Improved digital mapping of soil texture using the kernel temperature–vegetation dryness index and adaptive boosting by Xu Zhai, Yuzhong Liu, Yuanyuan Hong, Yunjie Yang, Pengju Wang, Zhicheng Ye, Xiaoyan Liu, Tianlong She, Lihui Wang, Chen Xu, Lili Zhang, Qiang Wang

“…In this study, we collected 399 soil samples collected from Mingguang City in southeast China and made spatial predictions of soil texture based on remote sensing indices such as the kernel normalized difference vegetation index computed from Landsat8 data and topographic attributes computed via digital elevation model as environmental covariates. …”
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Spatiotemporal prediction of soil organic carbon density in Europe (2000–2022) using earth observation and machine learning by Xuemeng Tian, Sytze de Bruin, Rolf Simoes, Mustafa Serkan Isik, Robert Minarik, Yu-Feng Ho, Murat Şahin, Martin Herold, Davide Consoli, Tomislav Hengl

“…Prediction accuracy varies by land cover, depth interval and year of prediction with the worst accuracy for shrubland and deeper soils 100–200 cm. …”
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IMPROVE OF UNCERTAIN MICROSATELLITE MAGNETIC CLEANLINESS BASED ON MAGNETIC FIELD SPATIAL HARMONICS COMPENSATION by Б.І. Кузнецов, Т.Б. Нікітіна, І.В. Бовдуй, К.В. Чуніхін, В.В. Коломієць, Б.Б. Кобилянський

“…Both vector game solution calculated based on particles multi-swarm optimization (PMSO) algorithms from Pareto optimal solutions taking into account binary preference relations. Prediction model and location of compensating units in spherical coordinates as well as multipole harmonic coefficients of dipoles, quadrupoles and octupoles are calculated during prediction and control of uncertain microsatellite MC. …”
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A Moroccan soil spectral library use framework for improving soil property prediction: Evaluating a geostatistical approach by Tadesse Gashaw Asrat, Timo Breure, Ruben Sakrabani, Ron Corstanje, Kirsty L. Hassall, Abdellah Hamma, Fassil Kebede, Stephan M. Haefele

“…A soil spectrum generated by any spectrometer requires a calibration model to estimate soil properties from it. To achieve best results, the assumption is that locally calibrated models offer more accurate predictions. …”
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A dynamic adaptive graph convolutional recurrent network model for efficient mid-short term prediction of global sea surface salinity by Guangwen Peng, Yingbing Liu, Cong Xiao, Wenying Du, Changjiang Xiao

“…AGCRUs dynamically construct topological relationships via graph convolution to model spatial variations, while GRUs capture temporal dependencies. …”
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A Robot Error Prediction and Compensation Method Using Joint Weights Optimization Within Configuration Space by Fantong Meng, Jinhua Wei, Qianyi Feng, Zhigang Dong, Renke Kang, Dongming Guo, Jiankun Yang

“…A spatial-interpolation-based unbiased estimation method with joint weights optimization is proposed for robot errors prediction, and the particle filter method is utilized to search for the optimal joint weights, enhancing the anisotropic characteristics of the prediction model. …”
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Predicting cortical bone resorption in the mouse tibia under disuse conditions caused by transient muscle paralysis by Himanshu Shekhar, Sanjay Singh, Jitendra Prasad

“…Dissipation energy density induced by loading, based on interstitial fluid flow, has been adopted as the mechanotransduction-triggering stimulus. The developed model uses the loss of stimulus due to the disuse of bone as an input and predicts the quantity of bone loss with spatial accuracy. …”
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Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins by Senlin Tang, Fubao Sun, Wenbin Liu, Hong Wang, Yao Feng, Ziwei Li

“…Abstract Streamflow prediction in ungauged basins (PUB) is challenging, and Long Short‐Term Memory (LSTM) is widely used to for such predictions, owing to its excellent migration performance. …”
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Modeling the effects of land use change on agricultural carrying capacity and food security by R. Harini, R. Rijanta, E.H. Pangaribowo, R.F. Putri, I. Sukri

