Network-based flow accumulation for point clouds: Facet-Flow Networks (FFN)

Aljoscha Rheinwalt; Bodo Bookhagen

doi:10.1117/12.2318424

10 October 2018 Network-based flow accumulation for point clouds: Facet-Flow Networks (FFN)

Aljoscha Rheinwalt, Bodo Bookhagen

Proceedings Volume 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX; 107831C (2018) https://doi.org/10.1117/12.2318424
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Point clouds provide high-resolution topographic data which is often classified into bare-earth, vegetation, and building points and then filtered and aggregated to gridded Digital Elevation Models (DEMs) or Digital Terrain Models (DTMs). Based on these equally-spaced grids flow-accumulation algorithms are applied to describe the hydrologic and geomorphologic mass transport on the surface. In this contribution, we propose a stochastic point-cloud filtering that, together with a spatial bootstrap sampling, allows for a flow accumulation directly on point clouds using Facet-Flow Networks (FFN). Additionally, this provides a framework for the quantification of uncertainties in point-cloud derived metrics such as Specific Catchment Area (SCA) even though the flow accumulation itself is deterministic.

Conference Presentation

Citation Download Citation

Aljoscha Rheinwalt and Bodo Bookhagen "Network-based flow accumulation for point clouds: Facet-Flow Networks (FFN)", Proc. SPIE 10783, Remote Sensing for Agriculture, Ecosystems, and Hydrology XX, 107831C (10 October 2018); https://doi.org/10.1117/12.2318424

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