Application of machine learning in soil heavy metals pollution assessment in the southeastern Tibetan plateau by Yan Li, Yilong Yu, Shiyuan Ding, Wenjing Dai, Rongguang Shi, Gaoyang Cui, Xiaodong Li

“…This study applies a machine learning approach based on the self-organizing map hyper-clustering, alongside advanced methodologies such as Positive Matrix Factorization (PMF), Incremental Spatial Autocorrelation, and Bivariate Local Indicators of Spatial Association (BiLISA), to analyze the ecological risk of soil HMs in representative watersheds of the southeastern Tibetan Plateau, focusing on spatial pattern clustering, pollutant source identification, and interaction risk assessment. …”
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Quantifying Thermal Discharges from Nuclear Power Plants: A Remote Sensing Analysis of Environmental Function Zones by Xiang Wang, Xiu Su, Lin Wang, Xinxin Wang, Qinghui Meng, Jin Xu

“…This study investigates the long-term thermal impact of the Haiyang Nuclear Power Plant on the adjacent marine environment using a decade-long Landsat thermal infrared dataset. Spatial and temporal patterns of thermal discharge were analyzed, focusing on the temperature difference between intake and outlet water, the warming trend in the thermal mixing zone, and the spatial distribution of the thermal plume. …”
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Spatiotemporal evolution analysis of OpenStreetMap buildings in the Yangtze River Delta of China based on Tree-like model by Rong Chen, Lingjia Liu, Xiaohui Ding, Wei Jiang

“…As a result, there is a relatively small number of studies on OSM building data in China, especially in terms of spatial patterns and evolution of OSM building data. …”
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Constructing Urban Agglomeration Ecological Networks to Reflect Biodiversity and Conservation Objectives by Yunyu Ge, Mengdi Zhang, Ce Xu, Boyu Xin

“…By conducting a comprehensive analysis of the current state and spatial distribution patterns of various ecological network components, the study proposes specific implementation strategies. …”
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Surface Heat Island in Shanghai and Its Relationship with Urban Development from 1989 to 2013 by Liang Chen, Rong Jiang, Wei-Ning Xiang

“…A remote sensing approach was taken to derive the spatial patterns of Shanghai’s land surface temperature (LST) from Landsat Thematic Mapper (TM) images and Operational Land Imager (OLI) data. …”
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Modeling of Angiogenesis in Tumor Blood Vessels via Lattice Boltzmann Method by Sara Zergani, K. K. Viswanathan, D. S. Sankar, P. Sambath

“…It is observed that the flow features are extremely sensitive to stenosis severity, even at small strains and stresses, and that a severe effect on flow patterns and wall shear stresses is noticed in the tumor blood vessels. …”
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Advanced Image Quality Assessment for Hand- and Finger-Vein Biometrics by Simon Kirchgasser, Christof Kauba, Georg Wimmer, Andreas Uhl

“…While NIQE (natural image quality evaluator) and BRISQUE (blind/referenceless image spatial quality evaluator) if trained in common images with usual distortions do not work well for assessing vasculature pattern samples’ quality, their variants being trained on high- and low-quality vasculature sample data behave as expected from a biometric quality estimator in most cases (deviations from the overall trend occur for certain datasets or feature extraction methods). …”
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Spatio-temporal evolution in habitat quality and its driving factors in Han River Basin, China by Jiefeng Kou, Jun Liu, Hongliang Wang, Shun Huang, Zheng Zhou, Chao Yang, Xiaolong Huang

“…In addition, it presents ‘high in the middle, low on both sides’ in space. (2) Approximately 69.31% of the basin maintained stable HQ, while 14.73% of the area experienced improvement and 15.96% suffered degradation. The spatial distribution revealed a vertical differentiation pattern characterized by ‘concentrated degradation at low elevations and localized improvement at middle and high elevations.’ (3) Over the past two decades, the primary driving factors for the evolution of HQ in the HRB were land use intensity and elevation, followed by temperature and GDP. …”
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Spatio-temporal distribution characteristics and its influencing factors of traditional villages in concentrated and connected areas in Yuxian County, Hebei Province, China by Guaini Jiang, Xiaohuang Lin, Miao Wang, Xia Cui, Man Feng

