A Predictive Compact Model of Effective Travel Time Considering the Implementation of First-Mile Autonomous Mini-Buses in Smart Suburbs by Andres Udal, Raivo Sell, Krister Kalda, Dago Antov

“…The one-dimensional distance-based spatial model with 5 residential origin zones and 6 destination districts in the city is applied. …”
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Suitability prediction of potential arable land in southeast coastal area of China by Yan Zheng, Xiaohuang Liu, Jianwei Shi, Ping Zhu, Run Liu, Liyuan Xing, Hongyu Li, Chao Wang

“…Then, the spatial distribution pattern and centroid migration trend of the potential habitat area under two greenhouse gas emission scenarios (SSP126 and SSP585) in the future 2021–2040 (2040s) and 2041–2060 (2060s) were modeled. …”
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Transformer based models with hierarchical graph representations for enhanced climate forecasting by T. Bhargava Ramu, Raviteja Kocherla, G. N. V. G. Sirisha, V. Lakshmi Chetana, P. Vidya Sagar, R. Balamurali, Nanditha Boddu

“…The model integrates three key components: Spatial-Temporal Fusion Module (STFM) to capture spatiotemporal dependencies, Hierarchical Graph Representation and Analysis (HGRA) to model structured climate relationships, and Dynamic Temporal Graph Attention Mechanism (DT-GAM) to enhance temporal feature extraction. …”
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Spatiotemporal Dynamics and Prediction of Habitat Quality Based on Land Use and Cover Change in Jiangsu, China by Ge Shi, Chuang Chen, Qingci Cao, Jingran Zhang, Jinghai Xu, Yu Chen, Yutong Wang, Jiahang Liu

“…This study utilizes the land use data of Jiangsu Province for the years 2000, 2010, and 2020, applying the FLUS model to investigate the driving force behind land expansion and to simulate a prediction for the land use of 2030. …”
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Effect of nuclear medium on the spatial distribution of pions by Satyajit Puhan, Navpreet Kaur, Arvind Kumar, Suneel Dutt, Harleen Dahiya

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Importance of Considering Seasonality in Tick Activity When Assessing Spatial Expansion Potential: A Case Study on Haemaphysalis longicornis by Younjung Kim, Raphaëlle Métras

“…In this study, we mapped the spatial expansion risk of H. longicornis in North America and Europe by training a habitat suitability model with its occurrence data from East Asia and Oceania. …”
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Urban air pollution and spatial strategic response by Chuyi Fang, Yuqing Zhao

“…We first develop a theoretical model in which environmental standards function as strategic complements, predicting that a prefecture’s pollution control efforts are positively influenced by those of neighboring regions. …”
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Spatio-Temporal Predictive Learning Using Crossover Attention for Communications and Networking Applications by Ke He, Thang Xuan Vu, Lisheng Fan, Symeon Chatzinotas, Bjorn Ottersten

“…This limitation reduces their prediction accuracy in spatio-temporal predictive learning, where understanding both spatial and temporal dependencies is essential. …”
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Assessing Coincidence of Satellite Acquisitions and Flood Events to Predict Suitability for Flood Map Synthesis by Lyle Prince, Riley C. Hales, Kel N. Markert, E. James Nelson, Gustavious P. Williams, Daniel P. Ames, Hyongki Lee, Amirhossein Rostami

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A Comparative Study of Downscaling Methods for Groundwater Based on GRACE Data Using RFR and GWR Models in Jiangsu Province, China by Rihui Yang, Yuqing Zhong, Xiaoxiang Zhang, Aizemaitijiang Maimaitituersun, Xiaohan Ju

“…In the validation of the correlation accuracy between the downscaling results and the measured groundwater levels, the Random Forest model demonstrated better predictive performance, which offers distinct advantages in improving the spatial resolution of groundwater storage changes in Jiangsu Province.…”
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Multi-scenario land use change simulation and spatial-temporal evolution of carbon storage in the Yangtze River Delta region based on the PLUS-InVEST model. by Jingru Zhou, Verner Carl Johnson, Jingchao Shi, Mou Leong Tan, Fei Zhang

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Spatial-and-local-aware deep learning approach for Ground-Level NO2 estimation in England with multisource data from satellite-based observations and chemical transport models by Siying Wang, Shuangyin Zhang, Dawei Wang, Weifeng Li

