• Corpus ID: 17817561

An Evolutionary Approach towards Clustering Airborne Laser Scanning Data

  title={An Evolutionary Approach towards Clustering Airborne Laser Scanning Data},
  author={Ronald Hochreiter and Christoph Waldhauser},
In land surveying, the generation of maps was greatly simplified with the introduction of orthophotos and at a later stage with airborne LiDAR laser scanning systems. While the original purpose of LiDAR systems was to determine the altitude of ground elevations, newer full wave systems provide additional information that can be used on classifying the type of ground cover and the generation of maps. The LiDAR resulting point clouds are huge, multidimensional data sets that need to be grouped in… 

Figures and Tables from this paper


Airborne laser scanning—an introduction and overview
Genetic algorithm-based clustering technique
Computational cluster validation in post-genomic data analysis
This review paper aims to familiarize the reader with the battery of techniques available for the validation of clustering results, with a particular focus on their application to post-genomic data analysis.
Evolutionary Multi-stage Financial Scenario Tree Generation
A new evolutionary algorithm to create scenario trees for multi-stage financial optimization models will be presented and numerical results and implementation details are presented.
R: A language and environment for statistical computing.
Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice
Evolutionary Optimization for Decision Making under Uncertainty
This overview article surveys Evolutionary Optimization techniques to solve Stochastic Programming problems - both for the single-stage and multi-stage case.
Well separated clusters and fuzzy partitions
  • Journal on Cybernetics
  • 1974
clValid: Validation of Clustering Results
  • clValid: Validation of Clustering Results
  • 2011
proxy: Distance and Similarity Measures, 2012. R package version 0.4-7
  • 2012