Using GIS Remote Sensing Image Data for Wetland Monitoring and Environmental Simulation

Through a comprehensive theoretical basis and actual test analysis of the application system design and functional efficiency of the cloud platform, this paper puts forward an artificial intelligence environmental data monitoring and wetland environmental simulation method based on GIS remote sensin...

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Bibliographic Details
Published in:Computational intelligence and neuroscience 2022-08, Vol.2022, p.1-11
Main Authors: Cheng, Qian, Dang, C.N.
Format: Article
Language:English
Subjects:
Aerial surveys
Analysis
Annotations
Artificial intelligence
Artificial satellites in remote sensing
Classification
Cloud computing
Drones
Economic development
Environmental impact
Estuaries
Geographic information systems
Image classification
Image enhancement
Information processing
Landscape ecology
Management methods
Matrix methods
Metadata
Middleware
Monitoring
Product information
Radiation
Remote sensing
Satellite imagery
Sensors
Simulation
Sustainable development
Systems design
Unmanned aerial vehicles
Wetlands
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Summary:Through a comprehensive theoretical basis and actual test analysis of the application system design and functional efficiency of the cloud platform, this paper puts forward an artificial intelligence environmental data monitoring and wetland environmental simulation method based on GIS remote sensing images. First, the basic storage and computing functions have been enhanced at the physical layer. Second, the middleware layer is more flexible in the use of management methods and strategies. There are many strategies and methods that can be used in combination. Finally, based on this, the application system design framework is more convenient and faster so that you can focus on business logic, and the strategic advantages of certain functions are very obvious. The method of object-oriented classification and visual interpretation using UAV image data and satellite remote sensing images from the typical recovery area and treatment area of wetland from 2016 to 2020 is given in detail together to extract wetland information and use GIS software for dynamic calculation. Using the wetland transmission matrix method, the distribution map of the characteristic types of the survey areas in the four periods and the conversion status of the characteristic types at each stage were obtained, and the effect of wetland treatment was quantitatively studied.
ISSN:1687-5265
1687-5273
DOI:10.1155/2022/7886358