University of Science and Technology of China

Chengzhi Xing

Cheng Liu

Wei Tan

Zaiwei Wang

Wanchao Ma

Yue Yang

Haoran Liu

Qihou Hu

Qihua Li

Xiangguang Ji

Weiheng Wang

A night hyper-spectral remote sensing imaging system for multi-component atmospheric trace constituents includes a light source unit, a detection light path unit, an unmanned aerial vehicle tracking light path unit, and a control and processing unit, where the light source unit couples and outputs first light source light with different wavelength ranges capable of imaging at night; the detection light path unit collimates and outputs the first light source light, and receive remote sensing light fed back based on the first light source light; the unmanned aerial vehicle tracking light path unit tracks and positions an unmanned aerial vehicle based on an unmanned aerial vehicle tracking light path; and the control and processing unit collects an original spectrum of the first light source light and a remote sensing spectrum and perform imaging analysis and process on the multi-component atmospheric trace constituents, and adjust and control the tracking light path.

Night hyper-spectral remote sensing imaging system for multi-component atmospheric trace constituents

Disclosed in the present invention is a method for whole-time space-air-ground integrated hyperspectral stereoscopic remote sensing, tracing and prediction of greenhouse/pollution gas, comprising: performing remote sensing of multi-source heterogeneous data: utilizing a hyperspectral stereoscopic remote sensing device, a hyperspectral imaging device, a hyperspectral unmanned aerial vehicle remote sensing device, a hyperspectral greenhouse gas remote sensing device based on grating light splitting and a night hyperspectral stereoscopic remote sensing device to perform the remote sensing of the multi-source heterogeneous greenhouse/pollution gas data; performing tracing and early warning of greenhouse/pollution gas components: progressively realizing tracing of greenhouse/pollution gas components at different locations based on the multi-source heterogeneous greenhouse/pollution gas data, and performing emission early warning according to a traced result; and performing stereo fusion and prediction of the multi-source heterogeneous data: performing data feature fusion based on the multi-source heterogeneous greenhouse/pollution gas data, and performing prediction of the greenhouse/pollution gas components at a future moment based on a fusion result. The system can complement the deficiencies of existing greenhouse/pollution gas monitoring and tracing technologies.

Integrated hyperspectral stereoscopic remote sensing, tracing and prediction of greenhouse/pollution gas

Growing community of inventors

Hefei, China

Chengzhi Xing