Spatio-Temporal Characteristics and Driving Forces of Landscape Ecological Risks in Highly Urbanized Areas: A Case Study of Suzhou City by Lingyue LU, Dawei SHAO, Dianming WU

“…The formation mechanism, spatio-temporal heterogeneous driving effect and scale response law of LER in highly urbanized areas still need to be systematically explored.MethodsUtilizing multi-source data spanning the period from 1995 to 2020, including Landsat TM/ETM imagery, digital elevation model (DEM) and NASA datasets, this research focuses on exploring the characteristics of spatio-temporal variability of LER and corresponding drivers in Suzhou at the optimal scale, utilizing the LER evaluation model and the geographically and temporally weighted regression (GTWR) framework.Results1) The landscape pattern of Suzhou City is scale-dependent, with significant variations in the landscape pattern index for each land type at the optimal scale. …”
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Fine-Resolution Satellite Remote Sensing Improves Spatially Distributed Snow Modeling to Near Real Time by Graham A. Sexstone, Garrett A. Akie, David J. Selkowitz, Theodore B. Barnhart, David M. Rey, Claudia León-Salazar, Emily Carbone, Lindsay A. Bearup

“…The evaluations of the SnowModel simulations using the Airborne Snow Observatories’ (ASO’s) light detection and ranging (lidar)-derived SWE estimates show that the versions of the SnowModel calibrated to the remotely sensed SCA had an improved performance (mean error ranging from −28 mm to −6 mm) compared with the baseline simulations (mean error ranging from 69 mm to 86 mm), and comparable spatial patterns to those of the ASO, especially at the highest elevations. …”
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A Comprehensive Method for Anomaly Detection in Complex Dynamic IoT Systems by Andrii Liashenko, Larysa Globa

“…Modern dynamic systems, such as transportation networks and IoT infrastructures, generate massive volumes of interrelated temporal data represented as temporal graphs. Conventional methods – like clustering, statistical thresholds, and classical time series analysis – often fail to account for the spatial-temporal dependencies inherent in these systems, leading to high false positive rates or missed complex anomalies. …”
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Monitoring of ecological security patterns based on long-term land use changes in Langsa Bay, Indonesia by Jiaojie Zhang, Fengqin Yan, Vincent Lyne, Xuege Wang, Fenzhen Su, Qian Cao, Bin He

“…The findings emphasize prioritizing ecological and agricultural land preservation to mitigate ecological risks in bays, offering spatial, temporal and land-use insights for sustainable coastal management.…”
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A Reevaluation on Regional Studies’ Models to Promote the Applied Fundamentals of Inter-Regional Security Relations’ Patterns by Behzad Ahmadi Lafuraki, Rouhollah Talebi Arani

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An Adaptive Convolutional Neural Network With Spatio-Temporal Attention and Dynamic Pathways (ACNN-STADP) for Robust EEG-Based Motor Imagery Classification by Aaqib Raza, Mohd Zuki Yusoff

“…Moreover, advanced deep learning models often utilize rigid architectures with fixed spatial-temporal filters, restricting their adaptability to dynamic EEG patterns. …”
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Beyond clinical scales: an observational study on instrumental gait analysis and biomechanical patterns in patients with Parkinson’s disease by Paolo De Pasquale, Mirjam Bonanno, Cristiano De Marchis, Luca Pergolizzi, Antonino Lombardo Facciale, Giuseppe Paladina, Maria Grazia Maggio, Federica Impellizzeri, Irene Ciancarelli, Angelo Quartarone, Angelo Quartarone, Rocco Salvatore Calabrò

“…Statistical analysis involved a non-parametric test to compare pathological and normal data, clustering methods to identify groups based on clinical evaluations, and a combination of non-parametric analysis and linear models to assess dependencies on clinical scales.ResultsThe results showed that PD patients had significant gait kinematic differences compared to normal values, with increased temporal and shortened spatial parameters. …”
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A Multi-Modal Approach Using a Hybrid Vision Transformer and Temporal Fusion Transformer Model for Stock Price Movement Classification by Ibanga Kpereobong Friday, Sarada Prasanna Pati, Debahuti Mishra

“…Concurrently, the vision transformer (ViT) model is used to process the images using an embedded projection and multi-head self-attention to extract salient spatial features into a non-overlapping patch of <inline-formula> <tex-math notation="LaTeX">$16\times 16$ </tex-math></inline-formula> pixels, which are treated as input tokens for the model. …”
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Consistent patterns of LiDAR-derived measures of savanna vegetation complexity between wet and dry seasons by Zhengyang Wang, Jenia Singh, Andrew B. Davies

