This is the fourth story of the "Practitioners' Insights" column, in which the Global Times exclusively interviewed the China ...

Abstract: Existing deep learning-based remote sensing images semantic segmentation methods require ... The network can be trained without any labeled data, and the trained model can be fine-tuned with ...

Accurate climate prediction, particularly precipitation forecasting, remains a cornerstone for agriculture, water resource management, and disaster ...

Abstract: In a forest inventory context, estimation for small areas and for remote and inaccessible regions may be problematic ... However, estimates obtained using probability-based, model-assisted ...

With the global population rapidly increasing and resources becoming ever more limited, the world faces unprecedented ...

Texas A&M researchers have developed a model that delivers comprehensive damage maps and recovery forecasts within hours of a ...

BEIJING -- A group of Chinese researchers have designed a Generalized Data Completion Model (GDCM) applicable to multi-source remote sensing data in aiming to solve the missing measurement caused by ...

Coral reefs form a vital part of the marine ecosystem, playing host to diverse species and supporting multiple industries, ...

A Jesuit priest, Pedro Porras was the first to research and document the Amazon rainforest’s Upano Valley culture dating back ...

A new study presents an advanced remote sensing and machine learning model that accurately distinguishes between natural and ...

The review identifies nine major functional domains where AI is significantly altering sustainable practices, including ...

This repo is used for recording, and tracking recent Remote Sensing Spatio-Temporal Vision-Language Models (RS-STVLMs). If you find any work missing or have any suggestions (papers, implementations, ...