Machine learning for lithology identification in electrical image logging: A case study of the Chang 73 Sub-Member, Yanchang Formation, East Gansu region, Ordos Basin - Jiaqi Li; Hongping Bao; Shilong Liu; Pingping Shi; Feiming Gao; Liubin Wei; Langlang Wang; Hongyan Yu (Earth Science Informatics, 2026)

Few-Shot intelligent identification of rock thin sections based on SAM - Yuan Zhou; Qing Li; Zhuofeng Zhang; Zhengyu Wei; Qiang Du; Xinlong Li (Earth Science Informatics, 2026)

Lithology prediction via multiscale feature-fusion convolutional neural networks - Wenliang Nie; Heyu Zhang; Jiayi Gu; Wei Huang; Bo Li; Jianfeng Liu; Xiangfei Nie (Earth Science Informatics, 2025)

A deep learning pipeline for large earthquake analysis using high-rate global navigation satellite system data - Claudia Quinteros-Cartaya; Javier Quintero-Arenas; Andrea Padilla-Lafarga; Carlos Moraila; Johannes Faber; Wei Li; Jonas Köhler; Nishtha Srivastava (Earth Science Informatics, 2025)
Deep learning techniques for processing large and complex datasets have unlocked new opportunities for fast and reliable earthquake analysis using Global Navigation Satellite System (GNSS) data. This work presents a deep learning model, MagEs, to estimate earthquake magnitudes using data from high-rate GNSS stations. Furthermore, MagEs is integrated with the DetEQ model for earthquake detection within the SAIPy package, creating a comprehensive pipeline for earthquake detection and magnitude estimation using HR-GNSS data. The MagEs model provides magnitude estimates within seconds of detection when using stations within 3 degrees of the epicenter, which are the most relevant for real-time applications. MagEs has also been trained on data from longer distances, up to 7.5 degrees away, and can process data from a single station or combine up to three stations at a time. The model was trained using synthetic data based on rupture scenarios in the Chile subduction zone, and the results confirm strong performance for Chilean earthquakes. Although the model also demonstrated robust performance on data from other regions, further improvements might be achieved through the application of transfer learning using datasets from the specific region of interest. The model has not yet been deployed in an operational real-time monitoring system, but simulation tests that update data in a second-by-second manner demonstrate its potential for future real-time adaptation.

Knowledge graphs analysis for research on minerals in coal - Pengfei Li; Na Xu; Qingfeng Wang; Yuqing Wang; Fei Li; Wei Zhu; Qing Li (Earth Science Informatics, 2025)

Segmentation of urban green space and water body based on high-resolution remote sensing images - Chen Yang; Ying Wei; Junwei Liu; Hao Yang; Zhoubang He; Jiaguang Li (Earth Science Informatics, 2025)

A multi-stage adaptive otsu thresholding algorithm for pore segmentation in rock thin-section images - Chengzhen Yu; Wenhui Wu; Jun Zheng; Wei Zeng; Dongyu Zheng; Zhiwu Li; Caihua Chen; Sheng Wang (Earth Science Informatics, 2025)

Optimizing landslide susceptibility mapping using integrated forest by penalizing attributes model with ensemble algorithms - Wei Chen; Chao Wang; Xia Zhao; Li Bai; Qingfeng He; Xi Chen; Qifei Zhao; Ruixin Zhao; Tao Li; Paraskevas Tsangaratos; Ioanna Ilia (Earth Science Informatics, 2025)

Deep learning in the advanced core sample porosity determination with XCT image - Hung-Yu Wu; Ching-Li Kuo; Chen-Yi Lin; Wei-Ta Chu (Earth Science Informatics, 2025)

Exploring advanced machine learning techniques for landslide susceptibility mapping in Yanchuan County, China - Wei Chen; Chao Guo; Fanghao Lin; Ruixin Zhao; Tao Li; Paraskevas Tsangaratos; Ioanna Ilia (Earth Science Informatics, 2024)

Tropical cyclone ensemble forecast framework based on spatiotemporal model - Tongfei Li; Kaihua Che; Jiadong Lu; Yifan Zeng; Wei Lv; Zhiyao Liang (Earth Science Informatics, 2024)

Ultra-short-term photovoltaic power prediction based on modal reconstruction and BiLSTM-CNN-Attention model - Wei Liu; Qian Liu; Yulin Li (Earth Science Informatics, 2024)

High-efficiency method for 3D visualization of marine environmental information - Chun-xin Li; Chong-wei Zheng (Earth Science Informatics, 2023)

Forecasting system with sub-model selection strategy for photovoltaic power output forecasting - Zhenkun Liu; Ping Li; Danxiang Wei; Jianzhou Wang; Lifang Zhang; Xinsong Niu (Earth Science Informatics, 2023)

