Universitätssiegel
Project
Funding: DFG
Runtime: 2011 - 2012
 

Research project

Airborne Laser Scanning for 3D Vegetation Characterization: Set-up of an International Signature Database


Mapping and characterization of vegetation by means of remote sensing is increasingly gaining in importance. Particularly, the inherent three-dimensional nature of high vegetation (i.e. forests) demands for new technologies and scientific approaches which are capable of assessing the full 3D perspective. Airborne laser scanning (ALS) has evolved into a state-of-the-art technology for highly accurate topographic data acquisition. Pioneer studies have already indicated a high value for 3D surface characterization. However, the full potential for 3D vegetation characterization has not been exploited so far. Deeper insight is required for prominent tasks in forest inventory and management, carbon sink analysis, biodiversity characterization, habitat analysis and renewable energy production. This research aims at bridging the gap between sensor and target perspective by systematic exploratory analysis of ALS vegetation signatures. These signatures describe characteristic properties of defined reference objects provided in laser data representation and are fundamental for increasing the understanding of the interaction of laser beam (sensor) and vegetation (target). As central element of this research a novel international open access ALS signature database will be established, which serves as unique tool for management and analysis of valuable reference signatures. This project seeks to develop a research exchange between several leading international groups focusing on improved methods for vegetation and forest characterization using ALS data. ALS data is frequently captured with different sensors and field specifications. The resulting technical challenges, related to data fusion, scale and data quantity are best addressed by a community of scientists who share approaches and data. Thus it is important to foster the exchange of information and techniques so that the discipline will continue to grow.

Cooperations:

  • University of California Berkeley, Ecosystem Sciences Division, Dept. of Environmental Sciences, Policy and Management (Berkeley, USA)
  • Vienna University of Technology, Institute of Photogrammetry and Remote Sensing (IPF; Vienna, Austria)
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