Integrated analysis of single-cell, spatial and bulk RNA-sequencing identifies a cell-death signature for predicting the outcomes of head and neck cancer by Yue Pan, Lei Fei, Shihua Wang, Hua Chen, Changqing Jiang, Hong Li, Changsong Wang, Yao Yang, Qinggao Zhang, Yongwen Chen

Get full text

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. …”
Get full text

Performance Evaluation of Real-Time Image-Based Heat Release Rate Prediction Model Using Deep Learning and Image Processing Methods by Joohyung Roh, Sehong Min, Minsuk Kong

“…For comparative analysis, the YOLO segmentation model was used. Furthermore, the fire diameter and flame height were determined from the spatial information of the segmented flame, and the HRR was predicted based on the correlation between flame size and HRR. …”
Get full text

Research Status and Development Direction of Formation Damage Prediction and Diagnosis Technologies by Zhe Sun, Zhangxing Chen

“…This study systematically reviews advancements in formation damage prediction and diagnostics, focusing on wellsite diagnosis, experimental methods, imaging techniques, analytical approaches, numerical modeling, and artificial intelligence applications. …”
Get full text

CNN-based salient features in HSI image semantic target prediction by Vishal Srivastava, Bhaskar Biswas

Get full text

Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…At large scale, increasing soil heterogeneity complicates the response relationship between soil spectra and SOC, making global models ineffective for local SOC predictions. Here, we propose a local learning approach that searches spectrally and spatially similar samples for site-specific SOC predictive modelling. …”
Get full text

Effect of bin width on variogram model accuracy: a case study of teak tree volume specific to Solomon clone in Tawau, Sabah, Malaysia by Johannah Jamalul Kiram, Rossita Mohamad Yunus, Yani Japarudin, Mahadir Lapammu, Olivier Monteuuis, Doreen Kim Soh Goh

Get full text

Spatial analysis of annual precipitation of Khuzestan province; An approach of spatial regressions analysis by Saeed balyani

“…In this research, for determine of precipitation model and predicting of it with geographical factors e.g. altitude, slope and view shade and latitude- longitude by using spatial regressions analysis such as ordinary least squares (OLS) and geographical weighted regressions(GWR), 13 synoptic stations of Khuzestan province from establishment to 2010 were used. …”
Get full text

Spatial and temporal evolution of carbon stocks in Yulin City under changing environments by Guikai Sun, Yadong Li, Rui Huang, Chongxun Mo

“…It then applies the PLUS model to predict the land use of Yulin City under different scenarios in 2030 and forecasts the future carbon stock, providing a theoretical basis for the city’s future development planning. …”
Get full text

Evaluating Remote Sensing Resolutions and Machine Learning Methods for Biomass Yield Prediction in Northern Great Plains Pastures by Srinivasagan N. Subhashree, C. Igathinathane, John Hendrickson, David Archer, Mark Liebig, Jonathan Halvorson, Scott Kronberg, David Toledo, Kevin Sedivec

“…The developed methodology of RFE for feature selection and RF for biomass yield modeling is recommended for biomass and hay forage yield prediction.…”
Get full text

Modeling land cover changes using an enhanced Markov-future land use simulation model with spatial distribution considerations: a case study in the Yellow River Basin by Jianchen Zhang, Heying Li, Hanwen Zhang, Jiayao Wang, Guangxia Wang, JianWei Xu, Haohua Zheng, HuiLing Ma

“…The traditional Markov-future land use simulation (FLUS) model for land use prediction primarily emphasizes the quantity changes and spatial distribution of land use types, but it neglects the influence of their inherent spatial characteristics on the prediction precision. …”
Get full text

High-Resolution Mapping of Litter and Duff Fuel Loads Using Multispectral Data and Random Forest Modeling by Álvaro Agustín Chávez-Durán, Miguel Olvera-Vargas, Inmaculada Aguado, Blanca Lorena Figueroa-Rangel, Ramón Trucíos-Caciano, Ernesto Alonso Rubio-Camacho, Jaqueline Xelhuantzi-Carmona, Mariano García

