Urban landcover mapping using different spectral mixture analysis methods

L. F. V. Zoran; C. Ionescu Golovanov; M. A. Zoran

doi:10.1117/12.830203

7 October 2009 Urban landcover mapping using different spectral mixture analysis methods

L. F. V. Zoran, C. Ionescu Golovanov, M. A. Zoran

Proceedings Volume 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX; 747814 (2009) https://doi.org/10.1117/12.830203
Event: SPIE Remote Sensing, 2009, Berlin, Germany

Abstract

The complex spatial and spectral variability of urban structures present fundamental challenges to deriving accurate remote sensing information for urban areas. Spectral mixture analysis (SMA), based on a physical mixture model, has ability to extract sub-pixel information such as the abundances of each endmember presented in the pixel (image unity). In this paper, different spectral mixture methods have been applied in order to examine the performance of each model in dealing with spectral variability of urban surface. The comparison is focused on linear spectral mixture analysis (LSMA) which is using a fixed number of endmembers for the entire scene and multiple endmember spectral mixture analysis (MESMA) which allows the number and types of endmembers to vary from pixel to pixel to extract the abundances of urban surface components. These techniques have been applied to map the physical components of urban land cover for the city of Bucharest, Romania, using Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+) and IKONOS imagery for 1989 - 2007 period. This paper demonstrates the potential of moderate-and high resolution, multispectral imagery to map and monitor the evolution of the physical urban environment.

Citation Download Citation

L. F. V. Zoran, C. Ionescu Golovanov, and M. A. Zoran "Urban landcover mapping using different spectral mixture analysis methods", Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 747814 (7 October 2009); https://doi.org/10.1117/12.830203

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available