基于植被信息遥感反演的东亚飞蝗监测研究

Research on the Monitoring Oriental Migratory Locust Based on Remote Sensing Retrieval of Vegetation Information

植被是东亚飞蝗发生和成灾的重要指示因子。运用遥感技术对植被生长进行监测,对东亚飞蝗的预测和防治具有重要意义。以河北省黄骅市为研究区,利用实地获取的植被冠层孔隙度数据反算的LAI数据以及Landsat-5 TM影像提取的各种VI数据,进行了LAI(LAI-2000改进型算法的反算结果)与TM影像上反演的VI之间的相关分析。结果表明,RDVI最适合反映研究区植被生长状况。分析RDVI与飞蝗发生面积的关系,发现两者呈负线性相关,即随着RDVI减小,飞蝗的发生面积呈线性增大。

Vegetation is one of the most important indicators for the occurrence and outbreak of oriental migratory locust. For the prediction and control of the locust it has significant meanings to monitor vegetation growing by remote sensing. In this study, Huanghua City in Hebei Province was taken as the study area. Firstly, from the 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 （GLAI） were analyzed and compared.These methods are the Bonhomme ＆ Chattier algorithm, the LAI - 2000 algorithm, the improved LAI - 2000 algorithm and the Campbell＇s ellipsoid distribution algorithm, respectively. The result shows that among them the LAI - 2000 algorithm is the best one in terms of the accuracy of LAI retrieval. Secondly,the correlation analyses were conducted between GLAI obtained by improved LAI - 2000 model in field and the VI values retrieved from Landsat - 5 TM image data. It is found that RDVI is the most optimum considering indicating vegetation growing condition among the different forms of VI. Thirdly, a negative correlation exists in the relation between RDVI and the area in which the locust outbreak appeared. In other words,with the decrease of RDVI,the locust outbreak area appears linearly increased.