Knowledge mapping and trends in research on remote sensing change detection using CiteSpace analysis - Yuanhe Yu; Yuzhen Shen; Yaoyao Liu; Yuchun Wei; Xudong Rui; Bingbing Li (Earth Science Informatics, 2023)

Prediction of groundwater level using the hybrid model combining wavelet transform and machine learning algorithms - Aihua Wei; Yuanyao Chen; Duo Li; Xianfu Zhang; Tao Wu; Hui Li (Earth Science Informatics, 2022)

Heterogeneous reservoir prediction of ultra-deep strike-slip fault-damaged zone constrained with local seismic anomaly data - Xiangwen Li; Jingye Li; Xukui Feng; Guangjian Dan; Gulan Zhang; Lei Zhang; Ming Zhang; Liangliang Zhang; Hongbo Zhou; Wei Zhao (Earth Science Informatics, 2022)

Characterization of seismic information entropy attributes of braided river delta sedimentary microfacies for the upper Shaximiao formation in the Wubaochang area, northeastern Sichuan Basin, China - Yanguo Qiao; Zhigang Liu; Wei Luo; Dianguang Zang; Chenrui Li; Fan Yang; Guoshuai Si (Earth Science Informatics, 2022)

Research on fish identification in tropical waters under unconstrained environment based on transfer learning - Shan Zhang; Weifang Liu; Yupeng Zhu; Wei Han; Yi Huang; Jianqiang Li (Earth Science Informatics, 2022)
Seafloor unconstrained environment video is shot in uncontrolled open sea area. There are multiple backgrounds, complex illumination and weather changes, and rapid growth of algae and attached lenses, which affect the stability of video shooting quality, resulting in difficulty in image recognition. At present, there is still no algorithm that is superior to other methods generally, and it is necessary to build a model combined with specific scenes and applications. In this paper, a fish identification method in tropical waters based on transfer learning under unconstrained environment is proposed. Firstly, the image is pre-processed by affine transformation to realize data enhancement. Furthermore, RestNet50 deep convolutional neural network is constructed based on transfer learning to compare the effect of fish recognition before and after transfer learning. The results show that, the accuracy and loss indicators are better than those of non-transfer learning when the trained model of imagenet is introduced as the initial weight of the network. When the model is trained to 150 epochs, the indicators begin to converge, which can better complete the fish identification task in tropical waters under unconstrained environment.

A novel large-scale land degradation remote sensing index and its application in Three River Source Region - Ye Wen; Qiubing Wang; Bing Guo; Chao Meng; Yumei Cai; Haorun Xue; Huihui Zhao; Wenqian Zang; Cuixia Wei; Yang Yu; Yifeng Liu; Jialin Li (Earth Science Informatics, 2022)

Spatial–temporal evolution pattern and prediction analysis of flood disasters in China in recent 500 years - Cuixia Wei; Bing Guo; Hailing Zhang; Baomin Han; Xiangshen Li; Huihui Zhao; Yuefeng Lu; Chao Meng; Xiangzhi Huang; Wenqian Zang; Hongwei Wu (Earth Science Informatics, 2022)

Fracture recognition in ultrasonic logging images via unsupervised segmentation network - Wei Zhang; Tong Wu; Zhipeng Li; Shiyuan Liu; Ao Qiu; Yanjun Li; Yibing Shi (Earth Science Informatics, 2021)

Change detection in SAR images based on superpixel segmentation and image regression - Rui Zhao; Guo-Hua Peng; Wei-dong Yan; Lu-Lu Pan; Li-Ya Wang (Earth Science Informatics, 2021)

Seismic spatiotemporal characteristics in the Alpide Himalayan Seismic Belt - Xiaolu Li; Lirong Yin; Li Yao; Wenping Yu; Xiaojun She; Wei Wei (Earth Science Informatics, 2020)

Terrace extraction based on remote sensing images and digital elevation model in the loess plateau, China - Lanhua Luo; Fayuan Li; Ziyang Dai; Xue Yang; Wei Liu; Xuan Fang (Earth Science Informatics, 2020)

Research on key techniques of multi-resolution coastline image fusion based on optimal seam-line - Bo Wang; Hongtao Li; Wei Hu (Earth Science Informatics, 2020)

Designing sea ice web APIs for ice information services - Xintao Liu; Songnian Li; Wei Huang; Jun Gong (Earth Science Informatics, 2015)

Voltage stability in a long-distance power transmission system impacted by the geoelectric field due to a geomagnetic disturbance - Wei-li Wu; Lian-guang Liu; Chun-ming Liu (Earth Science Informatics, 2014)