How Does the Platform Economy Affect Urban System: Evidence from Business-to-Business (B2B) E-Commerce Enterprises in China by Pengfei Fang, Xiaojin Cao, Yuhao Huang, Yile Chen

“…This study develops an innovative measurement framework based on Business-to-Business (B2B) e-commerce enterprises to analyze platform-driven urban systems across 337 Chinese cities. Using spatial autocorrelation, rank-size distributions, and urban scaling laws, we reveal spatial differentiation patterns of cities’ B2B platforms. …”
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RETRACTED ARTICLE: Spatio-temporal analysis and simulation of urban ecological resilience in Guangzhou City based on the FLUS model by Zhenjie Liao, Lijuan Zhang

“…Finally, based on the FLUS model, the spatial pattern of urban land use under the 2035 benchmark and innovation- and entrepreneurship-oriented scenarios was simulated and the spatial distribution of the ecological resilience level under different urban development scenarios was evaluated. …”
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Seismicity characteristics based on the spatiotemporal ETAS model in North China from the perspective of different cut-off magnitude. by Jinmeng Bi, Fuyang Cao, Yong Ma

“…Combining the analysis of the spatial distribution of the background earthquake occurrence rate, low b-value, and clustering rate in North China under different cut-off magnitudes, we found that regions including the intersection area of the Zhangjiakou-Bohai seismic belt and the Tanlu seismic belt, and the western part of the northern margin of the Ordos have relatively high seismic hazard. …”
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Landslide susceptibility mapping based on data mining models in Lesser Caucasus and Kura foreland basin (Armenia and Azerbaijan) by Israr Ullah, Klaus Reicherter, Tomáš Pánek, Alessandro Tibaldi, Husam Al-Najjar, Bahareh Kalantar, Naonori Ueda, Hans-Balder Havenith

“…XGBoost achieves the highest accuracy (0.81) on the testing data set, followed by SVM (0.80) and LGR (0.73). The first two models show strong validation performance, with AUC values of 0.89 and 0.87, respectively, while LGR shows a lower AUC of 0.78. …”
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The generation method of orthophoto expansion map of arched dome mural based on three-dimensional fine color model by Chunmei Hu, Yang Wang, Guofang Xia, Yang Han, Xinjian Ma, Guofeng Jing

“…This method combines a three-dimensional virtual space simulation model with an RTT virtual camera and adopts a spatial reference orthogonal ray scanning model. …”
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Approaches to Estimating Indoor Exposure to Radon—A Systematic Review by Chunxiao Su, Mingxia Wang, Yanmei Yin, Chanjuan Sun, Zhijun Zou, Haidong Wang, Yuwei Dai

“…Through the search and screening of databases, a total of 28 related articles were included. The results show that the main methods for indoor radon estimation are mathematical models, statistical methods, and the geographic information system (GIS) method. …”
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Assessment of soil erosion and sediment transport index in the Awash River Basin, Ethiopia: an application of the USLE model and GIS techniques by Abayneh Gebremichael, Ephrem Gebremariam, Hayal Desta

“…Soil loss and the sediment transport index (STI) in the Awash River Basin were predicted using GIS and the Universal Soil Loss Equation (USLE) Model. Using the Universal Soil Loss Equation (USLE) in conjunction with Geographic Information System (GIS) and remote sensing technologies, this study evaluates the spatial distribution and intensity of soil erosion in the basin. …”
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Hydrological model and integrated GIS techniques for simulation and analysis of the long-term water balance in a coastal aquifer, Spain by Ehab Mohammad Amen, María Luisa Calvache

“…In this study, a hydrological model, WetSpass-M, was used to simulate the spatial and temporal distribution of water balance components such as the groundwater recharge, surface runoff, and actual evapotranspiration in the Motril-Salobreña coastal aquifer (south of Spain) for the period 1980–2020. …”
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Effect of involuntary and voluntary exercise in an enrichment environment on astrogliosis reaction of hippocampus white matter in type 3 diabetic rat models by Masoud Jamshidi, Mohammadreza Kordi, Fatemeh Shabkhiz

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Artificial Intelligence-Driven Identification of Favorable Geothermal Sites Based on Radioactive Heat Production: Case Study from Western Türkiye by Elif Meriç İlkimen, Cihan Çolak, Mahrad Pisheh Var, Hakan Başağaoğlu, Debaditya Chakraborty, Ali Aydın

“…The potential geothermal sites identified by the AI models align closely with those identified by statistical models and show strong agreement with independent datasets, including existing drilling locations, thermal springs, and the distribution of major earthquake epicenters in the region.…”
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Spatiotemporal pattern evolution and quantitative prediction of electrical carbon emissions from a demand-side perspective in urban areas by Ying Tian, Hui Cao, Dapeng Yan, Jinmei Chen, Yayan Hua

