@misc{RheinwaltBookhagen2018,
  author    = {Rheinwalt, Aljoscha and Bookhagen, Bodo},
  title     = {Network-based flow accumulation for point clouds},
  series = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XX},
  volume    = {10783},
  journal   = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XX},
  publisher = {SPIE-INT Society of Photo-Optical Instrumentation Engineers},
  address   = {Bellingham},
  isbn      = {978-1-5106-2150-3},
  issn      = {0277-786X},
  doi       = {10.1117/12.2318424},
  pages     = {12},
  year      = {2018},
  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.},
  language  = {en}
}
@article{WielandDalchowSommeretal.2011,
  author    = {Wieland, Ralf and Dalchow, Claus and Sommer, Michael and Fukuda, Kyoko},
  title     = {Multi-Scale Landscape Analysis (MSLA) a method to identify correlation of relief with ecological point data},
  series = {Ecological informatics : an international journal on ecoinformatics and computational ecolog},
  volume    = {6},
  journal   = {Ecological informatics : an international journal on ecoinformatics and computational ecolog},
  number    = {2},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1574-9541},
  doi       = {10.1016/j.ecoinf.2010.09.002},
  pages     = {164 -- 169},
  year      = {2011},
  abstract  = {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.},
  language  = {en}
}