资源简介

摘要： 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DI 5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。 关键词： 森林扰动;  MODIS;  时间序列;  NDVI     Abstract: Forest disturbance play an important impact on terrestrial ecosystems.Remote sensing technique has become the most important way to detect the forest disturbance at regular intervals and in a sequential manner because of the capacity of obtaining large area synchronous forest observation data at regular intervals.Forest disturbance monitoring based on time series data is becoming the main method.Fujian Province is taken as a case study.Five kinds of forest disturbance indices of DI,IFZ,NBR,NDMI and NDVI,and the different disturbance types spectral response capacity are studied,and the classification accuracy is evaluated by using MODIS time series data set from 2001~2013.The results show that extraction capacity of DI for forest cutting,plant diseases and insect pests,and afforestation is strong,and NBR is most sensitive to forest fire,in addition,spectral response capacity of NDVI for four disturbance types is relatively weak.The separability index(SI) of DI and IFZ are higher than 1 for different disturbance,which indicate that these two indices can be used to monitor multiple disturbance types.The accuracy assessment shows that DI among the indices,has the highest extraction capability.Its total accuracy to monitor the different disturbance is the highest of 92.97% and its kappa coefficient reaches to 0.92,followed by IFZ,which has the total accuracy of 89.66% and kappa coefficient of 0.88.The monitoring accuracy of NBR and NDMI nearly are the same,and are higher than NDVI.

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