To verify the detection capability of X-band dual-polarization phased-array radar for forest fires,this paper utilizes X-band dual-polarization phased-array radar data,Himawari-8 satellite data,combined with ground me...To verify the detection capability of X-band dual-polarization phased-array radar for forest fires,this paper utilizes X-band dual-polarization phased-array radar data,Himawari-8 satellite data,combined with ground meteorological automatic station data.A case study of a forest fire in Ao Feng Mountain on February 19,2021,was conducted to comparatively analyze the monitoring results from these two remote sensing methods.The results show that both methods exhibit significant features associated with the forest fire process observed and are effective modern methods of forest fire monitoring.The Himawari-8 satellite identified the fire point at 07:10(LST;LST=UTC+8)with subsequent observations every 10 minutes until 10:00,nearly two hours before the fire was fully extinguished.Compared with the satellite,the Xband dual polarization phased array radar detectedthe fire 14 minutes earlier,with an improved temporal resolution of one minute,and was not affected by cloud cover.In the triggering stage,vigorous stage,sustained burning stage,and extinguishing stage of the forest fire,radar characteristic factors including reflectivity(Z),differential reflectivity(ZDR),and correlation coefficient(CC)showed strong correlations with the fire progression.The radar monitoring results were continuous,complete,and precise.In summary,the X-band dual-polarization phased-array radar offers more detailed detection information,shorter detection time interval,and higher detection spatial accuracy.It presents a promising new method for forest fire detection,providing crucial guidance for on-site rescue operations,particularly for small-scale fire events.展开更多
Forest fires are frequent natural disasters.It is necessary to explore advanced means to monitor,recognize and locate forest fires so as to establish a scientific system for the early detection,real-time positioning a...Forest fires are frequent natural disasters.It is necessary to explore advanced means to monitor,recognize and locate forest fires so as to establish a scientific system for the early detection,real-time positioning and quick fighting of forest fires.This paper mainly expounds methods and algorithms for improving accuracy and removing uncertainty in image-based forest fire recognition and spatial positioning.Firstly,we discuss a method of forest fire recognition in visible-light imagery.There are four aspects to improve accuracy and remove uncertainty in fire recognition:(1)eliminating factors of interference such as road and sky with high brightness,red leaves,other colored objects and objects that are lit up at night,(2)excluding imaging for specific periods and azimuth angles for which interference phenomena repeatedly occur,(3)improving the thresholding method for determining the flame border in image processing by adjusting the threshold to the season,weather and region,and(4)integrating the visible-light image method with infrared image technology.Secondly,we examine infrared-image-based methods and approaches of improving the accuracy of forest fire recognition by combining the spectrum threshold with an object feature value such as the normalized difference vegetation index and excluding factors of disturbance such as interference signals,extreme weather and high-temperature animals.Thirdly,a method of visible analysis to enhance the accuracy of forest fire positioning is examined and realized;the method includes decreasing the visual angle,selecting central points,selecting the largest spots,and judging the selection of fire spots according to the central distance.Case studies are examined and the results are found to be satisfactory.展开更多
基金National Key R&D Program of China(2022YFC3004101)Guangdong Basic and Applied Basic Research Foundation(2023A1515011971)+3 种基金Science and Tech-nology Projects in Guangzhou(2023B04J0232)Science and Technology Development Fund Project of Guangdong Meteor-ological Bureau(GRMC2022Q23,GRMC2022Q01)Jiangmen Basic and Applied Basic Research Key Programs(202312)Science and Technology Development Fund Project of Jiangmen Meteorological Bureau(202008,202004,201907,202007,201704)。
文摘To verify the detection capability of X-band dual-polarization phased-array radar for forest fires,this paper utilizes X-band dual-polarization phased-array radar data,Himawari-8 satellite data,combined with ground meteorological automatic station data.A case study of a forest fire in Ao Feng Mountain on February 19,2021,was conducted to comparatively analyze the monitoring results from these two remote sensing methods.The results show that both methods exhibit significant features associated with the forest fire process observed and are effective modern methods of forest fire monitoring.The Himawari-8 satellite identified the fire point at 07:10(LST;LST=UTC+8)with subsequent observations every 10 minutes until 10:00,nearly two hours before the fire was fully extinguished.Compared with the satellite,the Xband dual polarization phased array radar detectedthe fire 14 minutes earlier,with an improved temporal resolution of one minute,and was not affected by cloud cover.In the triggering stage,vigorous stage,sustained burning stage,and extinguishing stage of the forest fire,radar characteristic factors including reflectivity(Z),differential reflectivity(ZDR),and correlation coefficient(CC)showed strong correlations with the fire progression.The radar monitoring results were continuous,complete,and precise.In summary,the X-band dual-polarization phased-array radar offers more detailed detection information,shorter detection time interval,and higher detection spatial accuracy.It presents a promising new method for forest fire detection,providing crucial guidance for on-site rescue operations,particularly for small-scale fire events.
基金supported by the National High-Tech Research and Development Program of China("863"project)(Grant No.2006AA06Z418)
文摘Forest fires are frequent natural disasters.It is necessary to explore advanced means to monitor,recognize and locate forest fires so as to establish a scientific system for the early detection,real-time positioning and quick fighting of forest fires.This paper mainly expounds methods and algorithms for improving accuracy and removing uncertainty in image-based forest fire recognition and spatial positioning.Firstly,we discuss a method of forest fire recognition in visible-light imagery.There are four aspects to improve accuracy and remove uncertainty in fire recognition:(1)eliminating factors of interference such as road and sky with high brightness,red leaves,other colored objects and objects that are lit up at night,(2)excluding imaging for specific periods and azimuth angles for which interference phenomena repeatedly occur,(3)improving the thresholding method for determining the flame border in image processing by adjusting the threshold to the season,weather and region,and(4)integrating the visible-light image method with infrared image technology.Secondly,we examine infrared-image-based methods and approaches of improving the accuracy of forest fire recognition by combining the spectrum threshold with an object feature value such as the normalized difference vegetation index and excluding factors of disturbance such as interference signals,extreme weather and high-temperature animals.Thirdly,a method of visible analysis to enhance the accuracy of forest fire positioning is examined and realized;the method includes decreasing the visual angle,selecting central points,selecting the largest spots,and judging the selection of fire spots according to the central distance.Case studies are examined and the results are found to be satisfactory.
