摘要
基于PROSAIL模型,结合野外实测叶片等水分厚度、干物质重量、叶面积指数数据,构建一种基于归一化红外指数和归一化干物质指数的植被冠层可燃物含水率估算方法。首先,在PROSAIL模型输入实测参数模拟植被冠层光谱曲线,计算归一化红外指数、归一化干物质指数用于叶片等水分厚度、干物质重量的反演。结果表明:归一化红外指数与叶片等水分厚度、归一化干物质指数与干物质重量存在明显的线性关系,基于该关系建立叶片等水分厚度、干物质重量的经验估算模型,经验证估算结果精度较高;将该经验模型推广至利用Landsat 8数据拟合植被冠层可燃物含水率,并与实测数据进行验证,结果显示R^(2)达到0.743,RMSE达到34.2%,具有较高的精度。文章提出的植被冠层可燃物含水率估算模型,可实现广州市过渡带森林大面积、较高精度植被冠层可燃物含水率监测,为预防森林火灾提供参考。
Fuel moisture content(FMC),which is the ratio of equivalent water thickness(EWT)to dry matter content(DMC),plays a crucial role in the estimation of vegetation ignition probability and the fire propagation rate.The PROSAIL model can adequately simulate the canopy reflectance of vegetation,with the input of fieldmeasured data into the model ensuring conformity with the ecological rules.If the EWT and DMC can be estimated by an empirical statistical method according to the reflectance spectrum,the universality of the physical model and the efficiency of the empirical statistical method can be considered.In this study,a fast and versatile method is established for estimating FMC based on the EWT,DMC,leaf area index measured data,and the PROSAIL model.The Normalized Difference Infrared Index(NDII)and Normalized Dry Matter Index(NDMI)were obtained from the spectral curves,with the results showing an obvious linear relationship between the NDII and EWT,NDMI,and DMC.Therefore,EWT and DMC can be estimated using the NDII and NDMI.The accuracy of the estimation results is verified to be high.The estimation model can be extended to Landsat 8 data to estimate FMC.The estimated FMC data verified by the measured data showed that R^(2)was 0.743 and the RMSE was 34.2%.The model accuracy was reliable owing to large dynamic changes in the FMC.However,the estimated value of the FMC shifted significantly to the left during this study.The reasons for this are as follows:1)The field-measured points are not sufficient to support the analysis according to different vegetation types,and the physical and chemical properties of different types are varied,leading to altered simulated spectral curves;2)The vegetation spectrum is sensitive to the DMC at 1,650 nm,1,720 nm,and 2,270 nm bands,and the sensitivity near the 1,650 nm and 1,720 nm bands is greater than that at 2,270 nm.However,because the Landsat 8 image does not have a 1,720 nm band,the 2,270 nm band was selected to calculate the NDMI,making the value of the estimated DMC too large,resulting in a small value of the estimated FMC and a significant shift to the left;3)1,650 nm and 2,270 nm are not in the central wavelength of the two bands of Landsat 8;therefore,the estimated DMC and FMC are shifted.In addition,the fast and versatile method,which is established based on the EWT,DMC,leaf area index measured data and the PROSAIL model,can realize large-scale and high-precision monitoring of the FMC,providing a scientific reference for forest fire prevention.
作者
闻宏睿
国巧真
魏书精
曾宇怀
吴泽鹏
孙震辉
Wen Hongrui;Guo Qiaozhen;Wei Shujing;Zeng Yuhuai;Wu Zepeng;Sun Zhenhui(School of Geology and Geomatics,Tianjin Chengjian University,Tianjin 300384,China;Guangdong Provincial Key Laboratory of Silviculture,Protection and Utilization,Guangdong Academy of Forestry,Guangzhou 510520,China;Guangzhou Institute of Geography,Guangdong Academy of Sciences,Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System,Guangzhou 510070,China)
出处
《热带地理》
CSCD
北大核心
2023年第3期545-553,共9页
Tropical Geography
基金
广东省林业科技创新项目:森林火险预测预报关键技术研究与应用(2020KJCX003)。
