Artificial Intelligence, Remote Sensing and Digital Twin Driving Innovation in Sustainable Natural Resources and Ecology

Dear Colleagues,

Developing artificial intelligence and advancing “artificial intelligence science” are key strategic initiatives to accelerate the transformation of science and intelligence and enhance the intelligent management of natural resources and ecosystems. We will systematically leverage cutting-edge technologies such as big data, large models, the Internet of Things, remote sensing, and digital twins to achieve deep integration and practical application of AI in various fields, including intelligent breeding, intelligent perception and monitoring, intelligent management, intelligent ecosystem diagnosis, and intelligent conservation and innovative utilization of natural resources.

This Topic focuses on utilizing artificial intelligence, big data, large models, the Internet of Things, remote sensing, digital twins, and other technologies to carry out breeding, monitoring, management, evaluation, and decision support for natural resources and ecosystems. It includes, but is not limited to, the following: monitoring forest cover, vegetation, land use changes, mineral resource development, biodiversity, predicting ecological risks of climate change, and assessing the effects of ecological restoration through remote sensing and AI technology. It also includes simulating tree growth and constructing ecosystem models using digital twin technology to support precise agricultural management (soil moisture, pests, etc.), identifying and predicting change trends in advance, and assisting in precise agricultural and forestry management.

Prof. Dr. Huaiqing Zhang
Prof. Dr. Ting Yun
Topic Editors