A detection method for fire spread area in forest grassland fire

Abstract

The invention provides a method for detecting the spread area of ​​the fire field in forest and grassland fires, which is used to solve the problem in the prior art of detecting the spread area of ​​the fire field within a certain period of time. The detection method of the fire spread area, first from the T of the period to be detected 1 moment and t 2 The PMS and IRS files were obtained from the GF-4PMI images at each moment, and after radiometric calibration, physical quantity calculation, geometric fine correction, band reorganization, and geometric registration, T 1 and T 2 The 6-band image files at each moment, and then use the fire point and burn trace detection algorithms to identify the relevant pixels in the images acquired at two moments, and generate intermediate temporary files Temp1 and Temp2 to detect the fire spread area. The invention quantitatively and dynamically detects the regional area, average surface velocity and fire spreading direction of the fire field during the forest and grassland fire occurrence process, and provides reliable data for commanding fire emergency rescue work.

Description

technical field [0001] The invention belongs to the field of natural disaster detection, and in particular relates to a method for detecting the spread area of ​​a forest and grassland fire. Background technique [0002] In the natural state, such as forests and grasslands, due to the existence of fire in the environment and its own flammability, it is very easy to cause wild fires, and the losses caused by this are very huge every year. In the process of emergency fighting after a forest and grassland fire, it is necessary to pay close attention to the spread of the fire scene and effectively dispatch and command the fire fighting work. [0003] Forest and grassland fire spread is an important reference index for forest and grassland fire risk analysis and fire fighting decision-making. The existing forest and grassland fire spread models at home and abroad mainly include the physical mechanism model represented by the Rotherml model in the United States, and the FBP model ...

AI Technical Summary

Problems solved by technology

In the daily satellite remote sensing monitoring of forest and grassland fires at home and abroad, Terra / Aqua MODIS, NOAA / AVHRR, FY-3, etc. are mainly used with medium and low spatial resolution (thermal infrared sensors at the kilometer level) and high temporal resolution (day, night) Due to the limitations of the time, space and radiation resolution of these satellite images, people usually only use the single-time satellite images obtained to extract the fire pixels or fires in the forest and grassland at that moment. The pixels of the ruins, did not detect the spread area of ​​the fire scene within a certain period of time

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