Delineation of future urban growth boundaries on the Qinghai-Xizang Plateau by integrating socioeconomic development and ecosystem services conservation by Qiaoxian Bai, Zhifeng Liu, Binghua Gong, Shuhui Liu, Xufeng Mao, Chunyang He

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Autonomous inverse encoding guides 4D nanoprinting for highly programmable shape morphing by Shuaiqi Ren, Zhiang Zhang, Ruokun He, Jiahao Fan, Guangming Wang, Hesheng Wang, Bing Han, Yong-Lai Zhang, Zhuo-Chen Ma

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Facial Anatomy Teaching for Aesthetic Surgery: Using 3-dimensional Photogrammetry and Immersive Virtual Reality by Sara M. Hussein, MD, Andrew F. Emanuels, MD, Luciano César P.C. Leonel, PhD, Nirusha Lachman, PhD, Maria Peris Celda, MD, PhD, Jonathan M. Morris, MD, Eric M. Sheahan, BA, Erick O. Martinez, BFA, Christian R. Hanson, BA, Basel A. Sharaf, MD, DDS, FACS

“…Although cadaveric dissection remains a valuable teaching tool, its accessibility is limited by cost, ethical concerns, and the lack of structured curricula, making it less feasible for ongoing surgical education. To address these limitations, this article introduced a novel educational approach that integrates 3D photogrammetry and virtual reality technology into the surgical anatomy curriculum for craniofacial and aesthetic surgery. …”
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Tsetse fly (G. f. fuscipes) distribution in the Lake Victoria basin of Uganda. by Mugenyi Albert, Nicola A Wardrop, Peter M Atkinson, Steve J Torr, Susan C Welburn

“…The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control.…”
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Simulation and Numerical Analysis of Energy-and-Ecological Compatibility of Indoor Plant Lighting by S. A. Rakutko, E. N. Rakutko

“…Theoretically, possible reduction of losses in the source of electrical power is 22 percent, in the optical part – 14 percent; in spatial fl ow distribution – 16 percent; in surface fl ow distribution – 10 percent. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…Finally, the particle swarm optimization algorithm is used for hyperparameter optimization to improve the prediction accuracy. Experimental results demonstrate that the DSTGFP model achieves reductions of 24.66% in the mean absolute error and 25.47% in the root-mean-square error compared to existing deep learning methods, highlighting its superior predictive performance.…”
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Nonparametric quantification of uncertainty in multistep upscaling approaches: A case study on estimating forest biomass in the Brazilian Amazon by Denis Valle, Leo Haneda, Rafael Izbicki, Renan Akio Kamimura, Bruna Pereira de Azevedo, Silvio H.M. Gomes, Arthur Sanchez, Carlos A. Silva, Danilo R.A. Almeida

“…In these approaches, a series of models are fitted linking the information from these different sensors, often resulting in improved predictions over large areas. …”
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mlr3spatiotempcv: Spatiotemporal Resampling Methods for Machine Learning in R by Patrick Schratz, Marc Becker, Michel Lang, Alexander Brenning

“… Spatial and spatiotemporal machine-learning models require a suitable framework for their model assessment, model selection, and hyperparameter tuning, in order to avoid error estimation bias and over-fitting. …”
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Estimating vegetation aboveground biomass in Yellow River Delta coastal wetlands using Sentinel-1, Sentinel-2 and Landsat-8 imagery by Yiming Xu, Yunmeng Qin, Bin Li, Jiahan Li

“…Red-edge related-spectral indices derived from S2 were proved to be important predictors in AGB modelling. The spatial uncertainty quantified by QRF showed the spatial prediction uncertainties of AGB models based on S2S2L8plus and S2 were lower than AGB model based on S1L8. …”
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Spatiotemporally weighted regression (STWR) for assessing Lyme disease and landscape fragmentation dynamics in Connecticut towns by Zhe Wang, Xiang Que, Meifang Li, Zhuoming Liu, Xun Shi, Xiaogang Ma, Chao Fan, Yan Lin

“…The integration of data-driven and model-driven approaches in this study delivers a robust framework that combines empirical pattern detection with theoretical insight, enhancing the robustness and predictive power of ecological studies.…”
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Progress in Flood Risk Assessment Based on Data-Driven Methods by HE Xinyu, TIAN Wenchong, ZHANG Zhiyu, LIAO Zhenliang

“…Flood is one of the most common natural disasters in China,which has made a serious impact on China's economy and society.Flood risk assessment can help management decision makers prevent and reduce flood losses in flood-prone areas.In recent years,data-driven methods have played an increasingly important role in flood risk modeling due to their fast modeling processes and accurate spatial prediction capabilities.This paper summarizes the research progress in data-driven methods applied to flood risk assessment and divides data-driven methods into two categories,i.e.…”
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Unsupervised Multimodal UAV Image Registration via Style Transfer and Cascade Network by Xiaoye Bi, Rongkai Qie, Chengyang Tao, Zhaoxiang Zhang, Yuelei Xu

