Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

“…The forecasting method along with the selection of spatial drivers to predict land cover change, demonstrated high efficiency compared to other studies. …”
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Innovation of Yang Hussein Jassim’s method in solving nonlinear telegraph equations across multiple dimensions by Naser Rhaif Swain, Hassan Kamil Jassim

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Unleashing the potential of geostationary satellite observations in air quality forecasting through artificial intelligence techniques by C. Zhang, X. Niu, H. Wu, Z. Ding, K. L. Chan, J. Kim, T. Wagner, C. Liu, C. Liu, C. Liu

“…GeoNet leverages spatiotemporal series of satellite NO<span class="inline-formula">₂</span> observations to capture the intricate relationships among air quality, meteorology, and emissions in both temporal and spatial domains. Evaluation against ground-based measurements demonstrates that GeoNet accurately predicts diurnal variations and spatial distribution details of next-day NO<span class="inline-formula">₂</span> pollution, yielding a coefficient of determination of 0.68 and a root mean square of error of 12.31 <span class="inline-formula">µg</span> m<span class="inline-formula">⁻³</span>, significantly surpassing traditional air quality model forecasts. …”
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A GNN-Based False Data Detection Scheme for Smart Grids by Junhong Qiu, Xinxin Zhang, Tao Wang, Huiying Hou, Siyuan Wang, Tiejun Yang

“…However, since topological changes of power networks in smart grids often already predict the occurrence of anomalies, traditional models based on STGNNs to portray network evolution cannot be directly utilized in smart grids. …”
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Measurement of Suspended Sediment Concentration at the Outlet of the Yellow River Canyon: Using Sentinel-2 Images and Machine Learning by Genxin Song, Youjing Jiang, Xinyu Lei, Shiyan Zhai

“…Overall, the random forest model outperformed traditional methods in SSC prediction for sediment-laden rivers.…”
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Municipal solid waste management practices and sanitary landfill site selection using the AHP approach for emerging industrial zones by Mekonnen Amberber Degefu, Wubshet Asefa

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Female homicides in Brazil: global burden of disease study, 2000–2018Research in context by Nadia Machado de Vasconcelos, Juliana Bottoni de Souza, Adauto Martins Soares Filho, Polyanna Helena Coelho, Sofia Reinach, Caroline Stein, Crizian Saar Gomes, Luisa Sorio Flor, Emmanuela Gakidou, Antonio Luiz Pinho Ribeiro, Deborah Carvalho Malta

“…Summary: Background: Female homicides are a public health-relevant issue, and its spatial distribution may evidence socioeconomic vulnerabilities. …”
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High Resolution Sea Ice Concentration Using a Sentinel-1 U-Net Ice-Water Classifier by Jozef Rusin, Anthony P. Doulgeris, K. Andrea Scott, Thomas Lavergne, Catherine Taelman

“…We trained the U-Net across multilooking levels to balance resolution, noise reduction, and computational efficiency, allowing the model to handle noise artefacts effectively. …”
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Research on step-by-step visual servo control system of anchor drilling robot by Mengyu LEI, Xuhui ZHANG, Wenjuan YANG, Jicheng WAN, Yuyang DU, Henghan YU, Chenhui TIAN

“…Secondly, through displacement and angular sensors deployed on manipulator joints, this study constructed an enhanced kinematic model using the modified Denavit-Hartenberg (MDH) method, enabling accurate spatial position resolution of the end-effector and determination of its initial and target positions. …”
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Urbanization and forecast possibilities of land use changes by 2050: New evidence in Ho Chi Minh city, Vietnam by Tuan Nguyen Tran, Hegedűs Gábor, Phuong Nguyen Thi Tung

“…In contrast, the urban land group had a strong increasing trend, with an increase of nearly 25% after 20 years. In terms of spatial distribution, HCM city tended to develop in three main directions: east, southwest, and northwest. …”
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Integrated geophysical prospecting for deep ore detection in the Yongxin gold mining area, Heilongjiang, China by Yechang Yin, Jun Chen, Zhonghai Zhao, Yuanjiang Yang, Chenglu Li, Haina Li, Xiang Zhao

