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- W2364804170 abstract "The ability of HJ-CCD remote sensing data to retrieve vegetation leaf area index(LAI) and its sensitivity to atmospheric correction methods were investigated in the Kanas National Nature Reserve,Xinjiang.The 6Sand FLAASH models were employed to implement atmospheric corrections for the remote sensing data.The changes in the reflectance and vegetation indices(NDVI,SR,SAVI,MSR,ARVI)of different land cover types(needle leaved forests,broad leaved forests,mixed forests,and grasslands)with and without atmospheric correction were analyzed.Then,the best fitted models for estimating LAI were built with the field measurements of LAI and spatial distribution patterns of LAI were analyzed.The results show that after atmospheric correction,the reflectance in the visible bands decrease.Reflectance in the near infrared band increases with the atmospheric correction by the 6S model and decreases with the atmospheric correction implemented by the FLAASH model.Consequently,atmospheric correction causes NDVI,SR,MSR and SAVI(except needle leaved forests)to increase.As to ARVI,the influence of atmospheric correction is related to the correction model used and vegetation types.With the atmospheric correction by the 6S model,ARVI decreases for all land cover types.The atmospheric correction conducted by the FLAASH model causes ARVI to increase for need leaved and broad leaved forests and to decrease for mixed forests and grasslands.Atmospheric correction enhances the linkage between LAI and vegetation indices.The models based on reflectance with the atmospheric correction by the 6S model are better than the models base on reflectance with atmospheric correction by the FLAASH model for forests(needle leaved forests,broad leaved forests,and mixed forests).As to retrieval of LAI for grasslands,the model based on reflectance with the atmospheric correction by the FLAASH model outperforms the model based on reflectance with the atmospheric correction by the 6S.The results indicate that the HJ-CCD data can be used to estimate LAI in the study area with atmospheric correction properly implemented.In the locations near lakes and rivers,LAI of vegetation is high.Low LAI is distributed at locations with high elevation.The LAI averages of mountain foreststeppe zone,subalpine forest zone,alpine shrub meadow,alpine tundra and alpine glaciers are 2.6,3.9,2.5,1.7and 1.0,respectively." @default.
- W2364804170 created "2016-06-24" @default.
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- W2364804170 date "2013-01-01" @default.
- W2364804170 modified "2023-09-25" @default.
- W2364804170 title "Retrieval of Vegetation Leaf Area Index in Kanas National Nature Reserve, Xinjiang,Based on HJ-CCD Remote Sensing Data" @default.
- W2364804170 hasPublicationYear "2013" @default.
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