecycle Corrosion Management Using AI Analytics and Digital Twins by Bilal Ayyub, Karl Stambaugh

“…The non-parametric analysis of corrosion data is demonstrated to provide insights into spatial and temporal variations, helping in predictive modeling and decision-making. …”
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Advances and applications of empirical mode decomposition and its variants in hydrology: A review by CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong

“…Additionally, we review the progress of EMD and its variants, particularly in the context of multi-spatiotemporal scale analysis, trend detection, and predictive modeling of hydrological series. Key insights are drawn from the use of EMD in detecting trends, identifying temporal variation features, and improving model predictions for hydrological data across different spatial and temporal scales. …”
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Design of an Iterative Method for Time Series Forecasting Using Temporal Attention and Hybrid Deep Learning Architectures by Yuvaraja Boddu, A. Manimaran

“…This configuration adeptly extracts both spatial and temporal features, yielding a 15% reduction in prediction error across various datasets. …”
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Contribution of temperature and precipitation anomalies to the California drought during 2012–2015 by Lifeng Luo, Deanna Apps, Samuel Arcand, Huating Xu, Ming Pan, Martin Hoerling

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