叶面积指数(Leaf Area Index,LAI)是描述植被冠层结构的重要参数,它对分析橡胶光合潜力、预测产量和评估灾害都具有重要意义。本研究利用LAI-2000获得了海南儋州两院地区30个橡胶林连续2年半的LAI月动态。结果表明:(1)橡胶林LAI最小值出现在1~2月的落叶季,最小值为(0.54±0.14)m^2/m^2;随后的第一篷叶抽叶期(3~4月),LAI快速增长,4月底平均值增至3以上[最大观测值为(4.48±0.82)m^2/m^2],平均占全年最大LAI的77.75%;之后增长趋于缓慢,至9月底达到年度最大值,最大观测值为(5.27±0.79)m^2/m^2。(2)LAI年际差异较大,平均LAI相差可达1以上,影响因素主要有年际物候差和台风灾害等;(3)不同年龄的橡胶林之间LAI存在差异,在第一篷叶期间,平均LAI为老龄橡胶林(>20龄)>幼龄及初开割林(≤10龄)>中龄橡胶林(11~20龄),而在之后至落叶前期,平均LAI次序为幼龄及初开割林>老龄橡胶林>中龄橡胶林。
森林具有气候调节、水源涵养、生物多样性保护等诸多生态服务功能（Millennium Ecosystem Assessment,2005;van der Werf et al.,2009）,同时减少毁林和森林退化也是减缓温室气体排放协议REDD＋的重要内容（DeF ries et al.,2007;Grassi et al.,2008）。为了改善日益恶化的生态状况,提高森林资源的蓄积量,自20世纪70年代以来,中国实施了六大林业重点工程,包括天然林保护工程、“三北”和长江中下游地区等重点防护林体系建设工程、退耕还林还草工程、京津风沙源治理工程、野生动植物保护及自然保护区建设工程以及重点地区速生丰产用材林为主的林业产业建设工程。在森林砍伐和林业工程的双向驱动下，如何准确地监测中国森林覆盖度及其时空变化成为一大挑战。
Forest fires often result in varying degrees of canopy loss in forested landscapes. The subsequent trajectory of vegetation canopy recovery is important for ecosystem processes because the canopy controls photosynthesis and evapotranspiration. The loss and recovery of a canopy is often measured by leaf area index （LAD and other vegetation indices that are related to canopy photosynthetic capacity. In this study we used time series imagery from the Moderate Resolution Imaging Spectroradiometer （MODIS） sensor onboard the Terra satellite over the period of 2000-2009 to track the recovery of the vegetation canopy after fire. The Black Hills National Forest, South Dakota, USA experienced an extensive wildfire starting on August 24, 2000 that burned a total area of 33 785 ha, most of which was ponderosa pine forest. The MODIS data show that canopy photosynthetic capacity, as measured by IL,AI, recovered within 3 years （2001-2003）. This recovery was attributed to rapid emergence of understory grass species after the fire event. Satellite-based Normalized Difference Vegetation Index （NDVI） and Enhanced Vegetation Index （EVI） at the burned sites also recovered within 3 years （2001-2003）. Rapid recovery of LAI, NDVI, and EVI at the burned sites makes it difficult to use these variables for identifying and mapping burned sites several years after the fire event. However, the Land Surface Water Index （LSWI）, calculated as a normalized ratio between near infrared and shortwave infrared bands （band 2 and band 6 （1628 1652 nm） in MODIS sensor）, was able to identify and track the burned sites over the entire period of 2000 2009. This fmding opens a window of opportunity to identify and map disturbances using imagery from those sensors with both NIR and SWIR bands, including Landsat 5 TM （dating back to 1984）; furthermore, a longer record of disturbance and recovery helps to improve our understanding of disturbance regimes, simulations of forest succession, and the carbon cycle.
