Pearl River Delta: Scales, Times, Domains by Liang Xiong

“…A mapping method is developed according to the key notions in the understanding of urban deltas, namely its systems, scales, and temporality. The systematic mapping approach was used to organize and analyze both short-term and long-term spatial data during the rapid delta urbanization processes by transforming spatial data via scales, times, and domains. …”
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Ensemble deep learning and anomaly detection framework for automatic audio classification: Insights into deer vocalizations by Salem Ibrahim Salem, Sakae Shirayama, Sho Shimazaki, Kazuo Oki

“…Audio recordings have emerged as a pivotal tool in field observations, enriching environmental monitoring in both the spatial and temporal dimensions. However, the richness and complexity of these recordings pose significant challenges, primarily when extracting specific sound clips from long recordings owing to the presence of ambient noise and other irrelevant sounds. …”
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Assessing water clarity in the Chesapeake Bay using satellite-derived Secchi disk depth by Seunghyun Son, Nikolay P. Nezlin, Veronica P. Lance

“…Assessments of SDD from remotely-sensed ocean color data benefit from wide spatial and temporal coverage but are subject to low accuracy resulting from unstable relationship between water transparency and the color of water surface. …”
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When, where, and how prey pair antipredator behaviors to natural and anthropogenic mortality risks by Michael E. Egan, Abigail M. Weber, Nicole Gorman, Michael W. Eichholz, Daniel Skinner, Peter E. Schlichting, Guillaume Bastille-Rousseau

“…Despite prioritizing humans, mesopredators impacted behavioral state, suggesting that mesopredators still have important impacts on prey behavior. Finally, temporal patterns of avoidance align with other studies that indicate avoidance of predators is time-dependent, but further highlight the complex push–pull relationship of human modified areas on wildlife.…”
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Leaves and Tree Rings as Biomonitoring Archives of Atmospheric Mercury Deposition: An Ecophysiological Perspective by Fabrizio Monaci, Davide Baroni

“…This perturbation profoundly affects global atmospheric Hg concentrations, residence times, and spatial distribution patterns. While early investigations focused on forest stands near heavily polluted areas, contemporary research has expanded to diverse ecosystems, revealing that trees provide tissues that function as temporal archives for atmospheric-terrestrial Hg exchange. …”
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Assessment of the Spatiotemporal Evolution Characteristics and Driving Factors of Ecological Vulnerability in the Hubei Section of the Yangtze River Economic Belt by Shuai Wu, Guanzhong Zeng, Jie Sun, Xiaohuang Liu, Xuanhui Li, Qinghua Zeng, Shijie Gu

“…The Theil index decreased and then rose, the degree of spatial agglomeration was floating in a “V” shape, and the spatial pattern of vulnerability was essentially the same in the hot- and cold-spot areas. …”
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Hybrid CNN–LSTM Model With Soft Attention Mechanism for Short‐Term Load Forecasting in Smart Grid by Syed Muhammad Hasanat, Muhammad Haris, Kaleem Ullah, Syed Zarak Shah, Usama Abid, Zahid Ullah

“…The proposed model leverages Convolution Neural Networks (CNNs) to extract spatial patterns, LSTMs to capture temporal dependencies, and attention mechanisms to prioritize important information, enhancing predictive performance. …”
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vBerlinV2N: Recreating a Cellular Network Measurement Campaign With Simulations by Christian L. Vielhaus, Mauri Seidel, Vincent Latzko, Alexander Grob, Peter Sossalla, Martin Reisslein, Frank H. P. Fitzek

“…We analyze the distributions as well as the temporal and spatial variations of the received signal quality metrics of the radio environments and compare the end-to-end throughput, delay, and handovers.…”
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Video-Based Plastic Bag Grabbing Action Recognition: A New Video Dataset and a Comparative Study of Baseline Models by Pei Jing Low, Bo Yan Ng, Nur Insyirah Mahzan, Jing Tian, Cheung-Chi Leung

“…The second approach leverages a multiple-frame <i>convolutional neural network</i> (CNN) to exploit temporal and spatial patterns in the video data. The third approach explores a 3D CNN-based deep learning model, which is capable of processing video data as volumetric inputs. …”
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From river flow regime diversity to proxies for hydrologic homogeneity a Canada-wide case study by Sarah Ariano, Geneviève Ali

