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Research on Key Technologies of Earthquake Emergency Response Based on Multi-Sensor Data

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DOI: 10.23977/acss.2023.070601 | Downloads: 24 | Views: 409

Author(s)

Yan Yang 1, Wengang Yin 1, Siyu Dong 1

Affiliation(s)

1 Officers College of PAP, Chengdu, Sichuan, 610213, China

Corresponding Author

Yan Yang

ABSTRACT

Remote sensing has achieved good application in disaster monitoring, and also exposed some problems in earthquake remote sensing emergency monitoring. This paper mainly introduces the demand for remote sensing data under different geographical environments, existing remote sensing data sources and actual earthquake cases in earthquake emergency remote sensing monitoring and evaluation, especially the use of high-resolution radar remote sensing data to successfully identify a large number of landslides and barrier lakes caused by earthquake disasters, and determine their distribution and scale, Measure the area, length, etc. When remote sensing images before and after earthquakes are from different sources, a post-classification change detection method based on object-oriented combination is proposed to overcome the requirements of traditional change detection for data type and time consistency, and realize multi-sensor data assimilation and information collaborative processing. The rapid development of multi-remote sensing sensing technology provides a timely and effective technical means for earthquake disaster monitoring and disaster assessment. This paper focuses on the research of multi-mode remote sensing image seismic disaster information identification and disaster dynamic change monitoring methods before and after the earthquake, and explores the intelligent and automatic remote sensing earthquake emergency application of multi-mode remote sensing data collaboration.

KEYWORDS

Multiple remote sensing sensing data, Earthquake emergency response, Key technology

CITE THIS PAPER

Yan Yang, Wengang Yin, Siyu Dong, Research on Key Technologies of Earthquake Emergency Response Based on Multi-Sensor Data. Advances in Computer, Signals and Systems (2023) Vol. 7: 1-7. DOI: http://dx.doi.org/10.23977/acss.2023.070601.

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