elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Contact | Deutsch
Fontsize: [-] Text [+]

Klassifikation einer Zeitserie von AWiFS-Multispektraldaten

Schaumberger, Stefan (2012) Klassifikation einer Zeitserie von AWiFS-Multispektraldaten. Diploma, Julius-Maximilians-Universität Würzburg.

Full text not available from this repository.

Abstract

In regard of the EU project TIRAMISU different LULC classification methods are tested and compared. Additionally, their implementation in the DLR internal image processing program is checked for proper operation. This is done by use of a time series of 14 IRS-P6 AWiFS images from 2011 of an area in southern Germany. After analysing, correcting and bypassing errors in the data basis, the k-means, maximum-likelihood and fuzzy classification are applied. Additionally a hierarchical classifier is developed. In consideration of lack of quality in the data basis, all the methods deliver good overall accuracies in between 77% and 81%. The self-developed decision tree achieves the best result. With respect to TIRAMISU it has to be noted that for an area with the natural landscape present in southern Germany (small plots of surface types), a geometric resolution of 60 meters is too low. On the other hand, the use of a time series turns out to be useful due to a high reliability. Identified objectives for improvements as well as errors of the image processing program are documented. Which classification methods are supposed to be used for the TIRAMISU project cannot be determined until the data basis and its characteristics are defined. To achieve the required high reliability, multiple methods are recommended to be applied in parallel.

Document Type:Thesis (Diploma)
Title:Klassifikation einer Zeitserie von AWiFS-Multispektraldaten
Authors:
AuthorsInstitution or Email of Authors
Schaumberger, Stefanstefan.schaumberger@dlr.de
Date:November 2012
Number of Pages:89
Status:Published
Keywords:classification, time series, project TIRAMISU, AWiFS, maximum-likelihood, fuzzy classification, decision tree
Institution:Julius-Maximilians-Universität Würzburg
Department:Institut für Geographie
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Dr.-Ing. Danielle Hoja
Deposited On:13 Nov 2012 12:45
Last Modified:16 Jul 2013 14:26

Repository Staff Only: item control page

Browse
Search
Help & Contact
Informationen
electronic library is running on EPrints 3.3.12
Copyright © 2008-2012 German Aerospace Center (DLR). All rights reserved.