“…Predictions of spatial land changes will reveal changes in land function, carrying capacity and food security between regions.METHODS: Land changes were studied using remote sensing imagery-based mapping methods and spatial simulations using the cellular automata approach. …”
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Information-Theoretic Modeling of Categorical Spatiotemporal GIS Data by David Percy, Martin Zwick

“…An NLCD tool reports how much change occurred for each category of land use; for the study area examined, the most dynamic class is Evergreen Forest (EFO), so the presence or absence of EFO in 2021 was chosen as the dependent variable that our data modeling attempts to predict. RA predicts the outcome with approximately 80% accuracy using a sparse set of cells from a spacetime data cube consisting of neighboring lagged-time cells. …”
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FEN-MRMGCN: A Frontend-Enhanced Network Based on Multi-Relational Modeling GCN for Bus Arrival Time Prediction by Ting Qiu, Chan-Tong Lam, Bowie Liu, Benjamin K. Ng, Xiaochen Yuan, Sio Kei Im

“…The proposed module captures spatial relationships in dense, multi-route areas by using graph convolution layers based on multi-relational modeling to aggregate spatial information. …”
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Combination of spatial and temporal de-noising and artifact reduction techniques in multi-channel dry EEG by Milana Komosar, Gabriella Tamburro, Gabriella Tamburro, Uwe Graichen, Silvia Comani, Silvia Comani, Jens Haueisen

“…IntroductionDry electroencephalography (EEG) allows for recording cortical activity in ecological scenarios with a high channel count, but it is often more prone to artifacts as compared to gel-based EEG. Spatial harmonic analysis (SPHARA) and ICA-based methods (Fingerprint and ARCI) have been separately used in previous studies for dry EEG de-noising and physiological artifact reduction. …”
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Pedestrian Movement Prediction and Pattern Analysis by V. Toshev, K. Karamitov, D. Petrova-Antonova, D. Petrova-Antonova

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Can transparency governance promote interregional coordinated carbon emission reduction? A new perspective from China provincial transparency index by Nan Jiang, Juan Huang

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Research on traffic state prediction method based on traffic flow prediction under multi-time granularity by Yue Chen, Jian Lu

“…In order to improve the accuracy of traffic state prediction model, a traffic state prediction method based on multi-time granularity traffic flow prediction is proposed. …”
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Improving GNSS precise point positioning with tropospheric constraints from data-driven numerical weather prediction model by Yuanfan Deng, Wu Chen, Junsheng Ding, Ahmed El-Mowafy, Duojie Weng, Long Tang, Lei Bai, Xiaolong Mi

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Modeling and predicting land use and land cover changes using remote sensing in tropical coastal ecosystems of southern Peru by Ellen Delgado, Elgar Barboza, Nilton B. Rojas-Briceño, Alexander Cotrina-Sanchez, Armando Valdés-Velásquez, Rocío López de la Lama, Camila Llerena-Cayo, Santiago de la Puente

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Predicting Wheat Potential Yield in China Based on Eco-Evolutionary Optimality Principles by Shen Tan, Shengchao Qiao, Han Wang, Sheng Chang

“…However, most existing crop models for wheat PY rely on type-specific parameters that describe wheat traits, which often require calibration and, in turn, reduce prediction confidence when applied across different spatial or temporal scales. …”
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Urban Traffic Travel Time Short-Term Prediction Model Based on Spatio-Temporal Feature Extraction by Leilei Kang, Guojing Hu, Hao Huang, Weike Lu, Lan Liu

“…In order to improve the accuracy of short-term travel time prediction in an urban road network, a hybrid model for spatio-temporal feature extraction and prediction of urban road network travel time is proposed in this research, which combines empirical dynamic modeling (EDM) and complex networks (CN) with an XGBoost prediction model. …”
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A prediction model of soil organic carbon into river and its driving mechanism in red soil region by Yanhu He, Yuyin Yang, Daoguo Xu, Zirui Wang

“…This study integrates the Soil and Water Assessment Tool (SWAT) for sediment yield simulation and a Soil Organic Carbon Content (SOCC) model to quantify SOCR at the basin scale. A Random Forest-based prediction model was developed to explore the spatial-temporal variability and driving mechanisms of SOCR in the Dongjiang River Basin (DRB), a representative red soil region in southern China. …”
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