Landslide assessment considering spatial calibration zoning of physical and mechanical parameters of rock and soil mass by Weimin YIN, Yuanyao LI, Xing LI, Ming LI, Le JU, Ou XIE

“…However, traditional SINMAP models overlook the spatial differences in rock and soil characteristics due to geological environmental changes, resulting in low accuracy in assessment results. …”
Get full text

Attention Mechanism with Spatial-Temporal Joint Deep Learning Model for the Forecasting of Short-Term Passenger Flow Distribution at the Railway Station by Zhicheng Dai, Dewei Li, Shiqing Feng

“…We conduct a comparative analysis of the prediction performance and time complexity of the proposed architecture against existing baseline models, demonstrating superior performance and robustness exhibited by the ST-Bi-LSTM model (achieving a reduction in RMSE of over 10%). …”
Get full text

Geospatial Modelling of Flood Susceptibility of the Calabar City, Cross River State, Nigeria by Joel Efiong, Eme Efiong, Oluyemi Akintoye, Ebin Inah, Obianuju Awan, Francis Ogban

Get full text

Modelling of spatially correlated weather-based electricity forecasting using combined frequency-based signal decomposition with optimized boosting approach by Indra A. Aditya, Didit Adytia

“…The primary contribution is a spatially correlation-driven feature selection technique to choose ideal weather input sites, coupled with the extraction of predominant frequency components from the load signal to enhance model input. …”
Get full text

Nonlocal fractional MGT-non-Fourier photothermal model with spatial and temporal nonlocality for controlling the behavior of semiconductor materials with spherical cavities by Mofareh Alhazmi, Ahmed E. Abouelregal

“…In this work, we present the nonlocal Moore-Gibson-Thompson photothermal (NMGTPT) theory, a novel framework that integrates spatial and temporal nonlocality to address limitations in both traditional and advanced thermoelastic models. …”
Get full text

Mean limiting pressure factors determination in contiguous pile walls using RAFELA and nonlinear regression models in spatially random soil by Divesh Ranjan Kumar, Sittha Kaorapapong, Warit Wipulanusat, Suraparb Keawsawasvong

Get full text

High-spatial-resolution surface soil moisture retrieval using the Deep Forest model in the cloud environment over the Tibetan Plateau by Zhenghao Li, Qiangqiang Yuan, Xin Su

“…As a key climate variable, soil moisture plays a crucial role in drought detection, flood warning, and crop yield prediction. In recent years, the demand for high-spatial-resolution soil moisture has increased, particularly in environmental management. …”
Get full text

An EG-Tree Model Incorporating Spatial Heterogeneity for Analyzing Multifactorial Coupling Effects on Carbon Emissions Across Industries and Regions in China by Jinrui Zang, Xin Hu, Kun Qie, Zian Zhang, Shi Zhang

Get full text

BUILDING PREDICTIVE MODELS TO ASSESS DEGRADATION OF SOIL ORGANIC MATTER OVER TIME USING REMOTE SENSING DATA by Abdulsalam Aljumaily, Ammar Kashmolaa

“…The results of the study showed the possibility of applying predictive models to Satellite data for a particular area and for previous years to give results with high spatial accuracy (R2 = 0.9581). …”
Get full text

Digital Twin Framework for Bridge Slab Deterioration: From 2D Inspection Data to Predictive 3D Maintenance Modeling by Hyunhye Song, Kiyeol Kim, Jihun Shin, Gitae Roh, Changsu Shim

“…Based on this data, eight representative damage states were defined to support the prediction of the service life. The damage and repair history was embedded into the 3D bridge models using a unique coding system to enable temporal and spatial tracking. …”
Get full text

Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…The proposed charging demand gravity model optimizes users' charging station selection behavior by integrating factors such as charging station size， electricity price， and user time cost， resulting in a more reasonable spatial and temporal distribution of the charging load[Conclusions] This study constructed a spatial and temporal distribution prediction model for electric vehicle charging loads by integrating information from multiple sources. …”
Get full text

Assessing spatial soil erosion under climate change using SWAT model in a semi-arid watershed of northeastern Tunisia by Fathia Jarray, Taoufik Hermassi, Haykel Sellami, Mohamed Ali Ben Abdallah, Mohamed Mechergui

Get full text

Spatial–Temporal Reconstruction of Trajectories in Free Space Using Automatic Target Position Detection Data by Yang Chen, Xin Chen, Bin Bai, Linjiang Zheng

“…Then, based on the reconstructed spatial trajectory of the target, this paper proposes a time series prediction model based on historical trajectories and an attention mechanism, which considers the impact of the target’s activity cycle and the surrounding status to predict the time series inside the trajectory. …”
Get full text

Modelling the Spatial Distribution of <i>Dosidicus gigas</i> in the Southeast Pacific Ocean at Multiple Temporal Scales Based on Deep Learning by Mingyang Xie, Bin Liu, Xinjun Chen, Wei Yu, Jintao Wang, Jiawen Xu

“…With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (<i>Dosidicus gigas</i>). …”
Get full text

SFSCDNet: A Deep Learning Model With Spatial Flow-Based Semantic Change Detection From Bi-Temporal Satellite Images by K. S. Basavaraju, N. Sravya, Vibha Damodara Kevala, Shilpa Suresh, Shyam Lal

“…Existing deep learning-based methods, particularly those relying on triple-branch architectures, often struggle to accurately localize and predict changes in complex spatial environments characterized by diverse land-cover types. …”
Get full text

Efficient room-level heat load prediction in buildings using spatiotemporal distribution characteristics by Xin Tan, Kaixuan Xu, Yahui Wang, Qihui Yu, Yongheng Yu, Guoxin Sun

“…A thermodynamic model built with DesignBuilder and a ResGRU neural network enables overall heat load prediction, with spatiotemporal matrix decomposition ensuring rapid room-level estimations. …”
Get full text

Numerical simulation study on the evolution of wrinkling defects in carbon fiber laminates based on spatial decomposition damage variable method by ZHENG Haocheng, ZHOU Bo, LI Hui, WANG Yajie, SUN Ning, ZHANG Xueyan

“…In order to investigate the compression damage evolution of carbon fiber laminates with wrinkles and accurately predict the mechanical behavior of damage initiation and propagation, a progressive damage finite element model was proposed based on three-dimensional elastic theory by employing a spatial decomposition of damage variables method to establish the damage constitutive relation. …”
Get full text

High‐Resolution Downscaling of Disposable Income in Europe Using Open‐Source Data by Mehdi Mikou, Améline Vallet, Céline Guivarch, David Makowski

“…It also yielded better results for the estimation of spatial inequality within administrative units. Using SHAP values, we explored the contribution of the model predictors to income predictions and found that, in addition to geographic predictors, distance to public transport or nighttime light intensity were key drivers of income predictions. …”
Get full text

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. …”
Get full text

Sensitivity of spatial and temporal precipitation patterns to aerosol loadings during an extreme precipitation event by Wenjia Cao, Robert V Rohli, Paul W Miller

“…National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) final (FNL) data were used as input to the Weather Research and Forecasting (WRF) model, to simulate the case study of the catastrophic 2016 flood in Louisiana, USA, for three aerosol loading scenarios: virtually clean, average, and very dirty, corresponding to 0.1×, 1×, and 10× the climatological aerosol concentration. …”
Get full text