Using Sentinel-2A multi-spectral image as the data source,the spatial pattern of pest damage at the southern foot of Changbai Mountain was quantitatively obtained by coupling the insect mouth density using spa-tial distribution of injured tree species extracted using a convolutional neural network model and leaf foliation rate by the difference of the leaf area index reversed by the PROSAIL model at multiple time points.Results show that:the overall accuracy of 7 LAI inversion in 2018-2020 was above 88％;the optimal reference phase of red pine was in June 2019,R2 is 0.82 and other species in June 2018;linear function,R2 is 0.755;larch pest area of 6174 hm2,and spruce damage area ratio of 65.19％.The reference phase of the leaf loss rate is June of the year before the disaster;the relationship between the pest density and the leaf loss rate is linear;the spatial pattern of different tree species is different,and the proportion of evergreen trees is generally higher than that of deciduous tree species.
关键词
食叶害虫/叶面积指数/针叶树种/遥感/失叶率/虫口密度
Key words
leaf eating pest/LAI/conifer species/remote sensing/leaf loss rate/insect mouth density
维普
万方数据