Chapter 13. Towards an Automated Update of Urban Biotope Maps Using Remote Sensing Data: What is Possible?

  1. Norbert Müller2,
  2. Peter Werner3 and
  3. John G. Kelcey4
  1. Mathias Bochow,
  2. Theres Peisker,
  3. Sigrid Roessner,
  4. Karl Segl and
  5. Hermann Kaufmann

Published Online: 16 APR 2010

DOI: 10.1002/9781444318654.ch13

Urban Biodiversity and Design

Urban Biodiversity and Design

How to Cite

Bochow, M., Peisker, T., Roessner, S., Segl, K. and Kaufmann, H. (2010) Towards an Automated Update of Urban Biotope Maps Using Remote Sensing Data: What is Possible?, in Urban Biodiversity and Design (eds N. Müller, P. Werner and J. G. Kelcey), Wiley-Blackwell, Oxford, UK. doi: 10.1002/9781444318654.ch13

Editor Information

  1. 2

    Department Landscape Management & Restoration Ecology, University of Applied Sciences Erfurt, Landscape Architecture, Post-box, 450155, 99081 Erfurt, Germany

  2. 3

    Institute Housing and Environment, Annastr. 15, 64285 Darmstadt, Germany

  3. 4

    Ceckovice 14, Bor U Tachova 348 02, Czech Republic

Author Information

  1. Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing, Telegrafenberg, 14473 Potsdam, Germany

Publication History

  1. Published Online: 16 APR 2010
  2. Published Print: 16 APR 2010

ISBN Information

Print ISBN: 9781444332667

Online ISBN: 9781444318654

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Keywords:

  • automated urban biotope mapping, using remote sensing data;
  • urban biotope mapping, introduction - Germany, 1970s;
  • urban biotope maps - in ecological urban planning;
  • biotope - basic spatial mapping unit;
  • digital surface model (DSM) - airborne laser altimeter;
  • hyperspectral image data - digital airborne imaging spectrometer;
  • input information for biotope identification - remote sensing-based derivation;
  • systemic spectral acquisition of surface materials;
  • fuzzy-logic based urban isotope identification;
  • feature-based fuzzy logic model development

Summary

This chapter contains sections titled:

  • Summary

  • Introduction

  • Study area and data

  • Remote sensing-based derivation of input information for biotope identification

  • Fuzzy-logic based identification of urban biotopes

  • Conclusions and outlook

  • References