摘要
林火场景对地球背景红外辐射特性影响的研究对于预警卫星的目标识别至关重要。首先,利用林火场景的动态性,根据中分辨率成像光谱仪(MODIS)遥感数据对火场参数进行等级分类,基于元胞自动机模型建立林火图像模型,并对其改进来适应卫星观测高度下大尺度空间的特点。其次,根据不同的火场等级,利用中光谱分辨率大气辐射传输模式(MODTRAN)进行辐射计算,分析不同等级的辐射特性。最后,建立林火场景下辐射特性数据库,实现林火场景下地球背景红外辐射图像的快速仿真,研究不同波段下林火规模和林火持续时间对区域辐照度的影响。结果表明:在2~3μm波段,小规模林火场景的辐照度最大值是无火场景的58.6倍,而在8~14μm波段,火点的辐照度比着火前增加40%左右;着火后,初期火势扩大导致火势规模扩大,辐照度上升,但随后保持稳定。
Objective Recognition of targets by early warning satellites is increasingly crucial in national defense and military applications.This is closely linked to the infrared radiation characteristics of the Earth’s background,which highlights the need to establish an accurate model for such radiation.Surface types and weather conditions significantly affect infrared radiation transmission.Therefore,it is necessary to incorporate actual environmental factors when simulating the Earth’s background infrared characteristics.This is particularly important in scenarios such as forest fires,which greatly alter these characteristics and pose additional challenges to simulation.While extensive research has been conducted by domestic and international scholars on simulating the infrared radiation characteristics of typical areas,there remains a gap in addressing forest fire scenes.Therefore,to more accurately and efficiently identify target infrared radiation characteristics,it is essential to conduct simulations specifically focused on the Earth’s background under forest fire conditions.Methods Based on observational characteristics of the Earth’s background within satellite field of view,a parameter law for forest fire scenes is determined using satellite remote sensing data.Surface parameters are established for varying fire intensities such as temperature and emissivity,along with atmospheric parameters like VIS,water vapor content,and CO_(2) concentration.An extreme scene parameter level model is developed.The cellular automata model used to simulate forest fire scenes is enhanced in three aspects:cell state,cell neighborhood,and cell rules,to effectively simulate largescale mixed pixels within the satellite’s field of view.By employing the extreme scene parameter level model,we calculate radiation brightness under different fire scenes using MODTRAN and store these values in a SQLite database.This approach establishes an infrared radiation simulation model specifically for forest fire scenes within the satellite’s field of view.Results and Discussions Through simulation images,it is evident that forest fires significantly increase the radiation brightness of the region,and the area affected by fire expands with its scale(Fig.8,Fig.9).In the 2‒3μm band,fires ntensify atmospheric backscattering and surface temperatures,leading to a notable rise in irradiance at the fire site.This complicates the identification of surface types in nonburning areas.The maximum irradiance in smallscale forest fire scenes is 58.6 times higher than that in nofire ones.Irradiance increases slightly in mediumscale forest fires.In largescale fires,however,additional ignition points do not significantly increase maximum irradiance,as mediumscale fires already cover the entire area.In the 8‒14μm band,radiation primarily originates from the surface,and fires release particles that enhance surface radiation absorption.Consequently,changes in maximum irradiance across the detection area are less pronounced compared to the shortwave segment.The maximum irradiance in the smallscale forest fire scene is 1.11×103 W/m2,which is only 1%higher than that in the nofire scene.In the large forest fire scene with the highest regional irradiance,the maximum irradiance is 1.16×103 W/m2,representing a mere 6%increase compared to the nofire scene.Regarding the duration of forest fires,in the initial stages,as the fire persists,fire points spread rapidly,expanding the fire area within the detection zone,thereby increasing overall irradiance[Fig.9(c)‒(d),Fig.10(a)‒(b)].As ignition time progresses further,the fire area within the detection zone does not significantly expand.This is because combustible materials in the original fire site are consumed,transitioning the fire from combustion to completion of combustion.The transition leads to gradual decreases in surface temperature and irradiance(Fig.10).Areas previously unaffected by fire may ignite due to diffusion,leading to increased surface temperatures and irradiance.Conclusions In the study of infrared radiation from forest fire scenes on Earth,satellite remote sensing data is utilized to establish parameter rules based on observed characteristics of the Earth’s background.These rules determine surface parameters such as surface temperature and emissivity,as well as atmospheric parameters like VIS,water vapor content,and CO_(2) concentration,tailored to different fire intensities.An extreme scenario parameter model is developed for these parameters.The cellular automata model used for simulating forest fire scenes in images is enhanced in three key aspects:cell state,cell neighborhood,and cell rules.These improvements enable the model to accurately simulate largescale mixed pixels within the satellite’s field of view.Using the parameter model for extreme scenarios,the radiant brightness under varying fire conditions is calculated using MODTRAN.This approach allows for the simulation of infrared radiation images of Earth’s background during forest fire scenes across arbitrary bands from 2 to 14μm,with a wavelength resolution of 0.1μm.The radiation data is stored in an SQLite database.Thus,an infrared radiation simulation model is established for forest fires within the field of view.This model considers numerical changes in surface temperature,surface emissivity,aerosols,and other parameters across various ignition stages.Not only do the simulation results enable comparative studies between areas affected by forest fires and those without within the satellite detection field of view,but also simulate infrared radiation scenes under different forest fire conditions by selecting varying fire scales and spread time.This simulation realizes the infrared radiation simulation of Earth’s background within the detection area during forest fire scenes,thus providing higher application value.
作者
郑浩
史波
邢世林
Zheng Hao;Shi Bo;Xing Shilin(College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China)
出处
《光学学报》
CSCD
北大核心
2024年第24期269-279,共11页
Acta Optica Sinica
关键词
红外成像
红外辐射
森林火灾
图像仿真
元胞自动机
infrared imaging
infrared radiation
forest fire
image simulation
cellular automaton
