## 1 Introduction  
Water resources are one of the irreplaceable strategic resources for human survival. Land surface water (LSW) is an important part of the water cycle. LSW mapping, using remote sensing techniques, plays an important role in wetland monitoring [1, 2, 3], flood monitoring [4, 5, 6], flood disaster assessment [7, 8, 9, 10], surface water area estimation [11, 12, 13, 14], and water resources management [15, 16, 17]. Over three decades, multi-resource remote sensing data, such as data from the Advanced Very High Resolution Radiometer (AVHRR) [5, 6, 18], Moderate-resolution Imaging Spectroradiometer (MODIS) [16, 19], Small Satellite Constellation For Environment and Disaster Monitoring And Forecasting A/B Satellites (HJ-1A/B) [12, 20], Multispectral Scanner System (MSS) [6, 11], Thematic Mapper (TM) [13, 20, 21], and Enhanced Thematic Mapper Plus (ETM+) [7, 11] have been employed to extract information on land surface water bodies. One widely used remote sensing dataset for LSW mapping are the TM and ETM+ images provided by the Landsat series satellites [11]. The Landsat-7 mission was flawless until May, 2003, when a hardware component failure left wedge-shaped spaces of missing data on either side of ETM+ images. The U.S. Geological Survey (USGS) stopped acquiring images from the 27-year-old Landsat-5 satellite in November 2011, due to a rapidly degrading electronic component that threatened to end the Landsat-5 mission. Fortunately, the National Aeronautics and Space Administration (NASA) launched the eighth Landsat satellite (Landsat-8) on 11 February 2013. NASA also launched a technology validation and demonstration mission satellite called Earth Observation-1 (EO-1). The Advanced Land Imager (ALI) instrument onboard EO-1 was used to validate and demonstrate technology for Landsat-8. The primary focus of EO-1 is to develop and test a set of advanced technology land-imaging instruments. EO-1 has been inserted into the same orbit as the Landsat-7 satellite, and is taking a series of the same images. Operating in a pushing broom pattern, at an altitude of 705 km, the ALI sensor provides panchromatic images at 10 m spatial resolution and nine bands of multispectral images at 30 m resolution. These nine multispectral bands have been designed to simulate the six Landsat-7 bands, with the three additional bands covering 0.433-0.453 \(\upmu\)m, 0.845-0.890 \(\upmu\)m, and 1.20-1.30 \(\upmu\)m. ALI remote sensing images are potentially useful in various applications related to land cover mapping [22], vegetation mapping [23, 24], forest classification [25], and the evaluation of dissolved organic matter in lake water [26]. Many studies have also examined the potential comparison of the ALI sensor to the TM and ETM+ sensors [24, 27, 28, 29]. However, inadequate attention has been paid to examining ALI's capability of delineating water bodies and mapping LSW, particularly in comparison to other sensors. The purpose of this study is to assess the potential of the ALI data for LSW mapping so that EO-1 and the series of Landsat satellite data can be clearly used to delineate water body information and to map LSW in the future. Surface water body information detection is of great significance to very related research in remote sensing [11]. Various surface water body information extracting algorithms [1, 2, 3, 11, 12, 13, 18, 19, 20, 21, 30, 31, 32, 33, 34, 35, 36, 37, 38] have been developed as they are the key points for transferring remotely sensed images into information for practical applications, such as LSW mapping [36]. In brief, these algorithms identify water in two broad ways: the general feature classification method [2, 3, 30, 31, 35, 39] and the thematic water body information detection method [1, 11, 12, 13, 18, 19, 20, 21, 32, 33, 34, 36].