摘要
大兴安岭是我国重点森林火灾区,准确预测该地区的森林可燃物含水率对于提高该地区林火发生预测的准确性意义重大。本研究采集典型林型的枯落物的光谱和含水率实测数据,通过一阶导数和去包络线的光谱分析方法识别森林枯落物含水率敏感波段。通过相关系数法从原始光谱、去包络线光谱、一阶导数光谱、去包络线之后的一阶导数光谱中筛选与枯落物含水率高度相关的波段作为含水率反演模型的备选自变量。利用逐步回归分析建立枯落物含水率反演模型,并对模型进行精度评价。结果表明,去包络线之后的一阶导数光谱对枯落物含水率变化存在显著响应,敏感波段位于398~668、768~1068、1098、1278、1388~1438、1458~1538、1868~1898、1988~2088、2198~2208、2228~2238 nm(P<0.05)。相关系数极值为-0.653、0.610,分别在波长2008、1888 nm处。通过多元逐步回归构建大兴安岭地区9种典型林型枯落物光谱和含水率的预测模型,模型决定系数R2=0.537,平均相对误差为0.303,均方根误差为0.499。本研究结果将为利用遥感技术快速测定森林枯落物含水率提供参考。
Daxing＇anling is a highly frequent forest fire disaster area in China.Accurate prediction of forest fuel moisture content is of great significance to improve the accuracy of forest fire forecast in this area.In this study,first derivative transformation and continuum removal methods were used to identify the bands sensitive to forest litter moisture.And the correlation coefficients were calculated between measured forest litter moisture and four spectral variables,including the original reflectance,the first derivative reflectance,the continuum-removal reflectance and first derivate of the continuum-removal reflectance.Then the highly relevant bands were selected as independent candidate variables and the forest litter moisture content estimation model was established by using a stepwise regression method.The determination coefficient（R^2）,mean relative error（MRE） and root mean square error（RMSE） of the model were calculated for evaluating the model.The results showed that there was a higher correlation between forest litter moisture content and first derivate of the continuum-removal reflectance compared to other spectral variables.The more sensitive bands were 398-668,768-1068,1098,1278,1388-1438,1458-1538,1868-1898,1988-2088,2198-2208,2228-2238 nm（P〈0.05）.The extreme values of the correction coefficients were-0.653 and 0.610 at 2008 and 1888 nm,respectively.The model used to estimate forest litter moisture content was established by using multi-linear stepwise regression method.The R2,MRE and RMSE of the model were 0.537,0.303 and 0.499,respectively.This study provides reference in fast estimating forest litter moisture content by using remote sensing technology.
出处
《生态学杂志》
CAS
CSCD
北大核心
2017年第11期3321-3328,共8页
Chinese Journal of Ecology
基金
林业公益性行业科研专项(201404402)资助
关键词
大兴安岭
森林枯落物
含水率
水分敏感波段
最优模型
Daxing＇ anling
forest litter
moisture
sensitive bands to moisture
optimal model
