A simple cloud-filling approach for remote sensing water cover assessments

Mullen, Connor; Penny, Gopal; Müller, Marc F.

doi:https://doi.org/10.5194/hess-25-2373-2021

Articles | Volume 25, issue 5

https://doi.org/10.5194/hess-25-2373-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-2373-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 5

Research article

|

06 May 2021

Research article |

| 06 May 2021

A simple cloud-filling approach for remote sensing water cover assessments

Connor Mullen, Gopal Penny, and Marc F. Müller

Supplement

https://doi.org/10.5194/hess-25-2373-2021-supplement

Data sets

Water Data for the Nation USGS https://waterdata.usgs.gov/nwis

Texas Reservoirs Texas Water Development Board https://www.waterdatafortexas.org/reservoirs/statewide

Model code and software

Gap-filling algorithm combined with MNDWI-based classification of Landsat 7 images C. Mullen and M. F Muller https://code.earthengine.google.com/49efc5e51b9257da9a72d45c8ce486be

Numerical experiments used to test the four underlying assumptions C. Mullen and M. F Muller https://code.earthengine.google.com/1d7e23f5d5594ff9574fa73dd651b52e

JRC Global Surface Water Metadata, v1.1 J.-F. Pekel, A. Cottam, N. Gorelick, and A. S. Belward https://code.earthengine.google.com/b41fdccbe6267d6a7e4c40deae8e9bf5

Short summary

The level of lake water is rapidly changing globally, and long-term, consistent observations of lake water extents are essential for ascertaining and attributing these changes. These data are rarely collected and challenging to obtain from satellite imagery. The proposed method addresses these challenges without any local data, and it was successfully validated against lakes with and without ground data. The algorithm is a valuable tool for the reliable historical water extent of changing lakes.