Influence of Clouds and Aerosols on Solar Irradiance and Application of Climate Indices in Its Monthly Forecast over China by Shuting Zhang, Xiaochun Wang

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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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LiDAR-Based Road Cracking Detection: Machine Learning Comparison, Intensity Normalization, and Open-Source WebGIS for Infrastructure Maintenance by Nicole Pascucci, Donatella Dominici, Ayman Habib

“…Preprocessing included noise removal, resolution reduction to 2 cm, and ground/non-ground separation using the Cloth Simulation Filter (CSF), resulting in Bare Earth (BE), Digital Terrain Model (DTM), and Above Ground (AG) point clouds. …”
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Bayesian analysis for inference of an emerging epidemic: citrus canker in urban landscapes. by Franco M Neri, Alex R Cook, Gavin J Gibson, Tim R Gottwald, Christopher A Gilligan

“…The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. …”
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Exploring the transmission of cognitive task information through optimal brain pathways. by Zhengdong Wang, Yifeixue Yang, Ziyi Huang, Wanyun Zhao, Kaiqiang Su, Hengcheng Zhu, Dazhi Yin

“…This study not only challenges the shortest path assumption through empirical network models but also suggests that cognitive task information routing is constrained by the spatial and functional embedding of the brain network.…”
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Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

“…Convolutional Neural Networks (CNNs) have demonstrated potential in this domain but encounter limitations when addressing varying scales, resolutions, and complex spatial dependencies inherent in wildfire datasets. …”
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Spatiotemporal Assessment of Desertification in Wadi Fatimah by Abdullah F. Alqurashi, Omar A. Alharbi

“…A Desertification Index (DI) was developed based on four variables: NDVI, LST, precipitation, and ET. Five regression models—ridge, lasso, elastic net, polynomial regression (degree 2), and random forest regression—were applied to evaluate the predictive capacity of these variables in explaining desertification dynamics. …”
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Variations and impact factors of land use carbon emissions in the Yangtze River Economic Belt from a multiscale perspective by Chong Liu, Xiaoman Wang, Haiyang Li

“…This study focuses on the Yangtze River Economic Belt (YREB), utilizing land use, nighttime light, and energy consumption data to compute LUCE at provincial, prefectural, and county scales, employing spatial autocorrelation, geographic detectors, and the Multiscale Geographically Weighted Regression (MGWR) model to analyze the spatiotemporal dynamics and impact factors of LUCE across different scales. …”
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Rolling Bearing Fault Diagnosis Based on Recurrence Plot by Zheming Chen, Bin Xu, Zhong Zhang

“…Compared to existing methods, this approach leverages the recurrence plot technique to convert vibration signals into color images, which carry more information than grayscale images. For the prediction model, the traditional convolutional neural network is enhanced by integrating bidirectional gated recurrent unit and multi-head attention mechanism, allowing it to capture temporal features alongside the spatial features typically extracted by convolutional neural network. …”
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Urban expansion and the loss of potential crop yield in the North China Plain: implications for regional food security (1980–2020) by Shuangqing Sheng, Shuangqing Sheng, Jinchuan Huang

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Machine Learning Recognizes Stages of Parkinson’s Disease Using Magnetic Resonance Imaging by Artur Chudzik

“…Using interpretable metrics, such as the volume- and centroid-based spatial distances, models achieved high diagnostic accuracy, presenting a promising framework for early-stage PD identification based on MRI scans.…”
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Electrofacies Analysis Using a Geostatistical Approach, Northern Iraq Case Study by Hussein S. Hussein

“…R2 ¼ 0.72 showed a statistically significant association between the described and anticipated lithologies. For subsequent prediction for other formations in the same well, the model with a higher coefficient of determination (0.72) might be evaluated. …”
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Drought risks are projected to increase in the future in central and southern regions of the Middle East by Younes Khosravi, Taha B. M. J. Ouarda

“…Abstract Drought prediction is vital for sustaining water security in regions highly exposed to climate change. …”
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Estimation of Soil Organic Carbon Content of Grassland in West Songnen Plain Using Machine Learning Algorithms and Sentinel-1/2 Data by Haoming Li, Jingyao Xia, Yadi Yang, Yansu Bo, Xiaoyan Li

“…Nine experiments were conducted under three variable scenarios to select the optimal model. We used this optimal model to achieve high-precision predictions of SOC content. …”
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Effective Urban Region Representation Learning Using Heterogeneous Urban Graph Attention Network (HUGAT) by Namwoo Kim, Yoonjin Yoon

“…Objective: This study aims to develop a model that effectively represents urban regions by incorporating both spatial features and human activity patterns, in order to better understand and predict urban dynamics. …”
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Selecting the best habitat mapping technique: a comparative assessment for fisheries management in Exmouth Gulf by Scott N. Evans, Scott N. Evans, Nick Konzewitsch, Renae K. Hovey, Gary A. Kendrick, Lynda M. Bellchambers

“…While advances in remote sensing, acoustic methodologies, geostatistical modelling, and predictive species distribution models have improved our ability to map underwater habitats, selecting the most appropriate approach, particularly in turbid or remote regions, remains challenging. …”
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Spatio-temporal characteristics and analysis of influencing factors of inclusive green growth in China’s oil and gas resource industry by Xiangyu Sun, Yanqiu Wang

“…This study introduces a novel index system for inclusive green growth (IGG) specific to China’s oil and gas resource industry, encompassing dimensions such as industrial development, social equity in opportunities, poverty and income inequality reduction, and green ecology. This research marks the first application of the CRITIC combined weighting-TOPSIS model to assess inclusive green growth in the oil and gas resource industry (IGGOG) across 30 Chinese provinces from 2012 to 2021. …”
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Potential of EnMAP Hyperspectral Imagery for Regional-Scale Soil Organic Matter Mapping by Yassine Bouslihim, Abdelkrim Bouasria

“…The resulting SOM predictions exhibited spatially consistent patterns that corresponded with known soil–landscape relationships, highlighting the potential of EnMAP hyperspectral data for mapping soil properties despite its limited geographical availability. …”
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All-Weather Precipitable Water Vapor Retrieval over Land Using Integrated Near-Infrared and Microwave Satellite Observations by Shipeng Song, Mengyao Zhu, Zexing Tao, Duanyang Xu, Sunxin Jiao, Wanqing Yang, Huaxuan Wang, Guodong Zhao

“…Accurate estimation of PWV is essential for numerical weather prediction, climate modeling, and atmospheric correction in remote sensing. …”
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Downscaling Satellite Night-Time Light Imagery While Addressing the Blooming Effect by Nikolaos Tziokas, Ce Zhang, Alexandros Tziokas, Qunming Wang, Peter M. Atkinson

“…For the ATPK-based residual part, considering the PSF led to increased accuracy of prediction. The suggested methodology has the potential to increase the detail and accuracy of the NTL data available for modeling socioeconomic phenomena at the city scale, with wide potential for application in future socioeconomic research.…”
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