_Remote Sens._**2013**, \(5\), 5530-5549; doi:10.3390/rs5115530  
_Remote Sensing_  
ISSN 2072-4292  
www.mdpi.com/journal/renotesensing  
A Comparison of Land Surface Water Mapping Using the Normalized Difference Water Index from TM, ETM+ and ALI  
**[PERSON] 1, [PERSON] 2,*, [PERSON] 3, [PERSON] 4, [PERSON] 1, [PERSON] 1,**  
**[PERSON] 1 and [PERSON] 1**  
1 Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China; E-Mails: [EMAIL_ADDRESS] (W.L.); [EMAIL_ADDRESS] (H.W.); [EMAIL_ADDRESS] (Y.G.); [EMAIL_ADDRESS] (B.S.); [EMAIL_ADDRESS] (X.Z.)  
2 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China  
3 Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China; E-Mail: [EMAIL_ADDRESS]  
4 National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430079, China; E-Mail: [EMAIL_ADDRESS]  
*Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +86-27-6877-8779; Fax: +86-27-6877-8229.  
_Received: 5 August 2013; in revised form: 15 October 2013 / Accepted: 16 October 2013 / Published: 28 October 2013_  
**Abstract:** Remote sensing has more advantages than the traditional methods of land surface water (LSW) mapping because it is a low-cost, reliable information source that is capable of making high-frequency and repeatable observations. The normalized difference water indexes (NDWIs), calculated from various band combinations (green, near-infrared (NIR), or shortwave-infrared (SWIR)), have been successfully applied to LSW mapping. In fact, new NDWIs will become available when Advanced Land Imager (ALI) data are used as the ALI sensor provides one green band (Band 4), two NIR bands (Bands 6 and 7), and three SWIR bands (Bands 8, 9, and 10). Thus, selecting the optimal band or combination of bands is critical when ALI data are employed to map LSW using NDWI. The purpose of this paper is to find the best performing NDWI model of the ALI data in LSW map. In this study, eleven NDWI models based on ALI, Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data were compared to assess the performance of ALI data in LSW mapping, at three different study sites in the Yangtze River Basin, China. The contrast method, Otsu method, and confusion matrix were calculated to evaluate the accuracies of the LSW maps. The accuracies of LSW maps derived from eleven NDWI models showed that five NDWI models of the ALI sensor have more than an overall accuracy of 91% with a Kappa coefficient of 0.78 of LSW maps at three test sites. In addition, the NDWI model, calculated from the green (Band 4: 0.525-0.605 \(\upmu\)m) and SWIR (Band 9: 1.550-1.750 \(\upmu\)m) bands of the ALI sensor, namely NDWI\({}_{\text{A4},9}\), was shown to have the highest LSW mapping accuracy, more than the other NDWI models. Therefore, the NDWI\({}_{\text{A4},9}\) is the best indicator for LSW mapping of the ALI sensor. It can be used for mapping LSW with high accuracy.  
**Keywords:** remote sensing; image segmentation; land surface water mapping; Advanced Land Imager (ALI); normalized difference water index; Landsat