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• W4312082747 endingPage "100897" @default.
• W4312082747 startingPage "100897" @default.
• W4312082747 abstract "The Caatinga is a typical biome of the Brazilian semiarid region, and there is a lack of studies to estimate its plant biomass using SAR images. Also, there are no studies at this topic that use information from polarimetric decomposition. Therefore, this study aimed to estimate aboveground biomass (AGB) of the arboreal Caatinga under different phenological conditions using entropy and alpha angle data obtained by different polarimetric filters by Dual Polarimetric Decomposition in Sentinel-1 SAR images. The forest inventory was carried out in 19 sample plots with an area of 30 × 30 m in the Caatinga of Sergipe state, Brazil, using an allometric equation to estimate the AGB. Sentinel-1 images were obtained in 3 phenological conditions of the Caatinga (Greenness, Intermediate and Dryness) to which polarimetric filters (BoxCar - BC, IDAN, Improved Lee Sigma - ILS and Refined Lee - RL) were applied and obtained the entropy (H) and alpha angle (α) attributes after Dual Polarimetric Decomposition. The attributes of each polarimetric filter were related to the AGB using linear regressions. The combination of attributes provided higher accuracy than individual estimates: data from Intermediate period provided higher accuracy for AGB estimates, using H of the IDAN filtering and α using ILS (R2: 32.05%). The attributes generated through Dual Polarimetric Decomposition in Sentinel-1 images showed a low relationship with the AGB of the Caatinga in the study area. Nevertheless, the study made it possible to indicate which polarimetric filters depending on the different leaf cover conditions in the Caatinga offer greater precision in relation to the measured AGB, serving as the basis for future studies." @default.
• W4312082747 created "2023-01-04" @default.
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• W4312082747 date "2023-01-01" @default.
• W4312082747 modified "2023-09-23" @default.
• W4312082747 title "Dual polarimetric decomposition in Sentinel-1 images to estimate aboveground biomass of arboreal caatinga" @default.
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• W4312082747 doi "https://doi.org/10.1016/j.rsase.2022.100897" @default.
• W4312082747 hasPublicationYear "2023" @default.
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