Annual NLCD Fractional Impervious Surface
The Annual National Land Cover Database (NLCD) impervious surface product represents the fractional surface area of the map unit (pixel) that is covered with artificial substrate or structures. This includes processed materials or structures (pavement, concrete, rooftops, and other constructed materials) that generate surface runoff. The majority of these materials are impervious to water, but many features that are not impervious like lawns and channelized ditches also contribute to surface runoff and water impairment.

The amount of impervious surface is generally less than suggested by the footprint of developed land cover because these classes often include permeable but developed vegetation, such as lawn grasses, that may be the majority surface cover. The impervious surface product provides a value for every land cover pixel mapped as developed and determines which intensity category the pixel will be placed into based on thresholds described in the primary land cover class legend in the Science Product User Guide. The value ranges from 0-100% area.
Data Access
Annual NLCD Land Cover Science Products can be accessed via the data access page.
Documents
Additional information on Annual NLCD and Annual NLCD science products can be found in the Science Product User Guide.
Annual NLCD Citation
Annual NLCD has no restrictions on the use of science products. Annual NLCD does ask that if you use the data as part of a publication or presentation that you use the following citation below; however, it is not a requirement to use the data.
U.S. Geological Survey (USGS), 2024, Annual NLCD Collection 1.0 Science Products: U.S. Geological Survey data release, https://doi.org/10.5066/P94UXNTS
Fractional Impervious Surface Characteristics, Constraints, and Caveats
The following artifact was discovered in the Fractional Impervious Surface product.
- Value/Range Truncation: Linear regression predictions produced values outside of the accepted 0-100 value range and were not properly truncated. This can cause values to be greater than 100 and, in some cases, cause a buffer underflow for the UINT8 data type.
Back to the Annual NLCD Product Suite page.
The Annual National Land Cover Database (NLCD) impervious surface product represents the fractional surface area of the map unit (pixel) that is covered with artificial substrate or structures. This includes processed materials or structures (pavement, concrete, rooftops, and other constructed materials) that generate surface runoff. The majority of these materials are impervious to water, but many features that are not impervious like lawns and channelized ditches also contribute to surface runoff and water impairment.

The amount of impervious surface is generally less than suggested by the footprint of developed land cover because these classes often include permeable but developed vegetation, such as lawn grasses, that may be the majority surface cover. The impervious surface product provides a value for every land cover pixel mapped as developed and determines which intensity category the pixel will be placed into based on thresholds described in the primary land cover class legend in the Science Product User Guide. The value ranges from 0-100% area.
Data Access
Annual NLCD Land Cover Science Products can be accessed via the data access page.
Documents
Additional information on Annual NLCD and Annual NLCD science products can be found in the Science Product User Guide.
Annual NLCD Citation
Annual NLCD has no restrictions on the use of science products. Annual NLCD does ask that if you use the data as part of a publication or presentation that you use the following citation below; however, it is not a requirement to use the data.
U.S. Geological Survey (USGS), 2024, Annual NLCD Collection 1.0 Science Products: U.S. Geological Survey data release, https://doi.org/10.5066/P94UXNTS
Fractional Impervious Surface Characteristics, Constraints, and Caveats
The following artifact was discovered in the Fractional Impervious Surface product.
- Value/Range Truncation: Linear regression predictions produced values outside of the accepted 0-100 value range and were not properly truncated. This can cause values to be greater than 100 and, in some cases, cause a buffer underflow for the UINT8 data type.
Back to the Annual NLCD Product Suite page.