[RS-ecology] PhD: Ecological applications of LiDAR

[Martin Wegmann]

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    PhD candidate in Ecology and Remote Sensing

Closing date

    24 February 2017

Supported by an eScience grant from the Netherlands eScience Center 
<https://www.esciencecenter.nl/project/eecolidar>, we have a vacancy for 
a PhD candidate on a project entitled: 'eEcoLiDAR, eScience 
infrastructure for Ecological applications of LiDAR point clouds: 
reconstructing the 3D ecosystem structure for animals at regional to 
continental scales'.

Distribution and abundance of many animals depends on the complexity of 
vegetation, but high-resolution measurements of 3D ecosystem structures 
across broad spatial extents are largely lacking. In this project, we 
aim to fill this gap by using Light Detection and Ranging (LiDAR) 
technology to characterize the vertical and horizontal complexity of 
vegetation and landscapes at high resolution across regional to 
continental scales. We will use massive amounts of LiDAR point clouds to 
classify objects such as trees, forests, vegetation strata, edges, 
bushes, hedges, and reedbeds. These newly LiDAR-derived 3D ecosystem 
structures will then be applied in species distribution models for 
animals in forests, marshlands and agricultural areas to better 
understand animal-habitat associations across Europe.

This PhD-project will apply and develop multi-scale object-based image 
analysis (OBIA) for the interpretation of LiDAR point clouds, including 
data storage, scalable computing, tools for machine learning and 
visualization (feature selection, annotation / segmentation, object 
classification, and evaluation). The project is supported by an eScience 
engineer who will develop a workbench that supports the workflow for 
handling, storage, and interactive object-based image analysis (OBIA) of 
massive amounts of LiDAR point cloud data using state of the art point 
cloud processing tools. In addition to developing the OBIA methodology, 
the PhD candidate will use the classified 3D ecosystem structures for 
species distribution modelling.

http://www.uva.nl/en/about-the-uva/working-at-the-uva/vacancies/item/17-033-phd-candidate-in-ecology-and-remote-sensing.html?m

-- 
Dr. Martin Wegmann

University of Wuerzburg
Institute of Geography
Department of Remote Sensing
Remote Sensing and Biodiversity Research
Am Hubland
Oswald Kuelpe Weg 86
97074 Wuerzburg, Germany

German Aerospace Center (DLR)
German Remote Sensing Data Center (DFD)

Phone:  +49-(0)931-31 83446
Email:  martin.wegmann at uni-wuerzburg.de

url: http://www.geographie.uni-wuerzburg.de/en/fernerkundung_neu/startseite/
url: http://www.dlr.de/caf