Distribution Characteristics of Nutrients and Eutrophication Assessment in Yueqing Bay by YAO Kaixue, YIN Rui, WANG Yang, CHEN Feng, LI Zhenhua

“…Based on the Marine environment monitoring data of Yueqing Bay in spring, summer, autumn and winter from 2018 to 2019, the spatial and temporal distribution characteristics of nutrient salts (dissolved inorganic nitrogen, DIN) and active phosphate (DIP) in the sea were analyzed, and the pollution degree, eutrophication degree and nutrient structure of the sea area were evaluated by single factor index method, eutrophication index method and potential eutrophication model. …”
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Spatio-temporal patterns and driving factors of green development level in alpine meadow regions: A case study in Gannan Tibetan Autonomous Prefecture by Yan-chen Zhao, Qi-peng Zhang, Hui-ran Zhang, Shuai Huang

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Accounting for spatiotemporal patterns of long‐term recursion in estimating local‐scale step selection by Michael E. Egan, Nicole T. Gorman, Michael W. Eichholz, Dan Skinner, Peter E. Schlichting, Guillaume Bastille‐Rousseau

“…Specifically, since the used and available steps in SSA are associated with specific places and times, covariates must account for variation in spatial and temporal patterns of long‐term behaviour. …”
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Impact of spatially-variable soil thickness and texture on simulated hydrologic conditions in a semiarid watershed in northwest Mexico by Luis A. Méndez-Barroso, Enrique R. Vivoni, Giuseppe Mascaro

“…Furthermore, soil texture patterns were an important factor controlling the spatial and temporal persistence of soil moisture which is highly evident during the transition from dry to wet conditions in the North American monsoon region. …”
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Examining the Spatial and Temporal Relationships among Aerosol Optical Depth, Soil Moisture, and Wind Speed from 2000 to 2024,(Case Study: Western Iran) by Sosan Salajegheh, Hamed Eskandari Damaneh, Hadi Eskandari Damaneh

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Long-term mean climate and seasonal variability drive spatial patterns of forage production fluctuation trends across California annual grasslands by Zheng Li, Leslie M Roche, Steven Ostoja, Yufang Jin

“…The RF model based solely on climate variables revealed that spatial patterns of trends in temporal fluctuations of forage production were mostly driven by long-term climatic means; specifically, drier areas with a long-term mean growing season (GS) precipitation below ∼500 mm, or warmer areas with long-term mean minimum temperatures above ∼6 °C, were more likely to exhibit significant increasing trends in forage production fluctuations. …”
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Solar and Wind 24 H Sequenced Prediction Using L-Transform Component and Deep LSTM Learning in Representation of Spatial Pattern Correlation by Ladislav Zjavka

“…Node-by-node feature selection and dynamical PDE representation of DfL are evaluated along with long-short-term memory (LSTM) recurrent processing of deep learning (DL), capturing complex spatio-temporal patterns. …”
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Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Lan Zhou, Shichao Long, Mengsi Li, Linhui Zhong, Aerzuguli Abudulimu, Wenguang Liu, Deng Pan, Ganmian Dai, Yigang Pei, Wenzheng Li

“…This study aimed to elucidate biological differences related to pTLS density and develop a radiomic classifier for predicting pTLS density in HCC, offering new insights for clinical diagnosis and treatment.Methods Spatial transcriptomics (n=4) and RNA sequencing data (n=952) were used to identify critical regulators of pTLS density and evaluate their prognostic significance in HCC. …”
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Recreational and tourist destination research methods by Tetiana Bozhuk

“… The methodological basis of the concept RTDe are the main provisions of the modern structural and socio-economic geography to study the spatial and temporal aspects of relations in the system "Man - Nature" and related sciences (knowladge about a tourizm, recreational geography, natural resources, etc.) that appeal to spatial heterogeneity of the studied phenomena. …”
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Analysis of the Construction and Evolution of Ecological Security Patterns in Karst Areas by FU Li, PENG Shuangyun, GONG Luping, HUANG Bangmei, MA Dongling, ZHU Ziyi

“…［Methods］ Based on the evaluation of ecosystem service importance and ecological sensitivity, in combination with methods such as MSPA, MCR, and the gravity model, the ecological security pattern of the Pearl River source region from 1990 to 2020 was constructed, and its spatial-temporal evolution characteristics were analyzed. …”
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Strategic Alignment of Technological Innovation for Sustainable Development: Efficiency Evaluation and Spatial Analysis in China’s Advanced Manufacturing Industry by Zhenghan Chen, Quan Zhang, Tianzhen Tang, Mingran Deng