“…The study found that the center of gravity of carbon emissions showed a significant southwest-northeastward migration trajectory, and there was a spatial differentiation feature of central urban agglomeration and peripheral area dispersion. …”
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Identifying trade-offs and synergies among land use functions using an XGBoost-SHAP model: A case study of Kunming, China by Kun Li, Junsan Zhao, Yongping Li, Yilin Lin

“…Exploring the spatial non-stationarity and driving mechanisms of trade-offs/synergies among land use functions(LUFs), which are crucial for effectively alleviating human-land conflicts and enhancing the overall benefits and sustainable development of regional territorial space. …”
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Construction and Overall Protection of Ecological and Marine Cultural Composite Landscape Network in Quanzhou, Fujian by Dongfang LU, Yaru ZHENG, Tianteng HAN, Shunhe CHEN

“…Based on the evaluation results of the gravity model, these corridors are classified into first-class, second class, and third-class corridors, forming the spatial pattern of the Quanzhou ecological network. …”
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Comparative Analysis of Machine Learning and Deep Learning Models for Individual Tree Structure Segmentation Using Terrestrial LiDAR Point Cloud Data by Sangjin Lee, Woodam Sim, Yongkyu Lee, Jeongmook Park, Jintaek Kang, Jungsoo Lee

“…A total of 17 input features were categorized into spatial coordinates and normals, geometric structure features, and local distribution features. …”
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Sensitivity of WRF model parameterizations in simulating extreme rainfall over complex terrain – case of July 2020 over the Poyang Lake basin, China by Jinru Wu, Jianzhong Lu, Xiaoling Chen

“…Increasing the horizontal resolution has a limited improvement in rainfall simulation (1.3%), while choosing a suitable parameterization schemes combination can significantly improve the simulation accuracy by 34.3%. (2) Among the 36 experiments, c5 containing parameterization schemes of Morrison, BMJ, YSU and Slab shows overall best performance in simulating accumulated areal rainfall as well as spatial and temporal distributions. (3) CU schemes have the largest impact on the rainfall simulation, followed by MP, PBL and LSM.…”
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Analysis on Spatiotemporal Variation in Soil Drought and Its Influencing Factors in Hebei Province from 2001 to 2020 by Biao Zeng, Bo Wen, Xia Zhang, Suya Zhao, Guofei Shang, Shixin An, Zhe Li

“…The results show the following: (1) over the past 20 years, soil drought in Hebei Province has shown a trend of “first intensifying and then easing”, experiencing two turning points, and its spatial distribution showed significant agglomeration characteristics. (2) Soil moisture showed single-peak seasonal fluctuation, with severe drought from January to May, peak soil moisture from June to August, soil moisture balance from September to October, and soil moisture deficit intensified in winter. (3) Soil moisture stability showed spatial differentiation, being high in the northeast and low in the southwest. …”
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Estimation of Snow Water Equivalent in Semiarid Zone from Data of Global Numerical Models ICON and GFS/NCEP (Case Study of the Selenga River Basin) by A. N. Shikhov, V. N. Chernykh, A. A. Aurzhanaev, S. V. Pyankov, R. K. Abdullin

“…In general, reasonable estimates of the SWE spatial distribution were obtained. While in 2021, both overestimation and underestimation by 1–15 mm (20–50%) of the calculated SWE was observed at different sites compared to the measurements, in 2022, its systematic underestimation was observed, especially significant in calculations using the ICON model data. …”
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Identifying the spatiotemporal evolution of nucleic acid testing sites and their influencing factors to support public health emergency management: A case study in Hangzhou, China by Song Yao, Mingjun Cheng, Yunchen Zhu, Xiangyang Quan, Fangqi Wang, Zhaoxuan Xia, Shan Huang, Yonghua Li

“…The results show that: (1) The number of NAT sites underwent four phases over time and exhibited substantial spatial concentration in Shangcheng, Gongshu, Xihu, and Binjiang districts. (2) The population density, human footprint, and the digital elevation model were the dominant potential influencing factors for the location of NAT sites, with the explanatory power of interactions among influencing factors being higher than that of individual factors. (3) The location of NAT sites in the Shangcheng, Gongshu, Xihu, and Binjiang districts has a significant positive correlation with population density, while the relationship was not significant in other regions. …”
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Characterization of river plume dynamics for a better water quality management by René Friedland, Thomas Neumann, Sarah Piehl, Hagen Radtke, Gerald Schernewski, Gerald Schernewski

“…Due to the missing separation of the river plume area from the open sea waters, its management is suffering from the too coarse classification. We apply two model-based techniques to study the spatial and temporal variability of the Oder river plume and to follow the distribution of its nutrients and pollutants in the sea. …”
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A dissimilarity-adaptive cross-validation method for evaluating geospatial machine learning predictions with clustered samples by Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla

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