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利用MODIS影像提取火烧迹地方法的研究

1. 1. 中国科学院地理科学与资源研究所,北京 100101
2. 中国科学院大学,北京 100049
• 收稿日期:2015-12-16 修回日期:2016-03-04 出版日期:2016-11-20 发布日期:2016-11-20
• 通讯作者: 冯险峰 E-mail:xiaox.13s@igsnrr.ac.cn;fengxf@lreis.ac.cn
• 作者简介:

作者简介：肖潇（1993-）,女,湖南衡阳人,硕士生,研究方向为生态遥感。E-mail: xiaox.13s@igsnrr.ac.cn

• 基金资助:
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）

Burned Area Detection in the Ecosystem Transition Zone Using MODIS Data

XIAO Xiao(), FENG Xianfeng*(), SUN Qingling

1. 1. Institute of Geographic Sciences and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
• Received:2015-12-16 Revised:2016-03-04 Online:2016-11-20 Published:2016-11-20
• Contact: FENG Xianfeng E-mail:xiaox.13s@igsnrr.ac.cn;fengxf@lreis.ac.cn

Abstract:

Fires belong to one of the main disturbance factors and play an important role in various ecosystems. Burned area detection not only indicates the impact of fires on ecosystems, but also provides a scientific support for the global carbon cycle studies. Traditional burned scar area detection approach mainly depends on ground survey and measurements, which still has several defects, such as the heavy workload, high cost, low efficiency, and poor timeliness etc. By applying remote sensing technology to map the burned area can produce burn scar information with greater spatial and temporal scale and effectively avoid the above-mentioned problems. Currently, many methods aiming to map the burned area on remote sensing images have been developed, and various global burned area products which provide the consistent assessments of fire activity at the global scale are also available; however, the efficiency of their performances differs within various ecosystems. In this study, we developed an algorithm to map the burned scar area in an ecosystem transition zone by using the Moderate Resolution Imaging Spectroradiometer (MODIS) data. This algorithm was developed based on the Normalized Burned Ratio differencing (dNBR) and the vegetation coverage data. The NBR index was originally developed specifically for mapping burned areas, and recently it has been used in the assessment of burning severity. Firstly, we used the near red and shortwave infrared bands of MODIS Surface Reflectance products (MOD09A1) to calculate the NBR values. Then, the differenced NBR (dNBR) calculated from the NBR values for a composite period with the previous 8-day range was calculated. The frequency distribution of dNBR maximum value in the burned scar area and the unburned region was analyzed. Since the change of NBR values in regions with different vegetation coverage was different, the tree cover and herbaceous cover data provided by the MODIS Vegetation Continuous Fields product (MOD44B) were also used for setting up rules to extract the burned scar area. A case study was carried out in an ecosystem transition zone within the southeast Siberia, where forest, grassland, farmland and other different ecosystems coexist. Comparison of the burned area detected by this algorithm with the adoption of high resolution burned scar information from Landsat ETM+ imagery shows a high accuracy. And the result obtained using this algorithm was better than the one using the MODIS Combined Burned Area product (MCD45A1), with the kappa coefficient increased from 0.70 to 0.75. To make a better comparison, we set up rules with the same threshold values of dNBR to extract the burned scar area, but without the usage of tree cover or herbaceous cover data. We found that the use of tree cover data as well as the herbaceous cover data can reduce mistakes during the process and improve the accuracy of burned area extraction, with the kappa coefficient increased from 0.69 and 0.73 respectively to 0.75.