A machine learning framework for predicting agricultural terrace suitability using positive and unlabelled datasets: an application for the Troodos Mountains, Cyprus

A two-stage machine learning framework for Chl-a reconstruction and short-term prediction in eutrophic lakes using GOCI observations

Zehui Huang, Ronghua Ma, Xinhui Chen, Kun Xue, Minqi Hu, Haoze Liu

Machine-learning framework for cross-scale estimation of desert vegetation aboveground biomass and driver analysis in the Junggar Basin using UAV classification and satellite data fusion

Linlin Sun, Renping Zhang, Jing Guo, Yaming Zhang, Huaqing Liu, Xiaoyu Yu, et al.

Geomorphology-constrained bathymetric inversion of turbid tidal channels using centerline-network priors and machine learning

Jianchun Chen, Chao Gao, Yan Gu, Xiangyu Ou, Xiaoyi Cheng, Shibing Zhu, et al.

Earth Observation–Based Machine learning for operational forecasting of harmful algal blooms in the Arabian Gulf and Sea of Oman

Kaltham A. Ismail, Roqaya A. Ismail, M. Salim

High-resolution (30-m) multi-decadal reconstruction of coastal water quality via Landsat-Sentinel fusion and ensemble machine learning (1985–2024)

Zihan Chen, Peng Chen, Siqi Zhang, Yunzhou Li, Delu Pan

Urban digital twin for environmentally sensitive mobility planning: conceptual framework and application in pilot region Leipzig

Thomas Trabert, Elmar Brockfeld, Alexander Sohr, Kerstin Krellenberg, Jakob Erdmann, Xiaoxu Bei, et al.

This study presents the development and pilot implementation of a conceptual, practice-oriented Urban Digital Twin (UDT) used for environmentally sensitive mobility management within the pilot region of Leipzig (Germany). The UDT uses modular traffic simulations (SUMO-simulation…Read more