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• W4321440602 abstract "Canopy height is a key physiognomic parameter of biodiversity, productivity and other ecosystem functions in high-elevation alpine ecosystems. However, little is known as to how altitude influences canopy height in these ecosystems. This study makes use of an open-access global forest canopy height map with a spatial resolution of 30 m that integrates Global Ecosystem Dynamics Investigation (GEDI)–Light Detection and Ranging (LiDAR) data (April–October 2019) and Landsat analysis-ready time-series data (year 2019). The variation in canopy height was quantified for each 100 m elevation band starting 500 metres below the alpine treeline ecotone at 3780 masl and extending up to 500 m above the alpine treeline ecotone. The global forest height map was compared to the in situ data (root-mean-square error [RMSE] = 6.6 m; mean absolute error [MAE] = 4.45 m). We observed a strong negative correlation (R2 = 0.96) between altitude and LiDAR-estimated canopy height. The altitude alone explained 96% of the variation in canopy height (p < 0.001). This chapter provides the first of its kind landscape-level quantification of the rate at which canopy height decreases with the increase in altitudinal gradient across the Indian Himalayan treeline." @default.
• W4321440602 created "2023-02-22" @default.
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• W4321440602 date "2023-01-01" @default.
• W4321440602 modified "2023-09-27" @default.
• W4321440602 title "Quantifying Variation in Canopy Height from LiDAR Data as a Function of Altitude Along Alpine Treeline Ecotone in Indian Himalaya" @default.
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• W4321440602 doi "https://doi.org/10.1007/978-981-19-4476-5_8" @default.
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