Sub-pixel mapping of water boundaries using pixel swapping algorithm (case study: Tagliamento River, Italy)

Milad Niroumand-Jadidi; Alfonso Vitti

doi:10.1117/12.2194579

14 October 2015 Sub-pixel mapping of water boundaries using pixel swapping algorithm (case study: Tagliamento River, Italy)

Milad Niroumand-Jadidi, Alfonso Vitti

Author Affiliations +

Proceedings Volume 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015; 96380G (2015) https://doi.org/10.1117/12.2194579
Event: SPIE Remote Sensing, 2015, Toulouse, France

Abstract

Taking the advantages of remotely sensed data for mapping and monitoring of water boundaries is of particular importance in many different management and conservation activities. Imagery data are classified using automatic techniques to produce maps entering the water bodies’ analysis chain in several and different points. Very commonly, medium or coarse spatial resolution imagery is used in studies of large water bodies. Data of this kind is affected by the presence of mixed pixels leading to very outstanding problems, in particular when dealing with boundary pixels. A considerable amount of uncertainty inescapably occurs when conventional hard classifiers (e.g., maximum likelihood) are applied on mixed pixels.

In this study, Linear Spectral Mixture Model (LSMM) is used to estimate the proportion of water in boundary pixels. Firstly by applying an unsupervised clustering, the water body is identified approximately and a buffer area considered ensuring the selection of entire boundary pixels. Then LSMM is applied on this buffer region to estimate the fractional maps. However, resultant output of LSMM does not provide a sub-pixel map corresponding to water abundances. To tackle with this problem, Pixel Swapping (PS) algorithm is used to allocate sub-pixels within mixed pixels in such a way to maximize the spatial proximity of sub-pixels and pixels in the neighborhood.

The water area of two segments of Tagliamento River (Italy) are mapped in sub-pixel resolution (10m) using a 30m Landsat image. To evaluate the proficiency of the proposed approach for sub-pixel boundary mapping, the image is also classified using a conventional hard classifier. A high resolution image of the same area is also classified and used as a reference for accuracy assessment. According to the results, sub-pixel map shows in average about 8 percent higher overall accuracy than hard classification and fits very well in the boundaries with the reference map.

Citation Download Citation

Milad Niroumand-Jadidi and Alfonso Vitti "Sub-pixel mapping of water boundaries using pixel swapping algorithm (case study: Tagliamento River, Italy)", Proc. SPIE 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015, 96380G (14 October 2015); https://doi.org/10.1117/12.2194579

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