Large-range detection method for forest fire point based on spatial context features
A technology of spatial context and detection method, applied in the field of remote sensing, can solve the problems of fire point detection and adverse effects of fire extinguishing
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2021-04-23
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Abstract
Description
technical field
[0001] The invention belongs to the technical field of remote sensing, and relates to a forest fire point detection method based on the geosynchronous orbit satellite Himawari-8. Background technique
[0002] The global ecological environment is gradually deteriorating under the influence of climate warming, and large-scale natural disasters and extreme weather events occur frequently. Among them, forest fires, as a serious natural disaster, have occurred many times in recent years, posing a huge threat to economic development, global ecological balance, and personal life and property safety. Fighting forest fires is very dangerous. On March 30, 2019, a forest fire broke out in Muli County, Liangshan Prefecture, Sichuan Province. The total burned area of the fire site was about 20 hectares, and 31 people died. Since July 8, 2019, forest fires in Australia have been raging. The burned area has reached 12 million hectares. About 1 billion wild animals have l...
Examples
Embodiment Construction
[0064] The present invention will be further described below in conjunction with the accompanying drawings.
[0065] Data acquisition: The remote sensing data used in the present invention is the data of the Japan Himawari-8 geosynchronous orbit satellite, the imaging range covers the entire Asia-Pacific region, and the imaging time is 10 minutes per scene. After submitting the account password, the user can obtain data through the following website: ftp: / / ftp.ptree.jaxa.jp / / jma / netcdf.
[0066] Implementation tools:
[0067] All the test process of the present invention is realized based on PYTHON 3.7, and the flow code is original of the present invention.
[0068] The image used in the attached figure is the Himawari-8 image at 13:20 on April 1, 2020, Beijing time, which was intercepted to the research area. The overview of the research area is as follows figure 2 shown.
[0069] The implementation process is as follows figure 1 shown in detail below.
[0070] step 1:...