“…Research has found that: (1) The spatial distribution of traditional villages in Yuxian County exhibits cohesive characteristics, with a pattern of “small-scale aggregation” and “large-scale scattered,” alongside significant spatial differences and imbalances. (2) The evolution of the spatio-temporal distribution: From the Yuan Dynasty to the Qing Dynasty, the distribution center of traditional villages followed a movement process of “southeast-northwest-southeast,” and the distribution pattern evolved from a “multi-core” pattern in the lower reaches of the Huliu River to a belt-shaped distribution pattern. (3) The factors influencing the spatio-temporal distribution include altitude and slope, rivers and water systems, population, economy, transportation, and historical and cultural resources. …”
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Construction and characterization of cultural landscape genomic maps of traditional miao communities in Leigong Mountain by Han Gu, Hongyu Chen, Yiting Luo, Ke Xu

“…ArcGIS10.8 was used as the technical platform to construct five types of cultural landscape genome mapping systems, namely cultural landscape factor information mapping, spatial sequence mapping, public space pattern mapping, arrangement pattern mapping, and spatial pattern mapping. …”
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Research on the suitability of production, living and ecological space development in Duolun County, Inner Mongolia by Dongchang Liu, Aruhan, Aruhan, Sai Na

“…The findings reveal that: (1) The suitability of production space, ecological space, and the comprehensive suitability of PLES in the study area exhibit a spatial differentiation pattern with higher values in the southwest and lower values in the northeast. …”
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Mapping urban functional zones with remote sensing and geospatial big data: a systematic review by Shouhang Du, Xiuyuan Zhang, Yichen Lei, Xin Huang, Wei Tu, Bo Liu, Qingyan Meng, Shihong Du

“…Data features consist of the remote sensing image-derived features (such as visual, spatial pattern, and abstract features) and the geospatial big data-derived features (such as spatial, attribute, and temporal features). …”
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Analysis of Sulawesi Earthquake Data from 2019 to 2023 using DBSCAN Clustering by Ody Octora Wijaya, Rushendra

“…The utilization of the DBSCAN algorithm was chosen for its ability to cluster data based on spatial density, well-suited for analyzing the spatial patterns of earthquakes. …”
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Time sequence of non-grain cultivated land restoration in Shandong Peninsula urban agglomeration, China by Jinhua Liu, Yuqing Wang, Zhongxiao Cong, Baokun Zhu, Keqiang Wang, Yan Zhao

“…The innovative ‘3D magic cube’ model was then employed to classify restoration priority zones across Shandong's counties, revealing spatial distribution patterns and investment priorities for non-grain cultivated land restoration. …”
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PERKEMBANGAN PERUMAHAN DAN DIVERSIFIKASI MATA PENCAHARIAN PENDUDUK KECAMATAN UNGARAN BARAT DAN UNGARAN TIMUR by Puji Hardati

“…The methods used to analyze the housing development process approach is use to analyze the spatial pattern of housing, with the nearest neighbor analysis, and to study the livelihood diversification using descriptive analysis. …”
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Large Eddy Simulation of Shallow Cumulus Clouds in the Southern Great Plains With an Interactive Land Surface Model by Jake J. Gristey, Graham Feingold, Wayne M. Angevine, Yao‐Sheng Chen

“…They impart complex patterns of solar heating on the surface below. These patterns are dominated by cloud shadows, which drive spatial variability in the surface latent and sensible heat fluxes via the surface energy balance. …”
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Improving the Parameterization of Complex Subsurface Flow Properties With Style‐Based Generative Adversarial Network (StyleGAN) by Wei Ling, Behnam Jafarpour

“…Abstract Representing and preserving complex (non‐Gaussian) spatial patterns in aquifer flow properties during model calibration are challenging. …”
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Swin-transformer for weak feature matching by Yuan Guo, Wenpeng Li, Ping Zhai

“…Abstract Feature matching in computer vision is crucial but challenging in weakly textured scenes due to the lack of pattern repetition. We introduce the SwinMatcher feature matching method, aimed at addressing the issues of low matching quantity and poor matching precision in weakly textured scenes. …”
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Impact of built environment on commuting carbon emissions using big data: a case study of Jinan’s main urban area by Yukang Li, Jianming Ye, Zhaoqi Li, Mengmeng Zhu, Yingbin Li

“…Through the integration of multi-source big data, including travel trajectory, urban land use, and street view data, the research analyzes the spatial patterns of commuting behavior and emissions. …”
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Exploring the Main Driving Factors for Terrestrial Water Storage in China Using Explainable Machine Learning by Xinjing Ma, Haijun Huang, Jinwen Chen, Qiang Yu, Xitian Cai

“…The launch of the Gravity Recovery and Climate Experiment (GRACE) satellite mission in 2002 has provided precise measurements of TWS, enabling systematic investigations into its spatial pattern and driving mechanisms. However, a comprehensive evaluation of the spatial drivers of TWS variations across China is still lacking. …”
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