Changlu Cui

Title: The Innovative Contributions of Changlu Cui in Remote Sensing Data Storage

Introduction

Changlu Cui, an inventive mind hailing from Wuhan, China, has made significant strides in the field of remote sensing data management. With one patent to his name, he stands out as a notable figure within his field, particularly for his innovative methods of manipulating and storing large datasets.

Latest Patents

Changlu Cui holds a patent for a method titled "Method of storing remote sensing big data in Hbase database." This innovative technique encompasses several intricate steps, including obtaining a remote sensing image, pre-cropping it based on the Google S2 algorithm, and selecting grid levels based on image resolution. The process further involves demarcating the image's coverage scope, calculating the grids covered, and cropping the image into multiple blocks. Each block is serialized and organized into an Hbase table, utilizing a specified RowKey calculated from various attributes. This method effectively integrates multi-source remote sensing image data, significantly enhancing the efficiency of data storage in Hbase databases.

Career Highlights

Changlu Cui is affiliated with Wuhan University, where he has contributed to the academic community through research and innovation. His focus on advancing data storage methods for remote sensing demonstrates his dedication to improving technological applications in this crucial area.

Collaborations

Collaborating with other experts, including his coworkers Lingkui Meng and Wen Zhang, Changlu Cui has fostered an environment of innovation and teamwork. Together, they are at the forefront of exploring cutting-edge methodologies that enhance the efficiency of data handling in remote sensing.

Conclusion

Through his patent and contributions at Wuhan University, Changlu Cui exemplifies the impact that innovation can have on the field of remote sensing data storage. His work not only advances academic pursuits but also provides practical solutions for managing big data effectively.