Abstract
This study conducts an exploratory evaluation of the performance of the newly available Sentinel-2A Multispectral Instrument (MSI) imagery for mapping water bodies using the image sharpening approach. Sentinel-2 MSI provides spectral bands with different resolutions, including RGB and Near-Infra-Red (NIR) bands in 10 m and Short-Wavelength InfraRed (SWIR) bands in 20 m, which are closely related to surface water information. It is necessary to define a pan-like band for the Sentinel-2 image sharpening process because of the replacement of the panchromatic band by four high-resolution multi-spectral bands (10 m). This study, which aimed at urban surface water extraction, utilised the Normalised Difference Water Index (NDWI) at 10 m resolution as a high-resolution image to sharpen the 20 m SWIR bands. Then, object-level Modified NDWI (MNDWI) mapping and minimum valley bottom adjustment threshold were applied to extract water maps. The proposed method was compared with the conventional most related band- (between the visible spectrum/NIR and SWIR bands) based and principal component analysis first component-based sharpening. Results show that the proposed NDWI-based MNDWI image exhibits higher separability and is more effective for both classification-level and boundary-level final water maps than traditional approaches.
Highlights
Urban surface water bodies, which significantly influence public health and the living environment, are important parameters in urban planning, regional climate, and the heat island effect
This study, which aimed at urban surface water extraction, utilised the Normalised Difference Water Index (NDWI) at 10 m resolution as a high-resolution image to sharpen the 20 m Short-Wavelength InfraRed (SWIR) bands
Various remote sensing data have been utilised in water surface mapping, including Synthetic Aperture Radar (SAR) satellites [1,2], LiDAR data [3], and various spatial resolution optical satellite images ranging from low-resolution [4,5] to very high-resolution imagery [6,7]
Summary
Urban surface water bodies, which significantly influence public health and the living environment, are important parameters in urban planning, regional climate, and the heat island effect. Numerous techniques have been applied to characterise and quantify water bodies using either ground measurements of field surveys or remotely sensed data. Remote sensing provides repetitive mapping in time- and cost-saving modes. Various remote sensing data have been utilised in water surface mapping, including Synthetic Aperture Radar (SAR) satellites [1,2], LiDAR data [3], and various spatial resolution optical satellite images ranging from low-resolution [4,5] to very high-resolution imagery [6,7]. Images from moderate-resolution optical satellites, such as Landsat, Advanced Spaceborne
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
