Prediction of spatiotemporal evolution and zoning of ecological sensitivity in the upper reaches of Minjiang river, sichuan, China by Lingfan Ju, Yan Liu, Shunduo Liu, Qing Xiang, Wenkai Hu, Peng Yu

“…In this study, an ecological sensitivity index system is established to quantitatively analyze the interrelationships of ecological factors. The CA-MC model and center of gravity migration are used to investigate the spatial and temporal evolution of ecological sensitivity in the upper Minjiang River basin from 2000 to 2020 and to predict the ecological sensitivity in 2040. …”
Get full text

Multi-Task Trajectory Prediction Using a Vehicle-Lane Disentangled Conditional Variational Autoencoder by Haoyang Chen, Na Li, Hangguan Shan, Eryun Liu, Zhiyu Xiang

“…Trajectory prediction under multimodal information is critical for autonomous driving, necessitating the integration of dynamic vehicle states and static high-definition (HD) maps to model complex agent–scene interactions effectively. …”
Get full text

Short-term displacement prediction for newly established monitoring slopes based on transfer learning by Yuan Tian, Yang-landuo Deng, Ming-zhi Zhang, Xiao Pang, Rui-ping Ma, Jian-xue Zhang

Get full text

Spatial Association Network of Land-Use Carbon Emissions in Hubei Province: Network Characteristics, Carbon Balance Zoning, and Influencing Factors by Yong Huang, Zhong Wang, Heng Zhao, Di You, Wei Wang, Yanran Peng

“…This study constructs a LUCE spatial association network for Hubei Province using a modified gravity model to uncover the spatial linkages in carbon emissions. …”
Get full text

Suitable habitat prediction and desertified landscape remediation potential of three medicinal Glycyrrhiza species in China by Fanyan Ma, Xiang Huang, Zhenan Yang, Panxin Niu, Keyao Pang, Mei Wang, Guangming Chu

“…This study employed the MaxEnt model to predict the potential habitats of these three species in China under climate change, and examined the relationship between their distribution and desert ecosystems. …”
Get full text

Prediction of the Morphological Characteristics of Asymmetric Thaw Plate of Qinghai–Tibet Highway Using Remote Sensing and Large-Scale Geological Survey Data by Jianbin Hao, Zhenyang Zhao, Jianbing Chen, Zhiyun Liu, Fuqing Cui, Xiaona Liu, Wenting Lu, Jine Liu

“…Through integrating remote sensing data and large-scale geological survey results with an earth–atmosphere coupled numerical model and a random forest (RF) prediction framework, we assessed the spatial distribution of thaw asymmetry along the permafrost section of the QTH. …”
Get full text

Real-time prediction of port water levels based on EMD-PSO-RBFNN by Lijun Wang, Shenghao Liao, Sisi Wang, Jianchuan Yin, Ronghui Li, Jingyu Guan

“…Subsequently, PSO was applied to fine-tune the center and spread parameters of the RBFNN, thereby enhancing the model’s predictive performance. The optimized PSO-RBFNN model was employed to make predictions on the decomposed sub-series. …”
Get full text

Predicting the current potential and future world wide distribution of the onion maggot, Delia antiqua using maximum entropy ecological niche modeling. by Shuoying Ning, Jiufeng Wei, Jinian Feng

“…Onion maggot, Delia antiqua, larvae are subterranean pests with limited mobility, that directly feed on bulbs of Allium sp. and render them completely unmarketable. Modeling the spatial distribution of such a widespread and damaging pest is crucial not only to identify current potentially suitable climactic areas but also to predict where the pest is likely to spread in the future so that appropriate monitoring and management programs can be developed. …”
Get full text

Digital Mapping of Soil Equivalent Calcium Carbonate Using Landsat 8 Satellite Images and Environmental Data by Machine Learning Models in Badr Watershed, Kurdistan Province by M. Zarinibahador

“…The present study aimed to digitally map calcium carbonate equivalent using auxiliary environmental variables, Landsat 8 satellite images, and predictive models and to present the best models in the Badr watershed in the south of Qorveh district. …”
Get full text

A cluster-based local modeling paradigm for high spatiotemporal resolution VPD prediction using multi-source data and machine learning by Mi Wang, Zhuowei Hu, Xiangping Liu, Wenxing Hou

