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090			_aB-16934
245	1	0	_aTowards rainfall interception capacity estimation using ALS LiDAR data
490	0		_vInternational GeoScience and Remote Sensing Symposium (IGARSS), v.7325869, p.735-738, 2015
520	3		_aIn this study we develop a spatial model for interception capacity of vegetation based on LiDAR data. The study is conducted in the natural wetland river valley dominated meadows, reeds and small bushes. The multiple regression model was chosen to relate the field measurements of interception capacity and LiDAR statistics at 2m grid. The optimal model was chosen by stepwise selection and further manual variables selection resulting in the r2 of 0.52 and the residual standard error of 0.27 mm. The model preserved the vegetation pattern spatially and showed reasonable estimates for both vegetation covered and not covered by field sampling. The model was, however, affected by LiDAR measurements corrupted by river inundation. The results show good perspective for using LiDAR data for interception capacity estimation.
650	1	4	_aINTERCEPTION
650	1	4	_aLIDAR
650	1	4	_aRAINFALL
650	1	4	_aREMOTE SENSING
650	1	4	_aRIPARIAN WETLANDS
650	1	4	_aVEGETATION
700	1	2	_aBerezowski, T.
700	1	2	_aChormanski, J.
700	1	2	_aKleniewska, M.
700	1	2	_aSzporak-Wasilewska, S.
856	4	0	_uhttps://drive.google.com/file/d/17yFjiciHtJNe3KT1CainS11NvHTJ7okS/view?usp=drivesdk _zPara ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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