Ying Shen

Title: Innovations of Ying Shen in Noise Detection Technology

Introduction

Ying Shen is a prominent inventor based in Zhejiang, China. He has made significant contributions to the field of remote sensing through his innovative approaches to noise detection in time-series vegetation indices. His work is particularly relevant for applications related to land surface analysis.

Latest Patents

Ying Shen holds a patent for a "Noise detection method for time-series vegetation index derived from remote sensing images." This invention introduces a systematic approach to classify observation values of each pixel into stationary and non-stationary series using a unit root test. For non-stationary series, a mathematical model is employed to predict discrete time-series vegetation indices (TSVI). The deviations between actual observation values and predicted values are calculated, allowing for effective noise detection. This method enhances the reliability of land surface-related applications by providing an accurate noise mask.

Career Highlights

Ying Shen is affiliated with Zhejiang University, where he continues to advance research in remote sensing and environmental monitoring. His innovative methodologies have garnered attention in academic and professional circles, contributing to the understanding of vegetation indices and their applications.

Collaborations

Ying Shen has collaborated with notable colleagues such as Wei Wu and Jiancheng Luo. Their combined expertise has furthered research initiatives and fostered advancements in the field of remote sensing.

Conclusion

Ying Shen's contributions to noise detection technology in remote sensing are invaluable. His innovative patent not only improves the accuracy of vegetation index analysis but also enhances the reliability of various land surface applications.