Next Article in Journal
Modeling the Dispersion of E. coli in Waterbodies Due to Urban Sources: A Spatial Approach
Previous Article in Journal
Changes of Permeability of Nonwoven Geotextiles due to Clogging and Cyclic Water Flow in Laboratory Conditions
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Water 2017, 9(9), 658; https://doi.org/10.3390/w9090658

Coupling the Modified Linear Spectral Mixture Analysis and Pixel-Swapping Methods for Improving Subpixel Water Mapping: Application to the Pearl River Delta, China

1,2,3,4
,
1,* , 2,3,4,* and 5
1
Guangdong Engineering Research Center of Water Environment Remote Sensing Monitoring, Guangdong Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
2
Guangzhou Institute of Geography, Guangzhou 510070, China
3
Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, China
4
Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, China
5
Department of Computer Science, Guangdong University of Education, Guangzhou 510310, China
*
Authors to whom correspondence should be addressed.
Received: 7 July 2017 / Revised: 24 August 2017 / Accepted: 25 August 2017 / Published: 1 September 2017
Full-Text   |   PDF [20154 KB, uploaded 1 September 2017]   |  

Abstract

High-resolution water mapping with remotely sensed data is essential to monitoring of rainstorm waterlogging and flood disasters. In this study, a modified linear spectral mixture analysis (LSMA) method is proposed to extract high-precision water fraction maps. In the modified LSMA, the pure water and mixed water-land pixels, which are extracted by the Otsu method and a morphological dilation operation, are used to improve the accuracy of water fractions. The modified LSMA is applied to the 18 October 2015 Landsat 8 OLI image of the Pearl River Delta for the extraction of water fractions. Based on the water fraction maps, a modified subpixel mapping method (MSWM) based on a pixel-swapping algorithm is proposed for obtaining the spatial distribution information of water at subpixel scale. The MSWM includes two steps in subpixel water mapping. The MSWM considers the inter-subpixel/pixel and intra-subpixel/subpixel spatial attractions. Subpixel water mapping is first implemented with the inter-subpixel/pixel spatial attractions, which are estimated using the distance between a given subpixel and its surrounding pixels and the water fractions of the surrounding pixels. Based on the initialized subpixel water mapping results, the final subpixel water maps are determined by a modified pixel-swapping algorithm, in which the intra-subpixel/subpixel spatial attractions are estimated using the initialized subpixel water maps and an inverse-distance weighted function of the current subpixel at the centre of a moving window with its surrounding subpixels within the window. The subpixel water mapping performance of the MSWM is compared with that of subpixel mapping for linear objects (SPML) and that of the subpixel/pixel spatial attraction model (SPSAM) using the GF-1 reference image from 20 October 2015. The experimental results show that the MSWM shows better subpixel water mapping performance and obtains more details than SPML and SPSAM, as it has the largest overall accuracy values and Kappa coefficients. Furthermore, the MSWM can significantly eliminate the phenomenon of jagged edges and has smooth continuous edges. View Full-Text
Keywords: subpixel water mapping; Landsat 8 OLI; normalized difference water index; linear spectral mixture analysis subpixel water mapping; Landsat 8 OLI; normalized difference water index; linear spectral mixture analysis
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Liu, X.; Deng, R.; Xu, J.; Zhang, F. Coupling the Modified Linear Spectral Mixture Analysis and Pixel-Swapping Methods for Improving Subpixel Water Mapping: Application to the Pearl River Delta, China. Water 2017, 9, 658.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Water EISSN 2073-4441 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top