An evaluation of Suomi NPP-VIIRS data for surface water detection

Abstract

Measuring surface water using remote sensing technology is an essential research topic in many research areas, including flood-related studies and water resource management. Recent advances in satellite remote sensing provide more efficient ways of monitoring surface water from space. As a newly available data source with a high frequency of global coverage and moderate resolution, Visible Infrared Imaging Radiometer Suite on board the Suomi National Polar-orbiting Partnership (Suomi NPP-VIIRS) has the advantage of monitoring the earth surface intensively and continuously. This study conducts an exploratory evaluation on the performance of Suomi NPP-VIIRS data for surface water detection. A Modified Histogram method was proposed and applied to its shortwave infrared (SWIR) band to estimate the water fraction within each single pixel. The estimated surface water fraction was then compared with that derived from a corresponding Moderate Resolution Imaging Spectroradiometer (MODIS) image and evaluated using a higher-resolution Landsat Operational Land Imager image. Evaluation results demonstrate that surface water was successfully delineated using the Suomi NPP-VIIRS SWIR band, even at sub-pixel level, bearing in mind that cloud and shadow may interfere surface water detection. A more precise detection result usually requires some additional approaches to help distinguish surface water from cloud and shadow. It was also revealed that the Suomi NPP-VIIRS can be an ideal surrogate of MODIS.

Acknowledgement

The authors are grateful to the editor and two anonymous reviewers for their constructive comments and suggestions.

ORCID

Chang Huang http://orcid.org/0000-0002-8621-4581

Additional information

Funding

This work was supported by National Major Scientific Research Program [grant number 2013CBA01806]; the Special Trade Project for Commonweal of Water Resources [grant number 201401026]; Social Development Scientific Plan [grant number 2012CA021]; Shanxi Key Science and Technology Innovation Team [grant number 2014KCT-27]; Northwest University Natural Science Foundation [grant number NI15005].