Assessing the trade-offs between urbanization policy and ecological construction: impacts on carbon balance in the Yangtze River Basin by Yaqiu Liu, Yuqi Wang, Muhammad Imran, Wei Mi, Nawal Abdalla Adam, Ji Shen

“…Using high-resolution raster data, multi-source remote sensing, panel carbon models, soil respiration analysis, and lithogenic carbon sink estimation, we quantify spatial–temporal patterns of carbon fluxes and land-use conflicts. …”
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Correcting Forecast Time Biases in CMA-MESO Using Himawari-9 and Time-Shift Method by Xingtao Song, Wei Han, Haofei Sun, Hao Wang, Xiaofeng Xu

“…The results indicate the following: (1) the time-shift method improved cloud simulations, necessitating a 30 min advance for Case 1 and a 3.5 h delay for Case 2; (2) time-shifting reduced the standard deviation of observation-minus-background (OMB) bias in certain regions and enhanced spatial uniformity; (3) the threat score (TS) demonstrated an improvement in forecast accuracy, particularly in cases exhibiting significant movement patterns. …”
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Topographic Drivers of Soil Moisture Across a Large Sensor Network in the Southern Appalachian Mountains (USA) by Jordan R. Stark, Jason D. Fridley

“…Remote sensing approaches capture large‐scale moisture patterns but are limited in spatial and temporal resolution, while commercial field sensors remain too expensive to deploy intensively over large spatial extents. …”
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Nonlinear variations and drivers of vegetation NPP on the Tibetan Plateau: Interaction of natural and human factors. by Jie Tang, Xinghong Peng, Wenfu Peng

“…However, the complexity and nonlinear variations of NPP across the Tibetan Plateau, along with spatial and temporal inconsistencies, present significant analytical challenges. …”
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Variations and impact factors of land use carbon emissions in the Yangtze River Economic Belt from a multiscale perspective by Chong Liu, Xiaoman Wang, Haiyang Li

“…Notably, spatial clustering intensified at the provincial and prefectural levels, while a diminishing trend in clustering was noted at the county scale. (3) Predominant clustering patterns at the prefectural and county scales included H–H and L–L types, with the county scale displaying more pronounced clustering characteristics. (4) Economic development emerged as the primary influencing factor on LUCE at both the prefectural and county scales. …”
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Permafrost and Rain Influence Summer Hydrologic Flowpaths in Boreal Catchments by Karen L. Jorgenson, Thomas A. Douglas, M. Torre Jorgenson, Neal J. Pastick, Tamara K. Harms

“…Temporal patterns in precipitation also influenced flowpaths. …”
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Spatiotemporal Changes and the Drivers of Ecological Environmental Quality Based on the Remote Sensing Ecological Index: A Case Study of Shanxi Province, China by Chi Cheng, Yanqiang Wang

“…The Theil–Sen Median, Mann–Kendall, and Hurst indices were comprehensively applied to systematically analyze the spatiotemporal differentiation patterns of ecological environmental quality. Furthermore, geodetector-based quantification elucidated the synergistic interactions among topographic, climatic, and anthropogenic drivers. …”
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MSDP-Net: A Multi-Scale Domain Perception Network for HRRP Target Recognition by Hongxu Li, Xiaodi Li, Zihan Xu, Xinfei Jin, Fulin Su

“…MSDP-Net introduces a hybrid spatial–spectral representation learning strategy through a multiple-domain perception HRRP (DP-HRRP) encoder, which integrates multi-head convolutions to extract spatial features across diverse receptive fields, and frequency-aware filtering to enhance critical spectral components. …”
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Dynamic assessment and zoning strategies for ecosystem health in Poyang lake urban agglomeration by Zhiyao Zou, Songkai Luo, Ping Duan

“…In the urban agglomeration, the comprehensive ecosystem health index remained stable in 78.18% of the total area, indicating a notable ‘polarisation’ in health levels among different areas. (3) Socioeconomic factors significantly influence ecosystem health in the urban agglomeration. (4) The urban agglomeration displayed distinct spatial patterns in terms of the types of changes in ecosystem health. …”
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Regional Low Flow Hydrology: Model Development and Evaluation by Vinícius B. P. Chagas, Pedro L. B. Chaffe, Günter Blöschl

“…Abstract Low flows result from the interplay of climatic variability and catchment storage dynamics, but it is unclear which of these variables is more relevant for explaining low flow spatial patterns. Here, we develop a new conceptual model that integrates process‐based hydrological knowledge with statistics and test it for 1,400 Brazilian catchments. …”
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A Dynamic Spatio-Temporal Deep Learning Model for Lane-Level Traffic Prediction by Bao Li, Quan Yang, Jianjiang Chen, Dongjin Yu, Dongjing Wang, Feng Wan

