By Topic

Differentiation of urban surfaces based on hyperspectral image data and a multi-technique approach

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Segl, K. ; GeoForschungsZentrum Potsdam, Germany ; Roessner, S. ; Heiden, U.

Airborne hyperspectral data yield a new potential for spectrally-based identification, but also raise new challenges in image analysis caused by a high spatial and spectral variability of the urban environment. The algorithms have to analyze spectrally mixed and non-mixed-pixels of various classes which often show spectrally similar characteristics. In this context the authors developed a multi-technique approach which combines linear spectral unmixing and spectral classification for a complete inventory of main urban surface cover types. Despite the good results, problems remained in differentiation of spectrally similar surfaces, such as buildings and sealed open surfaces. The authors present an improved approach including a new algorithm for shape-based detection of buildings and new rules for an optimized pixel-oriented endmember selection. The approach was developed using DAIS hyperspectral image data of the reflective and thermal wavelength ranges covering a study area in the city of Dresden (Germany). In the result a much improved identification of urban surfaces was achieved due to the incorporation of shape-based techniques

Published in:

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International  (Volume:4 )

Date of Conference:

2000