“…Abstract Geophysical exploration techniques play a pivotal role in enhancing the accuracy of mineral prospecting predictions. However, relying solely on individual methods often introduces uncertainties. …”
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Colonization in North American Arid Lands: The Journey of Agarito (Berberis trifoliolata) Revealed by Multilocus Molecular Data and Packrat Midden Fossil Remains. by Diego F Angulo, Leonardo D Amarilla, Ana M Anton, Victoria Sosa

“…The most important prediction of packrat middens palaeomodelling lies in the Mexican Plateau, a finding congruent with current and past niche modelling predictions for agarito and genetic results. …”
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LSTM-Based Neural Network to Recognize Human Activities Using Deep Learning Techniques by Sunitha Sabbu, Vithya Ganesan

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Evaluation of Personal and Built Environment Attributes to Physical Activity: A Multilevel Analysis on Multiple Population-Based Data Sources by Wei Yang, Karen Spears, Fan Zhang, Wai Lee, Heidi L. Himler

“…Multiple data sources were utilized including individual level data for health behaviors and health status from the Nevada Behavioral Risk Factor Surveillance System (BRFSS) and community level data from different data sources including indicators for recreation facilities, safety, air quality, commute time, urbanization, population density, and land mix level. Mixed model logistic regression and geographic information system (GIS) spatial analysis were conducted. …”
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A Spatiotemporal Attention-Guided Graph Neural Network for Precise Hyperspectral Estimation of Corn Nitrogen Content by Feiyu Lu, Boming Zhang, Yifei Hou, Xiao Xiong, Chaoran Dong, Wenbo Lu, Liangxue Li, Chunli Lv

“…A hyperspectral maize nitrogen content prediction model is proposed, integrating a dynamic spectral–spatiotemporal attention mechanism with a graph neural network, with the aim of enhancing the accuracy and stability of nitrogen estimation. …”
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Snow drought to hydrologic drought progression using machine learning and probabilistic analysis by Pouya Moghaddasi, Keyhan Gavahi, Hamid Moradkhani

“…This study explores the relationship between Snow Water Equivalent (SWE) and streamflow in snow-dominated watersheds using the Long Short-Term Memory (LSTM) model and probabilistic analysis. While LSTM model is typically used for prediction, we employed it primarily to understand how snow affects streamflow. …”
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Automated Detection of Center-Pivot Irrigation Systems from Remote Sensing Imagery Using Deep Learning by Aliasghar Bazrafkan, James Kim, Rob Proulx, Zhulu Lin

“…YOLOv11, using Landsat 8 panchromatic data, achieved the highest detection accuracy (precision: 0.98; recall: 0.91; and F1-score: 0.94) among all tested datasets and models. Spatial autocorrelation and hotspot analysis revealed systematic prediction errors, suggesting a need to adjust training data regionally. …”
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Mapping soil organic carbon stocks of different land use types in the Southern Moscow region by applying machine learning to legacy data by Yury A. Dvornikov, Lukyan A. Mirniy, Ekaterina S. Mukvich, Kristina V. Ivashchenko

“…The root mean square error of cross-validation (RMSEcv = 0.67 kg/m2) was chosen to describe the uncertainty of soil organic carbon stock prediction. According to the model, the total soil organic carbon stocks in the upper 10 cm soil layer of the Podolsky District were 2.65 0.72 Tg, for the Serpukhovsky District 2.77 0.73 Tg.…”
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Deep Learning-Based Atmospheric Visibility Detection by Yawei Qu, Yuxin Fang, Shengxuan Ji, Cheng Yuan, Hao Wu, Shengbo Zhu, Haoran Qin, Fan Que

“…Each model’s characteristics and application methods are discussed, highlighting the efficiency of CNNs in spatial feature extraction, RNNs in temporal tracking, GANs in image restoration, and Transformers in capturing long-range dependencies. …”
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The mean and extreme tropical cyclone wave climate throughout the Coral Sea, from 1979 to 2020 by John G. Miller, Guilherme Vieira da Silva, Darrell Strauss

“…An available WAVEWATCH III® hindcast model dataset with surface wind forcing from the National Centres for Environmental Prediction supplied Climate Forecasts System Version 2 was used. …”
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