2021-06-13T05:43:16Z
http://digital.csic.es/dspace-oai/request
oai:digital.csic.es:10261/212560
2021-01-29T11:44:14Z
com_10261_52
com_10261_7
col_10261_305
http://hdl.handle.net/10261/212560
http://dx.doi.org/10.3390/rs12101596
393285
Estimation of Canopy Gap Fraction from Terrestrial Laser Scanner Using an Angular Grid to Take Advantage of the Full Data Spatial Resolution
Multidisciplinary Digital Publishing Institute
2020
Gajardo, John
Riaño, David
rp10726
García, Mariano
Salas Rey, Javier
Martín, M. Pilar
rp03641
Riaño, David [0000-0002-0198-1424]
Martín, M. Pilar [0000-0002-5563-8461]
Terrestrial laser scanner
Gap fraction
Leaf area index
Angular grid
Hemispherical images
2020-05-17
© 2020 by the authors.
This paper develops an algorithm to estimate vegetation canopy gap fraction (GF), taking advantage of the full Terrestrial Laser Scanner (TLS) resolution. After calculating the TLS angular resolution, the algorithm identifies the missing laser hits (gaps) within an angular grid in the azimuthal and zenithal directions. The algorithm was first tested on angular data simulations with random (R), cluster (C) and random and cluster together (RC) gap pattern distributions. Noise introduced in the simulations as a percentage of the resolution accounted for the effect of TLS angular uncertainty. The algorithm performs accurately if angular noise is <6% of the angular resolution. To assess the impact of the change in projection, this study compared these GF estimates from angular grid simulations to their transformation into simulated hemispherical images (SHI). SHI with C patterns perform accurately, but R and RC patterns underestimate GF, especially for GF values below 0.6. The SHI performance to estimate GF was always far below the algorithm developed here with the angular grid simulations. When applied to actual TLS data acquired over individual Quercus ilex L. trees, the algorithm rendered a GF between 0.26 and 0.40. TLS had an angular noise <6%. Converting the angular grid into simulated HI (TLS-SHI) provided a better agreement with actual HI acquired in the same location as the TLS data, since they are in the same projection. The TLS-SHI underestimated GF by an average of 4% compared to HI. HI and TLS-SHI presented 14% and 17% lower values than the GF calculated from the angular grids, respectively. Nevertheless, the results from the simulations indicate that the algorithm based on the angular grid should be closer to the actual GF of the tree canopy.
European Commission
Ministerio de Economía y Competitividad (España)
Comisión Nacional de Investigación Científica y Tecnológica (Chile)
Remote Sensing
2020
12
1596