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Spatio-temporal dynamics of urban medical system carrying capacity and their obstacle factors: A case study of Yangtze River Delta urban agglomeration. by Chengshuang Sun, Ke Zhou, Guangxia Li, Weina Zhu, Dongjun Wan

“…The frequent occurrence of various urban disasters poses risks to human survival and welfare, and it is of great significance to evaluate the urban medical system carrying capacity (UMSCC), monitor the spatial and temporal patterns of the UMSCC and identify their obstacle factors to improve the public medical system and rationalize medical resource allocation. …”
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From Patterns to Predictions: Spatiotemporal Mobile Traffic Forecasting Using AutoML, TimeGPT and Traditional Models by Hassan Ayaz, Kashif Sultan, Muhammad Sheraz, Teong Chee Chuah

“…With the growing importance of data analytics, analyzing CDRs has become critical for optimizing network resources by forecasting demand across spatial and temporal dimensions. In this study, we examine publicly available CDR data from Telecom Italia to explore the spatiotemporal dynamics of mobile network activity in Milan. …”
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A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns by Irene Biliani, Ekaterini Skamnia, Polychronis Economou, Ierotheos Zacharias

“…Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. …”
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Travel Patterns Analysis Using Tensor-Based Model from Large-Scale License Plate Recognition Data by Zhaoxin Liu, Xiaolu Wang, Yufeng Bi, Jun Kong, Run Xu, Yuanpei Chen, Jinjun Tang

“…Travel patterns reflect the regularity of residents’ mobility, and it is a crucial factor to evaluate the reasonability of urban spatial structure and connectivity of road networks. …”
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A Temporal Attention-Based SARIMA-BiLSTM Residual Learning Model Tuned by Grey Wolf Optimizer for Parallel Urban Traffic Forecasting by Manas Kamal Das, Christopher Columbus Chinnappan, E. Elakiya

“…However, urban traffic exhibits high levels of temporal variability, spatial complexity, and nonlinear dependencies, posing challenges to traditional time series and machine learning models. …”
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Quantifying water supply–demand relationship and spatial flow in Qinghai–Xizang Plateau: Case study of Lhasa River Basin by Jun Wang, Xiaochi Liu, Xiao Zhang, Yan Gao

“…The Lhasa River Basin is the political, economic, and cultural core area and main cultivation area of Qinghai–Xizang Plateau and is considered ecologically fragile. With uneven spatial and temporal distribution of water resources, mismatched supply and demand may accentuate differences in distribution and affect the security of regional water resources. …”
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Tracking diurnal variation of NO2 at high spatial resolution in China using a time-constrained machine learning model by Sicong He, Yanbin Yuan, Zhen Li, Heng Dong, Xiaopang Zhang, Zili Zhang, Lan Luo

“…Evaluated with in-situ NO2 measurements, the results have demonstrated the robust and excellent performance of the T-XGB (R2: 0.920–0.948; MAE: 2.89–3.67 µg/m3/h), as well as the accuracy of the temporally conserved downscaling technique (R2 > 0.973). …”
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Impact of imported COVID-19 cases on South Korea’s response: variant transitions and regional patterns (2020–2023) by Haram Seo, Minchan Choi, Gerardo Chowell, Hyosun Lee, Byul Nim Kim, Sunmi Lee

“…The dataset included demographic information, countries of origin, entry points, and information on dominant viral variants during the specified period. Temporal and spatial analyses examined how variant transitions, particularly from Delta to Omicron, and quarantine policy changes influenced imported case patterns. …”
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Evaluation of the Effectiveness of Downscaled Precipitation Data in Drought Monitoring by Ping Ji, Qunming Wang

“…The results indicated that the SPI calculated from 1-km downscaled results can reproduce more detailed spatial distribution patterns of meteorological drought compared to the SPI derived from the 10-km original GPM. …”
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Spatio-temporal evolution of land subsidence and susceptibility zonation of associated ground fissures in the urban area of loess plateau: a case in Xianyang city, China by Yuemin Sun, Jiewei Zhan, Fei Qiang, Quanzhong Lu, Cong Liu, Zhaowei Yao, Jianbing Peng

“…Then, the gradient of land subsidence and its potential relation to ground fissure hazards were evaluated. The results highlight a strong spatial correlation between high subsidence gradient areas and dense ground fissure distribution. …”
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Exploring the Coupling of Land Development Intensity and Green Economy Development in the Pearl River Delta: Patterns, Challenges, and Strategic Pathways by Huiming Huang, Shuangyu Xu, Kailun Fang

“…A comprehensive evaluation framework is developed using a coupling coordination degree model and panel vector autoregression (PVAR) model to explore the spatial and temporal evolution of their relationship. …”
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