Loreys height regression for ICESAT-GLAS waveforms in hyrcanian deciduous forests of IranReport as inadecuate

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1 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale 2 Faculty of Natural Resource 3 UPR BSEF - Biens et services des écosystèmes forestiers tropicaux 4 AgroParisTech 5 LISAH - Laboratoire d-étude des interactions entre sols, agrosystèmes et hydrosystèmes

Abstract : Since Lidar technology provides the most direct measurements of 3D of phenomena, it plays a critical role in a variety of applications. Forest canopy height as a main factor in forest biomass estimation is costly and time consuming to be measured on the ground. This study aims to estimate Lorey-s height -Hlorey- using GLAS data based on regression models. Different metrics like waveform extent -Wext-, trail-edge extent -Htrail- and lead-edge extent -Hlead- were extracted from waveforms and a terrain index -TI- was also calculated using a digital elevation model. Hlorey estimated using multiple regression models were compared to field measurements data. A 5-fold cross validation method was used to validate the results. Best model with lowest AIC 297.440 was resulted using combination of Wext and TI R a^2=0.72; RMSE= 5.04m. The results show capability of ICESat-GLAS to estimate Lorey-s height in sloped area with a simple regression model. It is prospected to reach better result using other statistical methods and also improvement of processing techniques for LiDAR waveforms in the case of sloped terrain


Author: M. Rajab Pourrahmati - N. Baghdadi - A. Asghar Darvishsefat - M. Namiranian - V. Gond - Jean-Stéphane Bailly -

Source: https://hal.archives-ouvertes.fr/


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