东亚飞蝗自20世纪80年代以来在我国再度猖獗危害。本文选择国家一类蝗区河北省黄骅市为实验区.用植被冠层孔隙度反演了该地区不同植被的LAI。从光学模型建立机理及数量分析的角度.分析和对比了四种由槽被冠层孔隙度反演LAI的算法。结果表明.在四种估算方法中LAI-2000算法最适用于研究区植被LAI的估算。为了验证分析结果.用实测的植被盖度与四种算法反演的LAI进行了拟合.发现LAI与植被盖度之间呈明显的正相关关系。且LAI-2000算法最能反映研究区的植被特征。在此基础上,建立了LAI与飞蝗发生面积的关系模型.发现两者之间呈负线性相关,即随着LAI的减小,飞蝗的发生面积呈线性增大。研究结果为实时、快速、大面积监测蝗虫种群动态奠定了基础.并为合理、经济地防治蝗灾提供了科学依据。
Outbreaks of the Oriental migratory locust, Locusta migratoria manilensis (Meyen)have once again become a serious problem in the last two decades of the 20th century in China. One of the coastal breeding areas of the locust, Huanghua city in Hebei province was chosen as a study area in this paper. LAI of different kinds of vegetations in the study area have been derived from the gap fraction of vegetation canopy. From the point of view of the mechanism of developing the optical models and quantitative analysis, four algorithms used for LAI retrieval based on the gap fraction of vegetation canopy were analyzed and compared. The result shows that the LAI-2000 algorithm is the best one in terms of the accuracy of LA| retrieval among them. For verifying the conclusion, a fitting between canopy closure and the LAI retrieved from four algorithms were made. It is found that a positive correlation exists between the retrieved LAI and the canopy closure for all the three kinds of vegetations. In addition, a negative correlation exists between the LAI and the area where the locust outbreaks appeared. In other words, with the decrease of the LAI, the locust outbreak affected area appeared a linear increase. These findings laid the scientific foundation for quick monitoring the dynamics of locust populations in real time and at large scale and efficient control of locust plague.