Multi-Source Data Fusion-Based Grid-Level Load Forecasting by Hai Ye, Xiaobi Teng, Bingbing Song, Kaiming Zou, Moyan Zhu, Guangyu He

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New Paradigms for Geomorphological Mapping: A Multi-Source Approach for Landscape Characterization by Martina Cignetti, Danilo Godone, Daniele Ferrari Trecate, Marco Baldo

“…A fully remote mapping approach, based on multi-source and multi-sensor applications, was implemented for the recognition of landforms and processes. …”
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A federated LSTM network for load forecasting using multi-source data with homomorphic encryption by Mengdi Wang, Rui Xin, Mingrui Xia, Zhifeng Zuo, Yinyin Ge, Pengfei Zhang, Hongxing Ye

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An exploration of the spatial and temporal factors influencing industrial park vitality using multi-source geospatial data by Xiao Ding, Fang Zheng, Guifen Lyu, Botao Feng

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Exploring the Relationship between Spatiotemporal Distribution of Urban Vibrancy and Neighborhood Attributes by Coupling Multi-Source Data: A Case of Nanshan District in Shenzhen by Liu Feng, Tang Zhong, Zhang Liang, Yu Lingmin, Liu Ke

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The Design and Implementation of an Intelligent Carbon Data Management Platform for Digital Twin Industrial Parks by Lingyu Wang, Hairui Wang, Yingchuan Li, Xingyun Yan, Min Wang, Meixing Guo, Mingzhu Fang, Yue Kong, Jie Hu

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A Novel Method for Traffic Parameter Extraction and Analysis Based on Vehicle Trajectory Data for Signal Control Optimization by Yizhe Wang, Yangdong Liu, Xiaoguang Yang

“…An innovative algorithm is proposed to identify which intersections vehicles pass through, effectively solving the challenge of mapping GPS points to road network nodes. A dual calculation method based on instantaneous speed and time difference is adopted, improving parameter estimation accuracy through multi-source data fusion. …”
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Dynamic Assessment of Population Exposure to Urban Flooding Considering Building Characteristics by Shaonan Zhu, Xin Yang, Jiabao Yang, Jun Zhang, Qiang Dai, Zhenzhen Liu

“…We developed an agent-based simulation framework that incorporates (1) building-based urban environment, (2) hydrodynamic flood modeling outputs, and (3) empirically grounded human mobility patterns derived from multi-source geospatial big data. The implemented model systematically evaluates transient population exposure through spatiotemporal superposition analysis of flood characteristics and human occupancy patterns across different urban functional zones in Lishui City, China. …”
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Spatiotemporal Dynamics of Urban and Rural Settlements in Tanzania (1975–2020): Drivers, Patterns, and Regional Disparities by Jiaqi Zhang, Rongrong Zhang, Jiaqi Fan, Xiaoke Guan, Hui Liang

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AI-based carbon peak prediction and energy transition optimization for thermal power industry in energy-intensive regions of China by Chenhao Huang, Zhongyang Lin, Jian Wu, Penghan Li, Chaofeng Zhang, Yanzhao Liu, Weirong Chen, Xin Xu, Jinsong Deng

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Research on Thermal Environment Influencing Mechanism and Cooling Model Based on Local Climate Zones: A Case Study of the Changsha–Zhuzhou–Xiangtan Urban Agglomeration by Mengyu Ge, Zhongzhao Xiong, Yuanjin Li, Li Li, Fei Xie, Yuanfu Gong, Yufeng Sun

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Multi-Decision Vector Fusion Model for Enhanced Mapping of Aboveground Biomass in Subtropical Forests Integrating Sentinel-1, Sentinel-2, and Airborne LiDAR Data by Wenhao Jiang, Linjing Zhang, Xiaoxue Zhang, Si Gao, Huimin Gao, Lin Sun, Guangjian Yan

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Assessing landslide susceptibility in the Upper Ravi river catchment, Himachal Pradesh, India: a comprehensive analysis using the logistic regression model by Pooja Sharma, Vishwa Bandhu Singh Chandel, Simrit Kahlon, Som Nath Thakur

“…Conclusions The study successfully maps landslide-susceptible zones using logistic regression and multi-source geospatial data. It provides actionable insights for local authorities, planners, and disaster risk managers. …”
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