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• W4288773399 abstract "Vegetation height estimation of desert ecosystems is important for understanding the groundwater cycle. ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) provides an opportunity to measure vegetation heights on a global scale. This letter proposed a method for retrieving low and sparse vegetation heights in desert ecosystems. Considering the significant difference in density between the vegetation photons and the ground photons, the ground photons were removed based on the terrain-adaptive method first. The localized density parameter was then introduced to distinguish the vegetation photons and the noise photons. Finally, the vegetation heights were obtained by the elevation percentile approach. The proposed method was tested using the ICESat-2 data acquired over a desert located in Arizona. The vegetation height results derived by the proposed method have an RMSE of 0.78 m which is significantly less than that of ATL08 with an RMSE of 4.26 m, which demonstrates it is feasible to extract low and sparse vegetation height in desert areas. The results showed that ICESat-2 photon cloud lidar data are suitable for low and sparse vegetation height investigations in desert ecosystems." @default.
• W4288773399 created "2022-07-30" @default.
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• W4288773399 date "2022-01-01" @default.
• W4288773399 modified "2023-10-16" @default.
• W4288773399 title "Retrieving Low and Sparse Vegetation Heights in Desert Ecosystems Using ICESat-2 ATL03 Photon-Counting LiDAR Data" @default.
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• W4288773399 doi "https://doi.org/10.1109/lgrs.2022.3194877" @default.
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