“…In traffic prediction, the mining of spatial features is an important step and graph-based methods are effective methods. …”
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STFDSGCN: Spatio-Temporal Fusion Graph Neural Network Based on Dynamic Sparse Graph Convolution GRU for Traffic Flow Forecast by Jiahao Chang, Jiali Yin, Yanrong Hao, Chengxin Gao

“…The dynamic sparse graph convolution gated recurrent unit (DSGCN-GRU) in this model is a novel component that integrates adaptive dynamic sparse graph convolution into the gated recurrent network to simulate the diffusion of information within a dynamic spatial structure. This approach effectively captures the heterogeneous and local features of spatial data, further reflecting the irregularities and dynamic variability inherent in spatial information. …”
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Research on the Complexity of Forms and Structures of Urban Green Spaces Based on Fractal Models by Yilu Gong, Xueming Li, Xueping Cong, He Liu

“…The fractal nature of urban green spaces is the product of the self-organizing evolution of the complex urban system into a higher stage, and orderly patterns and complex structures of urban green spaces will tend to manifest after they develop to a certain stage. …”
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Automated violence monitoring system for real-time fistfight detection using deep learning-based temporal action localization by Baolong Qi, Baoyuan Wu, Bailing Sun

“…However, essential individual features can be extracted by examining human skeletal movements’ progression and temporal patterns. This paper presents a novel multimodal spatio-temporal fistfight detection model (MSTFDet) that integrates RGB images and human skeletal data to identify violent behaviors accurately. …”
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Histogram-based gradient boosting machine with SHAP-driven interpretability for predicting intensity of urban heat Island effect by Nhat-Duc Hoang

“…The input features include topographical, spatial, and urban morphological factors. Moreover, for a better explanation of thermal patterns in the study region, past records of LST are also taken into account. …”
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Quantifying the impact of urban blue-green spaces on humid-heat exposure risk: A case study of Nanjing’s central urban area by Yueyue Ma, Chenfeng Xu, Zhijie Yang

“…This dataset was further combined with conventional heat exposure assessment methods to develop a novel Population-Weighted Humid Heat Exposure Index (PWHHEI). The spatial distribution patterns between PWHHEI and urban blue-green spaces (UBGS) were analyzed using the bivariate Local Moran’s I statistic, and a Geographically Weighted Random Forest model was applied to assess the regulatory effects of UBGS morphological characteristics on humid-heat exposure and their spatial heterogeneity. …”
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Seasonal synchronization of influenza in the United States older adult population. by Julia B Wenger, Elena N Naumova

“…<h4>Conclusions/significance</h4>Our findings suggest that a systematic description of influenza seasonal patterns is a valuable tool for disease surveillance and can facilitate strategies for prevention of severe disease in the vulnerable, older adult population.…”
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Geomorphology and Hydroclimate Control Regional Urban Expansion by Serena Ceola, Giulia Grandi, Enrico Bertuzzo

“…Existing studies acknowledge that several environmental, hydroclimatic, socioeconomic, policy, and institutional factors control urban growth, yet key information about its detailed spatial and temporal dynamics is still missing. The ability to reproduce observed patterns of urban expansion is essential for projecting reliable scenarios for the near future. …”
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LSEVGG: An attention mechanism and lightweight-improved VGG network for remote sensing landscape image classification by Yao Lu

“…The model exhibits particularly strong performance in identifying natural landscape categories, achieving 88%–92% accuracy for classes with uniform spatial patterns such as forests, beaches, and meadows, where the SE attention mechanism effectively captures distinctive textural and spatial features characteristic of different landscape types. …”
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Regional differences and distributional dynamic evolution of science and technology innovation driven green development efficiency in Chinese agriculture by Lingling Wang, Min Li, Panpan Zhang

“…This study assesses the spatiotemporal efficiency of ASTI in promoting green agricultural development across 30 Chinese provinces, aiming to uncover persistent regional disparities and dynamic evolution patterns.MethodsConstructing an evaluation model and indicator system for science, technology and innovation driven green development in agriculture, applying the network Slack-Based Measure (SBM) model to measure the level of efficiency, and analyzing regional differences and dynamic features through the Theil index, kernel density estimation and spatial Markov methods.Results and discussionThis study explores the regional differences and distributional dynamic evolution of the efficiency of Agricultural science and technology innovation (ASTI) driven green development in China. …”
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