“…The prediction model achieved R2 values of 0.914, 0.919, and 0.887 for 2019, 2020, and 2021, respectively, and performed well in urban regions. …”
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Spatial analysis of prehospital emergency medical services accessibility: a comparative evaluation of the GAUSS-probability two-step floating catchment area model in Handan City by Feng Tian, Feng Tian, Feng Tian, Saicong Lu, Saicong Lu, Saicong Lu, Zhenjie Yang, Tingting Zhao, Tingting Zhao, Tingting Zhao, Penghui Li, Penghui Li, Penghui Li, Haifang Zhang

“…In this study, the GAUSS-Probability Two-step Floating Catchment Area (GP2SFCA) method was applied to evaluate the spatial distribution of access to prehospital EMS in Handan City and to assess accessibility differences by comparing it with various models.ResultsThe results demonstrated that the GP2SFCA model achieved significantly improved performance, with an average correlation coefficient of 0.7017, indicating a notably higher predictive accuracy. …”
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Unmanned Aerial Vehicles Applicability to Mapping Soil Properties Under Homogeneous Steppe Vegetation by Azamat Suleymanov, Mikhail Komissarov, Mikhail Aivazyan, Ruslan Suleymanov, Ilnur Bikbaev, Arseniy Garipov, Raphak Giniyatullin, Olesia Ishkinina, Iren Tuktarova, Larisa Belan

“…We used an area in the Eurasian steppe zone (Republic of Bashkortostan, Russia) covered with the <i>Stipa</i> vegetation type as a test plot, and collected 192 soil samples from it. We estimated the models using a cross-validation approach and spatial prediction uncertainties. …”
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Air pollution’s numerical, spatial, and temporal heterogeneous impacts on childhood hand, foot and mouth disease: a multi-model county-level study from China by Zhangying Tang, Qi Sun, Jay Pan, Mingyu Xie, Zhoufeng Wang, Xiaojun Lin, Xiuli Wang, Yumeng Zhang, Qingping Xue, Yanchen Bo, Jinfeng Wang, Xin Liu, Chao Song

“…Conclusions This study underscores the nuanced and three-perspective heterogeneous influences of air pollution on HFMD in small areas, emphasizing the need for differentiated, localized, and time-sensitive prevention and control strategies to enhance the precision of dynamic early warnings and predictive models for HFMD and other infectious diseases, particularly in the fields of environmental and spatial epidemiology.…”
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MODEL SPACE TIME AUTOREGRESSIVE INTEGRATED (STARI) UNTUK DATA DEBIT AIR SUNGAI CITARUM DI PROVINSI JAWA BARAT by Mutik Alawiyah, Dianne Amor Kusuma, Budi Nurani Ruchjana

“…The spatial lag used in this study was the spatial lag of order 2, so the Citarum river water discharge could be predicted with the STARI model. …”
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Study on Subway Station Street Block-Level Land Use Pattern and Plot Ratio Control Based on Machine Learning by Mingyi Kuang, Fei Fu, Fangzhou Tian, Liwei Lin, Can Du, Yuesong Zhang

Subjects: “…metro station spatial growth prediction…”
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Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement by Qingmeng Shen, Yuming Wu, Limin Wan, Qian Chen, Yue Li, Zichao Liao, Wenbo Wang, Feng Li, Tao Li, Jiajun Shu

“…The settlement values of subway tunnels during the construction period exhibit significant nonlinear and spatial–temporal variation characteristics. To overcome the problems of historical data interference and spatiotemporal characteristics in tunnel settlement prediction models, this paper proposes a tunnel settlement prediction method based on data decomposition, reconstruction, and optimization. …”
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Evaluating logistic regression and geographically weighted logistic regression models for predicting orange-fleshed sweet potato adoption intention in Benin by Idrissou Ahoudou, Nicodeme V. Fassinou Hotegni, Charlotte O. A. Adjé, Tania L. I. Akponikpè, Dêêdi E. O. Sogbohossou, Nadia Fanou Fogny, Françoise Assogba Komlan, Ismail Moumouni-Moussa, Enoch G. Achigan-Dako

“…The GWLR model excels in elucidating the spatial nuances of diverse factors, offering a promising avenue for more reliable predictions for OFSP adoption.…”
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Spatial-temporal patterns and predictors of timing and inadequate antenatal care utilization in Zambia: A Generalized Linear Mixed Model (GLMM) investigation from 1992 to 2018. by Samson Shumba, Isaac Fwemba, Violet Kaymba

“…Predictors of inadequate utilisation of ANC were identified through the multilevel generalised linear model. Spatial effects were modeled using Quantum Geographic Information System (QGIS) version 3.34.1 to develop univariate choropleth maps. …”
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