The remote sensing data processing lab is focused on hyperspectral remote sensing image analysis, high-spatial-resolution remote sensing image interpretation, SAR data processing, LiDAR technology, environment remote sensing and industrial application.
Hyperspectral remote sensing image analysis
Hyperspectral Remote Sensing (HRS) technology, collects hyperspectral data of ground targets with dozens to hundreds of narrow and continuous bands, from ultraviolet, visible, near infrared, mid infrared to thermal infrared spectral range. Therefore, hyperspectral remote sensing is a combination of spectroscopy and optical imaging. Spectral curve can accurately reflect the diagnostic reflection and emission characteristics of different ground targets, and it is the physical basis of fine recognition. Targeted at new HRS observations such as Chinese space-borne, UAV-borne and deep space HRS, this direction aims at researching theories, methods and applications of HRS, building a full spectral range (joint VNIR-SWIR-TIR) HRS platform, integrating “classification, unmixing and target detection” HRS information processing system, and finally applying HRS technology to precise agriculture, land cover mapping, deep space exploration, etc.
High-spatial-resolution remote sensing image interpretation
High-resolution remote sensing is a kind of remote sensing science and technology with spatial resolution better than 5 m or even reaching sub-meter level. High-resolution remote sensing images can clearly express the boundary of land-cover classes and provide rich spatial information, which provides a data foundation for fine access to surface category information and human activities. Targeted at high-resolution remote sensing data such as ZY-3, GF-2, Worldview, aerial image, the remote sensing data processing lab works on the representation, processing and understanding problem of multi-source heterogeneous mass high-resolution remote sensing data, breakthrough the crucial technology of integration of representation, fusion processing, semantic understanding for high-resolution remote sensing data, and establish a high-resolution remote sensing data mining and application analytical system, realizing transformation from land cover identification to scene understanding for high-resolution remote sensing image, and finally applied to domestic satellite for global surface covering, time-long series change monitoring, etc.
SAR remote sensing data processing and application
SAR remote sensing includes all technologies that can process and analyze Earth observation data acquired by active microwave sensors to extract information for various applications. In recent years, LIESMARS has carried out numerous studies in the fields of high-accuracy SAR geometric processing, radiometric/polarimetric SAR calibration, polarimetric information extraction, Stereo Radargrammetry, SAR interferometry, polarimetric SAR interferometry, SAR tomography, etc. Comprehensive sets of theory and methodology for spaceborne SAR data processing and information extraction with unique characteristics have been developed to the support efficient use of satellite SAR data in Earth surface geometric information and target property information retrieval. This has been successfully applied in key projects such as topographic mapping in western China, urban land subsidence monitoring, large infrastructure health diagnosis, and geohazard monitoring in western mountainous areas, etc.
Atmospheric remote sensing
With respect to the technology of remote sensing of the atmosphere, Mie scattering lidar, Raman lidar and dual wavelength polarization lidar have been developed independently; it won the second prize of science and technology progress of Hubei province. Furthermore, the NASA traditional spaceborne lidar inversion algorithm has been improved for the satellite data application value.
In the aspect of atmospheric inversion algorithm theory, the development of radiometric calibration method has been highly praised by international peers, and effectively improved the work efficiency of the atmospheric remote sensing instruments under the environment of high concentration aerosol particles in China combined with other independently developed inversion methods.
Based on the above data and theoretical methods, the results of pollutant emission sources in Wuhan have been obtained, as well as the scope of pollutant dispersion and its influence and the mechanism on the radiation balance.
Environment remote sensing
Remote Sensing of the environment and its application is a multidisciplinary technology to detect Earth surface environment dynamics, and to implement application in monitoring of the environment and resources on the Earth. LIESMARS’ scientists studied complicated land-water surface environment monitoring and human activities analysis topics based on multi-source remote sensing big data.（1）Aiming at ecological and environmental issues, e.g. high turbidity and eutrophication for inland lakes, we proposed water environment monitoring methodology to couple remote sensing and hydraulic simulation with data assimilation, in order to analyze the human activities impacts on water environment. The proposed methodologies were successfully applied in Poyang and Erhai lake for ecological and environmental monitoring. The achievements aroused NASA, Vertical News, IOCCG concerns and were specially reported by CCTV-News.（2）In the issue of complicated human-earth relationship, night-time light remote sensing images were used to track urban economic development, revealing the impact of Syrian Civil War on urban environmental system. This research was cited by hundreds of organizations and media including United Nations, Associated Press, CCTV-News, The New York Times.
Intelligent unmanned aerial/ground vehicle
For the purpose of automatic mapping, we have built intelligent unmanned aerial/ground vehicles, which are able to do SLAM, obstacle avoidance, target searching and tracking, etc. The unmanned vehicles are already used for indoor mapping. We have ranked the 3rd place in the international challenges on UAV developing by DJI, Fort and UNDP.