Abstract
Lakes and reservoirs, as most humans experience and use them, are dynamic bodies of water, with surface extents that increase and decrease with seasonal precipitation patterns, long-term changes in climate, and human management decisions. This paper presents a new global dataset that contains the location and surface area variations of 681,137 lakes and reservoirs larger than 0.1 square kilometers (and south of 50 degree N) from 1984 to 2015, to enable the study of the impact of human actions and climate change on freshwater availability. Within its scope for size and region covered, this dataset is far more comprehensive than existing datasets such as HydroLakes. While HydroLAKES only provides a static shape, the proposed dataset also has a timeseries of surface area and a shapefile containing monthly shapes for each lake. The paper presents the development and evaluation of this dataset and highlights the utility of novel machine learning techniques in addressing the inherent challenges in transforming satellite imagery to dynamic global surface water maps.
| Original language | English (US) |
|---|---|
| Article number | 356 |
| Journal | Scientific Data |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2022 |
Bibliographical note
Funding Information:This work was supported in part by United States National Science Foundation Awards 1029711, 1838159, 1934633, and NASA grant NNX12AP37G. Access to computing facilities was provided by the University of Minnesota Supercomputing Institute.
Funding Information:
This work was supported in part by United States National Science Foundation Awards 1029711, 1838159, 1934633, and NASA grant NNX12AP37G. Access to computing facilities was provided by the University of Minnesota Supercomputing Institute.
Publisher Copyright:
© 2022, The Author(s).
