林火目标遥感多光谱识别指数构建方法研究

针对现有高温目标识别方法中波段筛选、识别指数构建缺少数学定量评判指标的问题,以内蒙古大兴安岭地区一次森林火灾为例,选用Landsat 8 OLI遥感影像数据进行林火目标多光谱识别指数构建方法的研究。研究发现,基于方差分析原理的"可分性度量"指标可作为高温目标识别方法研究中波段筛选、识别指数构建的数学定量评判指标,改进以往识别方法的定性分析方式。在区分林火目标与其他地物过程中,上述数学定量评判指标均具有遥感目标识别与分类的物理意义;其分类适宜性对林火目标的识别与提取具有重要作用。经过验证分析,利用"可分性度量"评判指标筛选出的适宜火点识别指数,在实际分类中效果良好、精确度较高,与理论结果相吻合。

Method of Remote Sensing Multispectral Recognition Index Construction for Forest Fire

Aiming at the problem of lack of mathematical quantitative evaluation index in band selection and identification index of existing high temperature target recognition method, a forest fire in Daxing''anling area of Inner Mongolia is taken as an example. Landsat8 OLI remote sensing image data are used to study the multispectral identification index of forest fire target. It is found that the "Separable Measure" index based on the variance analysis principle can be used as a mathematical quantitative evaluation index for the selection of the band in the high temperature target recognition method and the qualitative analysis method of the previous identification method. In the process of distinguishing between forest fire targets and other objects, the mathematical quantitative evaluation indexes all have the physical meaning of remote sensing target recognition and classification, and its classification suitability plays an important role in the identification and extraction of forest fire targets. After verification and analysis, the appropriate fire point identification index selected by the "Separable Measure" index is effective and accurate in the actual classification, which is consistent with the theoretical results.