森林火灾在景观上往往造成不同程度的森林冠层损失,而冠层影响光合作用和蒸散,因此刻画灾后森林冠层恢复的轨迹对于了解生态系统过程具有重要意义。森林冠层的损失和恢复通常采用叶面积指数(LAI)或其它能够反映冠层光合能力的植被指数进行表征。本研究中,我们采用Terra卫星搭载的中分辨率成像光谱仪(MODIS)的长时间序列影像(2000-2009年)来重建火灾后森林冠层恢复的过程。以美国南达科他州布莱克山国家森林公园(The Black Hills National Forest, South Dakota)为例,该地区在2000年8月24日经历了一次大的自然火灾,烧毁了近33 785 ha森林,其中大部分是美国黄松林。基于LAI的研究表明,植被冠层光合能力在3年内(2001-2003年)基本恢复,这主要来自于林下未烧毁草地在灾后的快速生长;火烧迹地的NDVI和EVI在这3年内也呈现恢复的态势。可见,LAI、NDVI和EVI在火灾几年之后便难以有效地识别火烧迹地。然而,陆地表面水分指数(基于近红外和短波红外波段的遥感标准化指数,简称LSWI),能够有效地识别和追踪火烧迹地至今的整个过程(2000-2009年)。这一研究结果也使得采用其它具有近红外和短波红外波段的传感器研究森林火灾迹地恢复和干扰过程成为可能,其中包括Landsat 5 TM影像(可追溯至1984年)。更长时间序列的数据对于研究森林火灾灾后生态系统干扰和恢复过程、森林演替模拟以及碳循环具有重要的支撑作用,LSWI指标证明能够有效地刻画这一过程。 Forest fires often cause different levels of forest canopy losses in the landscape, while canopy affects photosynthesis and evapotranspiration. Therefore, portraying the recovery of post-disaster forest canopies is of great significance for understanding ecosystem processes. Forest canopy loss and restoration are usually characterized by leaf area index (LAI) or other vegetation indices that reflect canopy photosynthesis. In this study, we used a long-time series of images (2000-2009) of the Terra satellite-based medium-resolution imaging spectrometer (MODIS) to reconstruct the forest canopy recovery process after a fire. In the case of The Black Hills National Forest, South Dakota, South Dakota, the area experienced a large natural fire on August 24, 2000, burning nearly 33,785 ha of forests, most of which Is the United States Huang Songlin. LAI-based studies show that the photosynthetic capacity of the vegetation canopy has basically recovered within 3 years (2001-2003), mainly due to the rapid growth of unburned grassland after the disaster in the forest; NDVI and EVI of the burned areas also appeared within these 3 years Recovery situation. Visible, LAI, NDVI and EVI in a few years after the fire will be difficult to effectively identify the fire place. However, the Surface Moisture Index (based on the Remote Sensing Standardization Indices for the Near Infrared and Shortwave Infrared bands, LSWI for short) can effectively identify and track the entire process to date (2000-2009). The results of this study also make it possible to study the recovery and disturbance processes of forest fires using other sensors with near infrared and shortwave infrared bands, including Landsat 5 TM images dating back to 1984. Longer time series of data for the study of forest fires after the disaster ecosystem disturbance and recovery process, forest succession simulation and carbon cycle has an important supporting role, LSWI indicators can effectively describe the process.