Hyperspectral Remote Sensing Application Division, RADI, CAS

We aim to improve the capabilities to monitor the quality and sustainability of the eco-environments, and to explore minerals and other resources of earth and deep-space, studying inversion mechanism of key parameters of environment and resources by

Collecting and interpreting geospatial data is central to everything we do as geographers, whether on computers or in the field. From local events to multi-scale processes, our faculty are developing and applying advanced remote sensing capabilities

We aim to focus on the basic theories of quality improvement, feature extraction and target detection of hyperspectral image. We try to propose fast and reliable algorithms or models for hyperspectral image fusion, feature extraction and target detec

We aims to improve the understanding and detection capabilities of vegetation photosynthesis and global climate change, by investigating the vegetation parameters inversion mechanisms of hyperspectral remote sensing and hyperspectral intelligent obser