利用MODIS影像提取火烧迹地方法的研究
发布时间:2018-11-21 21:00
【摘要】:火烧迹地监测不仅可以反映火灾对生态系统的影响情况及损失信息,还能为全球碳循环研究提供重要的数据支持。本文利用MODIS地表反射率产品(MOD09A1)的近红外和短波红外波段构建的归一化燃烧率指数(NBR),计算前后2期影像的NBR差值,并在光谱指数差分法的基础上,结合MODIS植被数据产品(MOD44B)提供的植被覆盖度信息,设置规则提取火烧迹地。本文选择西伯利亚地区东南部的林地、草地、农田等不同生态系统的交界地带作为实验区,利用本文算法提取该区域的火烧迹地。实验结果表明:(1)本文算法的火烧迹地提取效果较好,优于MODIS火烧迹地产品(MCD45A1),kappa系数由0.70提高到0.75;(2)利用林木覆盖度、草本覆盖度数据,可以减少误判,提高火烧迹地提取的精度,kappa系数分别由0.69、0.73都提高到0.75。
[Abstract]:Fire monitoring can not only reflect the impact of fire on ecosystem and loss information, but also provide important data support for global carbon cycle research. In this paper, the normalized combustion rate index (NBR),) of MODIS surface reflectivity product (MOD09A1) is used to calculate the NBR difference between the two periods of images in near infrared and short-wave infrared bands, and based on the spectral index difference method. Based on the vegetation coverage information provided by MODIS vegetation data product (MOD44B), rules are set to extract the burning area. In this paper, the forest land, grassland and farmland in the southeast of Siberia are selected as the experimental areas, and the burning areas in this area are extracted by using the algorithm in this paper. The experimental results show that: (1) the extraction effect of the algorithm is better than that of MODIS (MCD45A1), kappa coefficient is increased from 0.70 to 0.75; (2) using the data of forest cover and herbaceous coverage, the misjudgment can be reduced, and the precision of extracting from burning area can be improved. The kappa coefficient is increased from 0.69n0.73 to 0.75.
【作者单位】: 中国科学院地理科学与资源研究所;中国科学院大学;
【基金】:科技基础性工作专项(2013FY112800) 特色研究所培育建设服务项目“依托大数扬突发性公共安全事件预警与决策模拟平台”(TSYJS03)
【分类号】:P237
[Abstract]:Fire monitoring can not only reflect the impact of fire on ecosystem and loss information, but also provide important data support for global carbon cycle research. In this paper, the normalized combustion rate index (NBR),) of MODIS surface reflectivity product (MOD09A1) is used to calculate the NBR difference between the two periods of images in near infrared and short-wave infrared bands, and based on the spectral index difference method. Based on the vegetation coverage information provided by MODIS vegetation data product (MOD44B), rules are set to extract the burning area. In this paper, the forest land, grassland and farmland in the southeast of Siberia are selected as the experimental areas, and the burning areas in this area are extracted by using the algorithm in this paper. The experimental results show that: (1) the extraction effect of the algorithm is better than that of MODIS (MCD45A1), kappa coefficient is increased from 0.70 to 0.75; (2) using the data of forest cover and herbaceous coverage, the misjudgment can be reduced, and the precision of extracting from burning area can be improved. The kappa coefficient is increased from 0.69n0.73 to 0.75.
【作者单位】: 中国科学院地理科学与资源研究所;中国科学院大学;
【基金】:科技基础性工作专项(2013FY112800) 特色研究所培育建设服务项目“依托大数扬突发性公共安全事件预警与决策模拟平台”(TSYJS03)
【分类号】:P237
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