Global Inland Water

Data Access

Inland surface water bodies-including fresh and saline lakes, rivers, and reservoirs- cover only a small portion of the Earth's surface, but they are essential to terrestrial ecosystems and human civilization. The spatial distribution of water and its changes over time are central to many agricultural, environmental and ecological issues and are critical factors for human socioeconomic development. Accurate, high-resolution mapping of surface water is essential for the science and management of terrestrial ecosystems.

From the GLS 2000 epoch, 3,650,723 km2 of inland water were identified, around three quarters of which were in North America and Asia. Boreal forests and tundra hold the largest portion of inland water, about 40% of the global total. GIW exhibits strong linear correlation with both the MODIS dataset as well as 30-m resolution datasets over the United States and Canada. Residual errors were due primarily to the seasonality of water cover, snow and ice, and residual clouds.

Code Values
Value Label
0 No Data
1 Land
2 Water
4 Snow/Ice
200 Cloud shadow
201 Cloud
How to Cite This Data Set

Citation Format: Author (Publication Date), Collection Name, Product Name, Processing Level, Publisher, Publisher Location, Product Coverage Date.

Data Citation Parameters Example:

  • Author: Feng, Min, Joseph O. Sexton, Saurabh Channan, and John R. Townshend
  • Publication Date: 2015
  • Collection Name: Global Inland Water
  • Version: 1.0
  • Publisher: Global Land Cover Facility, Department of Geography, University of Maryland
  • Publisher Location: College Park, Maryland
  • Product Coverage Date: Circa 2000

Associated Peer-Reviewed Publication: Feng, Min, Joseph O. Sexton, Saurabh Channan, and John R. Townshend. 2015. "A Global, High-Resolution (30-M) Inland Water Body Dataset for 2000: First Results of a Topographic-Spectral Classification Algorithm." International Journal of Digital Earth. doi:10.1080/17538947.2015.1026420.

Intellectual Property Rights

University of Maryland; Department of Geography; use is free to all if acknowledgement is made. UMD holds ultimate copyright.


Source for this data set is the Global Land Cover Facility,

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