Evaluation of multi-temporal/sensor data fusion for urban change analysis

Research output: Contribution to conferencePaperpeer-review

Abstract

Natural Resource Management, Planning and Monitoring programs depend on accurate information about the land cover/use for varying sized regions. Satellite sensor images with moderate to various resolutions have facilitated scientific research activities at landscape and regional scales. In this study, a part of Istanbul metropolitan area that faced a great land cover/use change was investigated. For that purpose, 1992 dated SPOT 4 panchromatic image was fused with 2017 dated Landsat 8 OLI multispectral data. As an inverse approach 2017 dated Landsat 8 OLI Panchromatic image was fused with 1984 dated Landsat 5 TM multispectral data. Image fusion processes was performed using Gram Schmidt spectral sharpening algorithm which integrates all bands of the multispectral image into fusion. After fusion operations, two image datasets were classified in order to determine land cover/use changes. Results of the study showed that proposed methodology provided efficient and rapid determination of the changes due to their distinct spectral characteristics from their surroundings in fused images. These methods add significant advantages for land use/cover classification.

Original languageEnglish
Publication statusPublished - 2017
Event38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017 - New Delhi, India
Duration: 23 Oct 201727 Oct 2017

Conference

Conference38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017
Country/TerritoryIndia
CityNew Delhi
Period23/10/1727/10/17

Bibliographical note

Publisher Copyright:
Copyright © 2017 ISRS, All Rights Reserved.

Keywords

  • Gram Schmidt fuse algorithm
  • Image fusion
  • Istanbul
  • Land cover/use change

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