Drone-assisted climate-smart agriculture (DACSA): A spatially-based outcome prediction model as an initial approach to track yield changes in shallot planting areas

“…Machine learning algorithms were employed to make predictions, and the yield projections were integrated into spatial maps. …”
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Spatial autocorrelation in machine learning for modelling soil organic carbon by Alexander Kmoch, Clay Taylor Harrison, Jeonghwan Choi, Evelyn Uuemaa

“…This study compares various methods to account for spatial autocorrelation when predicting soil organic carbon (SOC) using random forest models. …”
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Interpretable machine learning unveils threshold responses and spatial patterns of global soil respiration by Junjie Jiang, Lingxia Feng, Junguo Hu, Chao Zhu

“…Additionally, we found significant biases in the annual Rs calculated by area weighting based on climate and ecosystem classifications because these factors characterise spatial heterogeneity differently. Such dynamics should be considered when modelling global Rs and analysing the results because they can help improve the estimation accuracy of global Rs prediction models.…”
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Sparse Boosting for Additive Spatial Autoregressive Model with High Dimensionality by Mu Yue, Jingxin Xi

“…In this paper, we consider additive spatial autoregressive model with high-dimensional covariates. …”
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Cognitive and Spatial Forecasting Model for Maritime Migratory Incidents: SIFM by Donatien Agbissoh Otote, Antonio Vázquez Hoehne

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ASSESSMENT OF ROMANIAN ALPINE HABITATS SPATIAL SHIFTS BASED ON CLIMATE CHANGE PREDICTION SCENARIOS by ADRIAN CONSTANTINESCU, JENICĂ HANGANU, ANTHONY LEHMANN, NICOLAS RAY

“…Maxent and BIOCLIM were used to create spatial distribution models for Mesophilous oligotrophic mountain pasture and Subalpine oligotrophic pastures. …”
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Prediction of spatial yield strength distribution in Al–Mg–Sc alloy fabricated by coaxial laser wire directed energy deposition by Xianyue Liu, Yuelan Di, Gang Wang, Longcen Ji, Yining Yuan, Yiming Rong

“…The spatially heterogeneous thermal history during additive manufacturing (AM) leads to variations in the mechanical properties of the fabricated parts. …”
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Spatial-Similarity Dynamic Graph Bidirectional Double-Cell Network for Traffic Flow Prediction by Zhifei Yang, Zeyang Li, Jia Zhang

“…This research advances traffic prediction methodologies through its integrated approach to dynamic spatial correlation modeling and bidirectional temporal learning, providing valuable insights for intelligent transportation system development.…”
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Integrating machine learning and spatial clustering for malaria case prediction in Brazil’s Legal Amazon by Kayo Henrique de Carvalho Monteiro, Élisson da Silva Rocha, Luis Augusto Morais, Elton Gino Santos, Sebastião Rogerio da S. Neto, Vanderson Sampaio, Patricia Takako Endo

“…The integration of K-means clustering further improved the model predictive accuracy by accounting for spatial heterogeneity and capturing localized transmission dynamics. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Therefore, this paper proposes a surface settlement prediction model based on environmental risk zoning. …”
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Single-nucleotide polymorphism analysis accurately predicts multiple impairments in hippocampal activity and memory performance in a murine model of idiopathic autism by Isabel Barón-Mendoza, Luis A. Márquez, Aliesha González-Arenas, Jessica Guzmán-Condado, Vladimir A. Martínez-Rojas, Johaly Anguiano-Buenfil, Montserrat Mejía-Hernández, Jorge Luis Almazán, Leonor Pérez-Martínez, Gustavo Pedraza-Alva, Emilio J. Galván, Angélica Zepeda

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Modeling to predict cases of hantavirus pulmonary syndrome in Chile. by Elaine O Nsoesie, Sumiko R Mekaru, Naren Ramakrishnan, Madhav V Marathe, John S Brownstein

“…Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes.…”
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Enhancing urban air quality prediction using time-based-spatial forecasting framework by Shrikar Jayaraman, Nathezhtha T, Abirami S, Sakthivel G

“…The outcomes demonstrate the TBS model’s ability to accurately predict AQI values. …”
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Autonomous Driving Decision-Making Method Based on Spatial-Temporal Fusion Trajectory Prediction by Yutao Luo, Aining Sun, Jiawei Hong

“…In this paper, we propose a driving strategy learning method based on spatial-temporal feature prediction. Firstly, the spatial interaction between vehicles is implicitly modeled using a graph convolutional neural network and multi-head attention mechanism, and the gated loop unit is embedded to capture the sequential temporal relationship to establish a prediction model incorporating spatial-temporal features. …”
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Self-adaptive spatial-temporal network based on heterogeneous data for air quality prediction by Feng Chang, Liang Ge, Siyu Li, Kunyan Wu, Yaqian Wang

“…However, accurately predicting future air quality remains a challenging task because of the complex spatial-temporal dependencies of air quality. …”
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Dynamic Spatial–Temporal Graph Neural Network for Cooling Capacity Prediction in HVDC Systems by Hao Sun, Shaosen Li, Jianxiang Huang, Hao Li, Guanxin Jing, Ye Tao, Xincui Tian

“…Traditional machine learning methods, while effective in static scenarios, struggle to capture these dependencies, and existing deep learning models often lack the ability to jointly model spatial and temporal relationships. …”
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Exploration of geo-spatial data and machine learning algorithms for robust wildfire occurrence prediction by Svetlana Illarionova, Dmitrii Shadrin, Fedor Gubanov, Mikhail Shutov, Usman Tasuev, Ksenia Evteeva, Maksim Mironenko, Evgeny Burnaev

“…The goal of this study is to explore the potential of predicting wildfire occurrences using various available environmental parameters - meteorological, geo-spatial, and anthropogenic - and machine learning (ML) algorithms. …”
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Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public. by Kim M Pepin, Amy J Davis, Daniel G Streicker, Justin W Fischer, Kurt C VerCauteren, Amy T Gilbert

“…We developed a dynamic patch-occupancy model which predicts spatio-temporal spreading while accounting for heterogeneous sampling. …”
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Transformer based spatially resolved prediction of mechanical properties in wire arc additive manufacturing by Mohammad Keshmiri, Shirin Dehgahi, Abdullah Mohiuddin, Ahmed J. Qureshi

“…The results demonstrate that the framework achieves good prediction capabilities using a small dataset. It provides a state-of-the-art methodology for predicting the spatial and temporal evolution of mechanical properties leveraging the transformer architecture. …”
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Modeling spatial distributions of Amah Mutsun priority cultural plants to support Indigenous cultural revitalization by Annalise Taylor, Alexii Sigona, Maggi Kelly

“…We utilized community science datasets with an ensemble modeling approach that combines the results of five machine learning models to predict not only the distribution of each species, but also the relative certainty of those predictions spatially. …”
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