Wednesday, November 15, 2017

Riparian forest habitat structure by hierarchical class modelling - Donauauen

Suggested by: Barbara Riedler, Stefan Lang

Background

Riparian forests are among the most complex ecological systems and most important biodiversity hotspots worldwide, but are at the same time amongst the most threatened European ecosystems. Management of such protected areas requires detailed knowledge about the occurring habitats. Earth Observation (EO) data can thereby compliment in-situ data and support the monitoring of protected areas through their advantage of area-wide coverage, overcoming the problem of accessibility and the option of regular, cost-efficient updates. Habitat classification based on species classification, their composition and age classes were applied for a variety of vegetation types using different EO data. Such habitat classification and modelling can be the basis for further analyses such as the assessment of habitat quality, its conservation status, monitoring of biodiversity or the evaluation of conservation measurements like water restoration projects.

Short description

The aim of the MSc thesis is to automatically classify habitats of the riparian forest of the Donauauen, Austria using very high resolution (VHR) satellite imagery. Previous work in the Salzachauen showed that single tree species classification based WorldView-2 imagery is possible using an OBIA (object based image analyses) approach. Based on such a single tree detection, habitat modelling following different habitat classification schemes (Habitats directive, EUNIS) leads to area-wide coverage and harmonized trans-boundary results of habitat classification, which in turn can be the basis for the assessment of habitat quality. As every riparian forest has its own characteristics (e.g. different tree species composition, age structure, water regime,….) the transferability of existing work and rulesets has not been proven and should be implemented in this work.
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Literature
  • Strasser, T., Lang, S., Riedler, B., Pernkopf, L., Paccagnel K., 2014, Multiscale Object Feature Library for Habitat Quality Monitoring in Riparian Forests, Geoscience Remote Sens. Lett. IEEE, 559-563.
  • Riedler, B., Pernkopf, L., Strasser, T., Lang, S., Smith, G., 2015, A composite indicators for assesing habitat quality of riparain forests derived from Earth observation data, Int. J. Appl. Earth Observ. Geoinf. 37, 114-123.
  • Riedler, B., Lang, S., in press, A spatially explicit model of habitat quality, integrating spatio-structural indicators, Ecological Indicators, http://dx.doi.org/10.1016/j.ecolind.2017.04.027

Start
any time

Prerequisites / qualification

basic knowledge in e-cognition / OBIA
interest and knowledge in ecology / botany is helpful


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