Investigating the Impact of Climate Change on the Effective Indicators in Desertification and Predicting its Spatial Changes by Azam Sadat Hosseini Khezr Abad, Abassali Vali, Amirhossein Halabian, Mohammad Hossein Mokhtari, Seyyed Ali Mousavi

“…Excessive dryness of arid regions has increased the intensity and spread of desertification. Investigating spatial and temporal patterns of desertification caused by climate change in the northwest of Yazd province using the Iranian model of desertification potential assessment (IMDPA) is one of the main objectives of this research. …”
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Spatial-temporal load prediction of electric bus charging station based on S2TAT by Guangnian Xiao, Hailin Tong, Yaqing Shu, Anning Ni

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Modelling and Using Spatial Effects in Nationwide Historical Data Improve Genomic Prediction of Rice Heading Date in Japan by Shoji Taniguchi, Takeshi Hayashi, Hiroshi Nakagawa, Kei Matsushita, Hiromi Kajiya-Kanegae, Jun-Ichi Yonemaru, Akitoshi Goto

“…To improve the prediction accuracy of models using historical data, we incorporated a spatial model to account for spatial structures among field stations, in addition to conventional genomic prediction models. …”
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Development of a river dissolved oxygen prediction model integrating spatial effects and multiple deep learning algorithm by Yubo Zhao, Mo Chen

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A Criterion of Reduction Quality of Femoral Neck Fractures Based on Spatial Residual Displacements of Femoral Head by Shuang‐Shuang Cui, Li‐Kun Zhao, Jing‐Bo Yu, Jian‐Xiong Ma, Xin‐Long Ma

“…The purpose of this study is to construct a reduction quality criterion based on spatial residual displacements of 3D reconstruction and to predict the occurrence of ONFH. …”
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Spatial Modeling of Auto Insurance Loss Metrics to Uncover Impact of COVID-19 Pandemic by Shengkun Xie, Jin Zhang

Subjects: “…spatial model…”
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Modeling Spatial and Temporal Changes in Land-Uses and Land Cover of the Urmia Lake Basin Applying Cellular Automata and Markov Chain by Hadi Eskandari Damaneh, Hamid Gholami, Hassan Khosravi, Rasoul Mahdavi Najafabadi, Asadollah Khoorani, Gimmy Li

“…After the integrated CA-Markov approach assessed the model, the land-use maps were predicted for the years 2028 and 2038. …”
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A crop model based on dual attention mechanism for large area adaptive yield prediction by Wei Xiang, Long Long, Zichen Liu, Feng Dai, Yucheng Zhang, Hu Li, Lin Cheng

“…Although existing models have improved accuracy by increasing model complexity and coupling different deep learning models, their generalization performance is poor due to significant spatial differences in crop growth environments, making it difficult to explore common features of crop environments in different regions.To address this issue, this paper comprehensively considers crop growth cycles and environmental factors such as soil and weather, presenting a large-scale crop yield prediction model based on an attention mechanism.The model consists of two modules: time attention module and feature attention module. …”
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Event Prediction Using Spatial–Temporal Data for a Predictive Traffic Accident Approach Through Categorical Logic by Eleftheria Koutsaki, George Vardakis, Nikos Papadakis

“…Finally, we implement the traffic accident prediction model using the Prolog language with the corresponding Queries in JPL.…”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

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OceanLSTM: xLSTM with spatial attention for salt spray formation and migration prediction in marine hot-humid environments by Chuan Chen, Ganxin Jie, Jun Wang, Shouhe Wang, Xiaonong Xu

Subjects: “…salt spray prediction…”
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PM2.5 prediction and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration using spatial temporal graph convolutional networks by Yawen Zhao

“…To address this, this study uses spatiotemporal analysis and Spatial Temporal Graph Convolutional Networks (ST-GCN) to evaluate the variation and driving factors of PM _2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) urban agglomeration from 2014 to 2024, and to make predictions. …”
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Spatial and temporal evolution of carbon stocks in Yulin City under changing environments by Guikai Sun, Yadong Li, Rui Huang, Chongxun Mo

“…Abstract Land use changes directly or indirectly affect the regional carbon balance. Investigating the spatial and temporal evolution of regional carbon stock and the contribution of land use driving factors is crucial for understanding the formation mechanisms of ecosystem carbon cycles and carbon budget balance.In this study, the researchers selected the model simulation method after comparing various carbon stock estimation methods. …”
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Machine Learning Traffic Flow Prediction Models for Smart and Sustainable Traffic Management by Rusul Abduljabbar, Hussein Dia, Sohani Liyanage

“…Specifically, this paper evaluates the impact of multisource sensor inputs and spatial detector interactions on machine learning-based traffic flow prediction. …”
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Prediction of land use around urban metro stations using the CA-Markov model by Xingzhong Nong, Ming Geng, Xia Jia

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SPATIAL MODEL OF BUILT-IN LAND CHANGE (NDBI) IN LANGSA CITY USING CELLULAR AUTOMATA MARKOV (CA-MARKOV) by Kania Maulia Rizky, Triyatno Triyatno

“…The method used in this study is a spatial-based quantitative method with the Cellular Automata Markov approach to create built-up land modelling in Langsa City, and the Analytical Hierarchy Process method to identify variables that influence changes in built-up land in Langsa City. …”
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Study on Key Influencing Factors of Carbon Emissions from Farmland Resource Utilization in Northeast China Under the Background of Energy Conservation and Emission Reduction by Mulin Sun, Yuhao Fu, Mingyao Sun, Run Huang, Yun Teng

“…A gray prediction model is constructed to predict the carbon emissions from the utilization of farmland resources in the next 10 years, and the logarithmic mean Divisia index model is used to analyze the effects of the various influencing factors on the carbon emissions from farmland utilization. …”
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Landslide Susceptibility Prediction Based on a CNN–LSTM–SAM–Attention Hybrid Model by Honggang Wu, Jiabi Niu, Yongqiang Li, Yinsheng Wang, Daohong Qiu

“…In this study, we propose a Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Spatial Attention Mechanism (SAM) hybrid deep learning model designed for spatial landslide susceptibility prediction. …”
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A homotopy estimation based temporal-spatial spectrum prediction for UAV communications with arbitrary flight paths by Shan Luo, Wenjun Zhou, Lifan Wu, Qixiang Zhang, Rongping Lin, Yao Yan, Hui Li, Siyu Xie

“…This paper introduces a temporal-spatial spectrum prediction approach for arbitrary flight within a specific region. …”
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Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

“…The selected features were classified using a CNN-LSTM model, capturing both spatial and temporal patterns. …”
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