at the joint invitation of professor wu xiaodan and researcher ma xuanlong from the college of earth and environmental science of lanzhou university, professor yin gaofei from southwest jiaotong university gave an academic presentation to our students and conduct an academic exchange after the meeting.
lecturer: prof. yin gaofei (southwest jiaotong university)
title: topographic effects in optical remote sensing observations: simulation and correction
time: wednesday, 30 march 2022, 19:30-21:00
tencent conference: 584 575 346
lecturer profile：
yin gaofei, a professor in the college of earth science and environmental engineering, southwest jiaotong university. he is mainly engaged in research on quantitative remote sensing of vegetation ecology and has published more than 70 academic papers. he is selected as the young talent in the ten thousand people plan of the ministry of organization, marie curie scholar of the european union, young scientist of the ministry of natural resources, and jieqingof sichuan province. he is an associate editor of ieee geoscience and remote sensing letters and an editorial board member of remote sensing.
report description:
topographic effects are one of the main sources of uncertainty in quantitative remote sensing of the mountain vegetation, which constrains the practical level of quantitative remote sensing in mountainous areas. the report introduced the key physical mechanisms that cause topographic effects, described a simulation method for mountain vegetation reflectance in terms of an adapted radiative transfer model parameterization scheme, and finally presented a physical method for topographic correction developed through mechanistic model simplification. the report introduced a method for modeling and correcting the reflectance of the mountain vegetation, which effectively balances the completeness of the physical mechanism with the simplicity of the mathematical form, and provided an effective theoretical tool and practical technical method for the development of quantitative remote sensing products of mountain vegetation and remote sensing monitoring of the ecological environment.
