遥感影像提取森林火灾可燃物蓄积量模型的建立

Extraction of Forest Fire Fuel Volume Based on Remote Sensing Image

森林火灾可燃物蓄积量的提取为森林火灾蔓延模型提供了定量的森林火灾可燃物信息。利用遥感影像对森林火灾可燃物的分类结果,采用多元回归法、参数优化的神经网络法和支持向量机法建立森林火灾可燃物蓄积量模型。研究了遥感影像的数据处理、建模方法对森林火灾可燃物蓄积量模型精度的影响。利用最优的森林火灾可燃物蓄积量模型,进行整个研究区域的森林火灾可燃物蓄积量反演。结果表明,数据处理后的遥感影像,采用支持向量机法建立的模型精度较高。

We established the forest fire fuel volume models based on the most accurate classification of images using multiple re-gression method, neural networks method of parameter optimization, and support vector machine method of parameter opti-mization.We studied the influence on the accuracy of forest fire fuel volume model of data processing and different model-ing method.By the optimal model of forest fuel volume for the entire study area, we inversed forest volumes and produced the thematic maps of forest volume.The model accuracy of forest fire fuel volume accuracy is higher based on image data processed by support vector machine modeling method.