“…Caution is therefore warranted when using existing non-hydrological zonal classifications for regional water policy planning, as they may lead to a mischaracterization of spatial differences in streamflow patterns.…”
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Change of human settlement resilience and its obstacle degree in resource-based cities in the Yellow River Basin by JIANG Haining, ZHENG Shuting, YANG Qi, JIANG Dongru, YU Jianhui

“…The growth-type, mature-type, and regeneration-type cities all showed an agglomeration of high resilience cities, while the decline-type cities with high resilience level tended to be dispersed. (2) From the perspective of spatial evolution, the resilience level of urban human settlements presents a spatial pattern of “periphery is higher than center, downstream is higher than upstream. …”
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Analysing Time Series of Land Subsidence in the West of Tehran Province (Shahriar Plain) and its Relation to Groundwater Discharge by InSAR Technique by Ramin Papi, ُSara Attarchi, Masoud Soleimani

“…The results of the time series analysis of land displacement signals to extract the spatial-temporal pattern of the region's subsidence, despite minor differences, are very similar to the results of other studies in the same region. …”
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MaxEnt Modeling of the Impacts of Human Activities and Climate Change on the Potential Distribution of <i>Plantago</i> in China by Da Liao, Bing Zhou, Haiyan Xiao, Yuxin Zhang, Shujian Zhang, Qitao Su, Xiaohong Yan

“…This study was conducted to elucidate the spatial distribution of <i>Plantago</i> species patterns across China and evaluate their differential responses to impending climate change and human interventions. …”
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Insights into gait performance in Parkinson's disease via latent features of deep graph neural networks by Jiecheng Wu, Jiecheng Wu, Ning Su, Xinjin Li, Xinjin Li, Chao Yao, Jipeng Zhang, Xucheng Zhang, Wei Sun

“…Using ST-GCN, we extracted spatial and temporal patterns from these five states directly from the data, thereby enhancing the accuracy of gait parameter calculation. …”
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Analysis of LULC Change Dynamics That Have Occurred in Tuscany (Italy) Since 2007 by Lorenzo Arcidiaco, Manuela Corongiu

“…Specifically, data spanning five temporal intervals (2007, 2010, 2013, 2016, and 2019) enabled a comprehensive comparative analysis of spatial persistence in LULC patterns. …”
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Research on the charging periods of the ultra-shallow play in front of the Hashan area, northwestern margin of the Junggar Basin by WANG Qianjun, ZHOU Jian, ZHANG Faqiang, YU Hongzhou, WU Qianqian, LU Hongli, LIU Qingxin, ZHOU Yu, CHENG Ming, YAN Jianzhao, LYU Yanfang

“…This stratigraphic variation in charging behavior offers crucial insights into the temporal and spatial distribution of hydrocarbons within the study area. (3) Calcite U–Pb dating identified two major thermal events at approximately 133 Ma (Early Cretaceous) and 73 Ma (Late Cretaceous). …”
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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

“…Based on land use classification results from three different periods, the spatial distribution and pattern changes of major land use types in the region over the past two decades were investigated through analyses of ellipses, centroid shifts, area changes, and transition matrices. …”
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Development of an enhanced base unit generation framework for predicting demand in free‐floating micro‐mobility by Dohyun Lee, Kyoungok Kim

“…The method identifies suitable base areal units by merging smaller ones while considering the similarities in temporal usage patterns and distances between different areas, mitigating the impact of MAUP during model learning. …”
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Investigating difficult to detect pancreatic lesions: Characterization of benign pancreatic islet cell tumors using multiparametric pancreatic 3-T MRI. by Kwadwo Antwi, Patricia Wiesner, Elmar M Merkle, Christoph J Zech, Daniel T Boll, Damian Wild, Emanuel Christ, Tobias Heye

“…Dynamic contrast-enhanced (DCE) Magnetic Resonance Images (MRI) with Golden-Angle-Radial-Sparse-Parallel (GRASP) reconstruction, enabling imaging at high spatial and temporal resolution, was used to assess enhancement-patterns of PICTs. …”
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Multi-century mean summer temperature variations in the Southern Rhaetian Alps reconstructed from <i>Larix decidua</i> blue intensity data by R. Cerrato, M. C. Salvatore, M. C. Salvatore, M. Brunetti, A. Somma, C. Baroni, C. Baroni

“…Considering their high temporal resolution, dendrochronological data have been recognized as a fundamental tool for reconstructing past climate variations. …”
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