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森林扰动是影响陆地生态系统的重要因素之一,遥感可定期地获得大面积森林覆盖数据,成为定期和连续森林扰动监测的重要手段,基于时间序列数据的森林监测成为主要方式。研究利用2001~2013年MODIS时间序列遥感影像,以福建省为例,利用NDVI、NBRI、NDMI、IFZ和DI5种森林扰动监测指数,结合植被变化追踪算法提取森林扰动区域,并从光谱响应特征和对不同扰动类型的响应能力等方面,分析了对我国南方森林扰动的监测能力。结果表明:DI对森林砍伐、森林病虫害和植树造林3种扰动类型的响应能力较强,NBR对森林火灾最为敏感,NDVI对4种扰动类型的响应能力相对较弱;5种指数中DI对森林扰动的响应能力较强,森林扰动提取精度最高,IFZ次之,NDMI和NBR监测精度相当,且优于NDVI。
Forest disturbance is one of the important factors affecting terrestrial ecosystems. Remote sensing can obtain large-area forest cover data regularly and become an important means of periodic and continuous forest disturbance monitoring. Forest monitoring based on time-series data is the main method. Using the MODIS time series remote sensing images from 2001 to 2013, taking Fujian Province as an example, the forest disturbance index (NDVI, NBRI, NDMI, IFZ and DI5) was used to extract the forest disturbance area. The spectral response characteristics and The ability to respond to different types of disturbances and so on, analyzes the monitoring capacity of forest disturbance in southern China. The results showed that DI responded well to the three types of disturbances such as deforestation, forest pests and afforestation, NBR was the most sensitive to forest fires, and NDVI had relatively weaker responses to the four disturbance types. Among the five indices, The disturbance response ability is stronger, forest disturbance extraction accuracy is the highest, IFZ is the second, NDMI and NBR monitoring accuracy is equal, and better than NDVI.