“…Through a Data Envelopment Analysis (DEA) and Spatial Durbin Model (SDM), we systematically evaluated TIE patterns using panel data from 11 provinces. …”
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Spatio-Temporal Influencing Factors of the Coupling Coordination Degree Between China’s New-Type Urbanization and Transportation Carbon Emission Efficiency by Han Jia, Weidong Li, Runlin Tian

“…This study focuses on the coupling and coordination between China’s new-type urbanization (NU) and transportation carbon emission efficiency (CET), revealing its spatial and temporal evolution patterns and driving factors. …”
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Spatio-temporal evolution analysis of coupling coordination of green finance, digital economy, and carbon emission intensity in the Yangtze River Economic Belt by Yue-Yue Sui, Xing-Fu Zhang

“…Therefore, to promote sustainable economic development, it is necessary to promote GF, DIEC, and CEI in an integrated way, and there are relatively few studies on the synergistic promotion of these three aspects.MethodsUsing the entropy method, the coupling coordination degree model (CCDM), and the spatial analysis method, this study thoroughly examines the spatio-temporal pattern of the coupling and coordination of GF, DIEC, and CEI in the Yangtze River Economic Belt using panel data from 11 provinces in the region from 2013 to 2022.ResultsThe findings demonstrate that: (1) The Yangtze River Economic Belt’s general extent of GF and DIEC advancement is increasing, and the DIEC’s level exhibits a pattern of a declining gradient from the downstream to the upstream areas. (2) The Yangtze River Economic Belt’s CEI is on the decline, with the upstream region having a higher CEI than the middle and downstream regions. (3) Although there is regional diversity, the Yangtze River Economic Belt’s three systems exhibit a growing trend in connection and coordination degree. (4) The Yangtze River Economic Zone shows a declining trend in the spatial difference in the coupling coordination degree (CCD) of the three systems(overall Gini coefficient reduced by 31% from 2013 to 2022), with the upstream showing the smallest discrepancy and the downstream showing the biggest. …”
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Spatio-temporal Coupling of Ecological Service Value and Human Activity Intensity in the Central Urban Area of Lhasa City by Jiarui ZHANG, Wangdwei MIGMAR, Li CHENG, Liyuan QIAN

“…Local cluster analysis further identified shifts in spatial patterns, with a 38.6% reduction in high-high clusters (areas with both high ESV and low HAI) and a 217% expansion in low-high clusters (areas with low ESV and high HAI), predominantly in newly urbanized areas. …”
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Revealing Spatiotemporal Urban Activity Patterns: A Machine Learning Study Using Google Popular Times by Mikel Barrena-Herrán, Itziar Modrego-Monforte, Olatz Grijalba

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Characteristics of Land Use Change and Evaluation of Ecological Sensitivity in Chongqing by XIE Xianjian, GOU Qiantao, WU Han

“…Specifically, the Coupled Spatial Distance Index Model, Spatial Autocorrelation Analysis, Geodetector Model, and Grid Coding techniques were applied to evaluate the ecological sensitivity comprehensively. …”
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Diagnosis of depression based on facial multimodal data by Nani Jin, Renjia Ye, Peng Li

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Toward accurate and scalable rainfall estimation using surveillance camera data and a hybrid deep-learning framework by Fiallos-Salguero Manuel, Soon-Thiam Khu, Jingyu Guan, Mingna Wang

“…However, traditional rainfall measurement methods face limitations regarding spatial coverage, temporal resolution, and data accessibility, particularly in urban settings. …”
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Coupling analysis of multi-systems urbanization: Evidence from China by Junqiang Luo, Weijing Ma, Shuang An, Zining Zhang, Yanchuan Fu, Hejun Huang, Genying Chang

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The Coupling Coordination Degree and Spatio-Temporal Divergence Between Land Urbanization and Energy Consumption Carbon Emissions of China’s Yangtze River Delta Urban Agglomeration... by Zhengru Li, Yang Yu, Bo Liu, Xiaoyu Zhang, Tianyin Li, Nuo Shi, Yichen Ren

“…The carbon emission subsystem showed sustained stable decline, with a gradual reduction in the number of cities maintaining low carbon emission levels. (2) Temporally, the overall coupling coordination degree of the urban agglomeration system demonstrated an upward trend, progressing from severe imbalance to the primary coordination stage. (3) Spatially, significant regional differences in coupling coordination degree were observed, showing higher values in the southeastern areas compared to the northwestern regions. (4) Most areas exhibited no significant clustering characteristics in the coupling coordination degree between land urbanization and energy consumption carbon emissions, while the local spatial clustering patterns demonstrated temporal variations. …”
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