“…The results show that the local modeling significantly enhances prediction accuracy, with the XGBoost model outperforming others across all clusters and maintaining high precision across seasons scales and different land use types. …”
Get full text

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model by Y. Liu, H. Huang, S.-C. Wang, T. Zhang, D. Xu, Y. Chen

“…A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. …”
Get full text

IoT-Based Traffic Prediction for Smart Cities by Zhinong Miao, Qilong Liao

“…The primary objective was to develop a predictive model that improves traffic forecasting accuracy, reduces congestion, and optimizes real-time traffic management. …”
Get full text

Unifying spatiotemporal and frequential attention for traffic prediction by Qi Guo, Qi Tan, Jun Tang, Benyun Shi

“…By leveraging deep learning to capture spatial correlations in traffic flow and applying spectral analysis to fuse time series data with underlying periodic correlations in both the time and frequency domains, we develop an innovative traffic prediction model called the Space-Time-Frequency Attention Network (STFAN). …”
Get full text

Intelligent Prediction and Numerical Simulation of Landslide Prediction in Open-Pit Mines Based on Multi-Source Data Fusion and Machine Learning by Li Qing, Linfeng Xu, Juehao Huang, Xiaodong Fu, Jian Chen

“…Five machine learning models for landslide prediction are compared using this dataset. …”
Get full text

Regularity and predictability of human mobility in personal space. by Daniel Austin, Robin M Cross, Tamara Hayes, Jeffrey Kaye

“…Studying a data set of almost 15 million observations from 19 adults spanning up to 5 years of unobtrusive longitudinal home activity monitoring, we find that in-home mobility is not well represented by a universal scaling law, but that significant structure (predictability and regularity) is uncovered when explicitly accounting for contextual data in a model of in-home mobility. …”
Get full text

Predicting changes in maximum temperatures in the mid-future period in Sistan and Baluchestan under SSP scenarios by abdolreza kashki, ghorban jafari

“…IDW interpolation in GIS was used to map spatial temperature changes. Paired-sample t-tests evaluated differences between baseline and mid-future periods.Finding: The CanESM5 model performed best in predicting temperature changes. …”
Get full text

Extending isolation by resistance to predict genetic connectivity by Robert J. Fletcher Jr, Jorge A. Sefair, Nicholas Kortessis, Roldolfo Jaffe, Robert D. Holt, Ellen P. Robertson, Sarah I. Duncan, Andrew J. Marx, James D. Austin

“…This framework extends isolation‐by‐resistance modelling to account for some common processes that can impact gene flow, which can improve predicting genetic connectivity across complex landscapes.…”
Get full text

Constraint-incorporated deep learning model for predicting heat transfer in porous media under diverse external heat fluxes by Ziling Guo, Hui Wang, Huangyi Zhu, Zhiguo Qu

“…The temperature field within porous media is considerably affected by different boundary conditions, and effective thermal conductivity varies with spatial structure morphologies. At present, traditional prediction methods for the temperature field are expensive and time consuming, particularly for large structures and dimensions, whereas deep learning surrogate models have limitations related to constant boundary conditions and two-dimensional input slices, lacking the three-dimensional topology and spatial correlations. …”
Get full text

Spatiotemporal Characteristics, Causes, and Prediction of Wildfires in North China: A Study Using Satellite, Reanalysis, and Climate Model Datasets by Mengxin Bai, Peng Zhang, Pei Xing, Wupeng Du, Zhixin Hao, Hui Zhang, Yifan Shi, Lulu Liu

“…Finally, we developed a prediction model for burned areas, leveraging the strong correlation between the FFMC and burned areas. …”
Get full text

Post-Disaster Recovery Effectiveness: Assessment and Prediction of Coordinated Development in the Wenchuan Earthquake-Stricken Areas by Liang Zhao, Chunmiao Zhang, Xia Zhou

“…By constructing a framework to assess post-disaster coordinated development, this study utilized the entropy weight method and mean-variance method for the comprehensive weighting of evaluation indicators. The gray system prediction model G(1,1) was used to forecast the coordinated development levels of the three cities from 2019 to 2025. …”
Get full text