“…The architecture integrates a cross-modal style transfer network (CSTNet) that transforms visible images into pseudo-infrared representations to unify modality characteristics, and a multi-scale cascaded registration network (MCRNet) that performs progressive spatial alignment across multiple resolution scales using diffeomorphic deformation modeling to ensure smooth and invertible transformations. …”
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A Study on Vector-Based Processing and Texture Application Techniques for 3D Object Creation and Visualization by Donghwi Kang, Jeongyeon Kim, Jongchan Lee, Haeju Lee, Jihyeok Kim, Jungwon Byun

“…In this research, data weight reduction, parallel processing, and polygon simplification algorithms were applied to optimize the 3D model generation speed. …”
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Vegetation Configuration Effects on Microclimate and PM_2.5 Concentrations: A Case Study of High-Rise Residential Complexes in Northern China by Lina Yang, Xu Li, Daranee Jareemit, Jiying Liu

“…Through field monitoring and ENVI-met 5.1 modeling of high-rise residential areas in Jinan, the results demonstrate that: (1) vegetation exhibits distinct spatial impacts in air-quality impacts, reducing roadside PM_2.5 by 26.63 μg/m³ while increasing building-adjacent levels by 17.5 μg/m³; (2) shrubs outperformed trees in PM_2.5 reduction (up to 65.34%), particularly when planted in inner rows, whereas tree crown morphology and spacing showed negligible effects; (3) densely spaced columnar trees optimize cooling, reducing T_a by 3–4.8 °C and the physiological equivalent temperature (PET*) by 8–12.8 °C, while planting trees on the outer row and shrubs on the inner row best balanced thermal and air-quality improvements; (4) each 1 m²/m³ leaf area density (LAD) increase yields thermal benefits (ΔT_a = −1.07 °C, ΔPET* = −1.93 °C) but elevates PM_2.5 by 4.32 μg/m³. …”
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Applying Causal Machine Learning to Spatiotemporal Data Analysis: An Investigation of Opportunities and Challenges by Christian M. Mulomba, Vogel M. Kiketa, David M. Kutangila, Pescie H. K. Mampuya, Junior N. Mukenze, Landry M. Kasunzi, Kyandoghere Kyamakya, Tasho Tashev, Selain K. Kasereka

“…Traditional spatiotemporal data analysis often relies on predictive models that overlook causal relationships, making it difficult to identify true drivers and formulate effective interventions. …”
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Local response to global risk: a case study of risk perception and communication on Chinese social media regarding Fukushima’s treated radioactive water discharge by Chenxi Sun, Qingliu Ren, Yuejing Ge

“…Three key findings emerge: (1) Temporal dynamics dominate public engagement, with attention peaking within two weeks post-discharge before gradually declining, while fear persists as the predominant emotion despite diminishing anger responses; (2) Coastal regions demonstrate heightened participation due to geographic proximity and seafood consumption patterns, though risk perception shows no consistent spatial gradient; (3) Socioeconomic factors - particularly education levels and seafood consumption - significantly predict communication intensity, whereas economic indicators like per capita GDP show limited influence. …”
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The Impact of Rural Population Decline on the Economic Efficiency of Agricultural Carbon Emissions: A Case Study of the Contiguous Karst Areas in Yunnan–Guizhou Provinces, China by Weini Chen, Dejun Han, Yu Zhan, Bo Chen

“…We map their spatiotemporal evolution patterns, apply spatial autocorrelation models to assess spatial dependencies, and investigate mechanisms through a mediation model integrated with agricultural modernization’s three core systems: industrial, production, and management. …”
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Constraints on the Projected Tropical SST Response to Greenhouse Warming by the Observed Antarctic Sea Ice Concentration by Yu‐Fan Geng, Fengfei Song, Lu Dong, Fengyun Luo

“…Under greenhouse warming, the reduction of Antarctic sea ice concentration (SIC) acts as an extratropical energy perturbation, exerting a substantial influence on the spatial distribution of tropical SST change. …”
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Environmental shadows in the age of progress: The toll of economic globalization on China's climate by Mengbing Du, Jianhui Ruan, Zhe Zhang, Mengxue Zhao, Hon S Chan, Li Zhang

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The Scuola Grande di San Marco in Venice between architecture and perspective reliefs: restitutions and applications of advanced fruition by Silvia Masserano, Veronica Riavis

“…These models can be utilized in a wider range of contexts, according to the specific needs of different categories of public (e.g., age, education, culture, disability, etc.).…”
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