TY  - GEN
A1  - Rheinwalt, Aljoscha
A1  - Bookhagen, Bodo
T1  - Network-based flow accumulation for point clouds
BT  - Facet-Flow Networks (FFN)
T2  - Remote Sensing for Agriculture, Ecosystems, and Hydrology XX
N2  - 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.
KW  - lidar
KW  - point clouds
KW  - stochastic filtering
KW  - flow accumulation
KW  - drainage networks
KW  - uncertainty quantification
KW  - TIN
KW  - DEM
Y1  - 2018
SN  - 978-1-5106-2150-3
U6  - https://doi.org/10.1117/12.2318424
SN  - 0277-786X
SN  - 1996-756X
VL  - 10783
PB  - SPIE-INT  Society of Photo-Optical Instrumentation Engineers
CY  - Bellingham
ER  - 
TY  - JOUR
A1  - Wieland, Ralf
A1  - Dalchow, Claus
A1  - Sommer, Michael
A1  - Fukuda, Kyoko
T1  - Multi-Scale Landscape Analysis (MSLA) a method to identify correlation of relief with ecological point data
JF  - Ecological informatics : an international journal on ecoinformatics and computational ecolog
N2  - A common problem in ecology is identifying the relationship between relief and site properties obtainable only by point measurements. The method of Multi-Scale Landscape Analysis (MSLA) identifies such correlations. MSLA combines frequency filtering of the digital elevation model (DEM) with an estimation of the optimum filter coefficients using an optimization procedure. Tested using point data of soil decarbonation from a German young moraine landscape, MSLA provided significant results. Implemented within open source software SAMT. MSLA is comfortable and flexible to use, offering applications for numerous other spatial analysis problems.
KW  - Landscape structure
KW  - DEM
KW  - Fourier transformation
KW  - Wavelet transformation
KW  - Singular value decomposition
KW  - SAMT
Y1  - 2011
U6  - https://doi.org/10.1016/j.ecoinf.2010.09.002
SN  - 1574-9541
VL  - 6
IS  - 2
SP  - 164
EP  - 169
PB  - Elsevier
CY  - Amsterdam
ER  -