TY  - JOUR
A1  - Rheinwahlt, Aljoscha
A1  - Goswami, Bedartha
A1  - Bookhagen, Bodo
T1  - A network-based flow accumulation algorithm for point clouds
BT  - Facet-Flow Networks (FFNs)
JF  - Journal of geophysical research : Earth surface
N2  - Flow accumulation algorithms estimate the steady state of flow on real or modeled topographic surfaces and are crucial for hydrological and geomorphological assessments, including delineation of river networks, drainage basins, and sediment transport processes. Existing flow accumulation algorithms are typically designed to compute flows on regular grids and are not directly applicable to arbitrarily sampled topographic data such as lidar point clouds. In this study we present a random sampling scheme that generates homogeneous point densities, in combination with a novel flow path tracing approach-the Facet-Flow Network (FFN)-that estimates flow accumulation in terms of specific catchment area (SCA) on triangulated surfaces. The random sampling minimizes biases due to spatial sampling and the FFN allows for direct flow estimation from point clouds. We validate our approach on a Gaussian hill surface and study the convergence of its SCA compared to the analytical solution. Here, our algorithm outperforms the multiple flow direction algorithm, which is optimized for divergent surfaces. We also compute the SCA of a 6-km(2)-steep, vegetated catchment on Santa Cruz Island, California, based on airborne lidar point-cloud data. Point-cloud-based SCA values estimated by our method compare well with those estimated by the D-infinity or multiple flow direction algorithm on gridded data. The advantage of computing SCA from point clouds becomes relevant especially for divergent topography and for small drainage areas: These are depicted with much more detail due to the higher sampling density of point clouds.
KW  - point clouds
KW  - drainage networks
KW  - lidar
KW  - tin
KW  - surface runoff
KW  - spatial sampling
Y1  - 2019
U6  - https://doi.org/10.1029/2018JF004827
SN  - 2169-9003
SN  - 2169-9011
VL  - 124
IS  - 7
SP  - 2013
EP  - 2033
PB  - American Geophysical Union
CY  - Washington
ER  -