Remote sensing monitoring of cyanobacteria density in Taihu Lake based on PIE-engine

Tianshi Feng; Zhiguo Pang; Wei Jiang; Pengjie Zhang; Hao Li

doi:10.1117/12.2642588

28 July 2022 Remote sensing monitoring of cyanobacteria density in Taihu Lake based on PIE-engine

Tianshi Feng, Zhiguo Pang, Wei Jiang, Pengjie Zhang, Hao Li

Author Affiliations +

Proceedings Volume 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022); 1230310 (2022) https://doi.org/10.1117/12.2642588
Event: International Conference on Cloud Computing, Internet of Things, and Computer Applications, 2022, Luoyang, China

Abstract

The development of earth observation technology and the maturity of data storage technology have prompted the remote sensing industry to enter the "big data" era. PIE-Engine is one of the remote sensing cloud computing platforms of China, which can integrate the main processing work involving remote sensing images into the program, so as to realize the rapid and batch processing of massive remote sensing data. This paper studies the application of PIE-Engine in water ecological environment monitoring. It selects landsat8 data in part of the Taihu Lake region from 2013 to 2020, and filters the data, quantitatively inverts the model, and visualizes the results. The program runs on the platform to study the concentration of turbidity of cyanobacteria blooms in the Taihu Lake. The results indicate that PIE-Engine can screen suitable remote sensing images and rely on established models to perform fast band calculations. Finally, the experimental results are exported according to user requirements. It can be seen that PIE-Engine has broad application prospects in water ecological environment monitoring. In the future, more experiments and research are still needed to continuously improve the accuracy and universality of different water quality parameter inversion models, and expand the platform data source and algorithm, give full play to the advantages of the platform and promote its applications.

Citation Download Citation

Tianshi Feng, Zhiguo Pang, Wei Jiang, Pengjie Zhang, and Hao Li "Remote sensing monitoring of cyanobacteria density in Taihu Lake based on PIE-engine", Proc. SPIE 12303, International Conference on Cloud Computing, Internet of Things, and Computer Applications (CICA 2022), 1230310 (28 July 2022); https://doi.org/10.1117/12.2642588

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KEYWORDS

Remote sensing

Clouds

Earth observing sensors

Landsat

Data modeling

Satellites

Analytical research

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