“…Our modeling approach allows us to estimate the continuous high-resolution spatial distribution of litter and duff fuel loads, aligned with their ecological context, which dictates their dynamics and spatial variability. …”
Get full text

Generating a 30 m Hourly Land Surface Temperatures Based on Spatial Fusion Model and Machine Learning Algorithm by Qin Su, Yuan Yao, Cheng Chen, Bo Chen

“…In this study, focusing on Chengdu city, a framework combining a spatiotemporal fusion model and machine learning algorithm was proposed and applied to retrieve hourly high spatial resolution LST data from Chinese geostationary weather satellite data and multi-scale polar-orbiting satellite observations. …”
Get full text

Spatial Evaluation of <i>Salurnis marginella</i> Occurrence According to Climate Change Using Multiple Species Distribution Models by Jae-Woo Song, Jaho Seo, Wang-Hee Lee

Get full text

Generative spatial artificial intelligence for sustainable smart cities: A pioneering large flow model for urban digital twin by Jeffrey Huang, Simon Elias Bibri, Paul Keel

“…The LFM demonstrates its novelty in comprehensive urban modeling and analysis by completing impartial city data, estimating flow data in new locations, predicting the evolution of flow data, and offering a holistic understanding of urban dynamics and their interconnections. …”
Get full text

High-resolution global modeling of wheat’s water footprint using a machine learning ensemble approach by Murat Emeç, Abdullah Muratoğlu, Muhammed Sungur Demir

“…The study revealed distinct outcomes for different clustering methods, demonstrating the model's robustness across varying spatial scales. …”
Get full text

Geometric Investigation of Al-Wind Dam Reservoir Northeastern Iraq, using Digital Elevation Models and Spatial Analyses System by Sabbar A. Saleh, Iktifaa T. Abdul Qadir, Amin M. Ibrahim, Huda M. Hussain

“… Geometric analysis of Al-Wind dam reservoir in Diyala discussed in this paper as necessary and strategic subject, spatial analysis systems were used to extract the area of Al-Wind dam reservoir from the digital elevations model (DEM), at 26 selected water levels in the reservoir with one meter interval, from 195 up to 219.5 m.a.s.l., the geometric criteria used to ​​extract the essential negative geometric elements represented by the Negative Volume (NV) Negative Planner Area (NPA) and Negative Surface Area (NSA), the perimeter of water body, the depth of water column and the shape factor of the reservoir, as well as for the positive geometric elements as Positive Volume (PV), Positive Planner Area (PPA) and Positive Surface Area (PSA) of the islands within the perimeter of the reservoir. …”
Get full text

Comparison of stochastic and deterministic models for gambiense sleeping sickness at different spatial scales: A health area analysis in the DRC. by Christopher N Davis, Ronald E Crump, Samuel A Sutherland, Simon E F Spencer, Alice Corbella, Shampa Chansy, Junior Lebuki, Erick Mwamba Miaka, Kat S Rock

“…The spatial heterogeneity in cases is reflected in modelling results, where we predict that under the current intervention strategies, the health area of Kinzamba II, which has approximately one third of the health zone's cases, will have the latest expected year for EoT. …”
Get full text

AI-powered simulation-based inference of a genuinely spatial-stochastic gene regulation model of early mouse embryogenesis. by Michael Alexander Ramirez Sierra, Thomas R Sokolowski

“…It also provides a framework for future exploration of similar spatial-stochastic systems in developmental biology.…”
Get full text

Within-Field Temporal and Spatial Variability in Crop Productivity for Diverse Crops—A 30-Year Model-Based Assessment by Ixchel Manuela Hernández-Ochoa, Thomas Gaiser, Kathrin Grahmann, Anna Maria Engels, Frank Ewert

“…The results revealed that the spatial variability in crop yield was higher than the temporal variability for most crops, except for sunflower. …”
Get full text