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Publication Details

High-resolution land cover of Kansas (2015) Data publication contains GIS data
Paull, Darci A.; Whitson, Jakob W.; Marcotte, Abbey L.; Liknes, Greg C.; Meneguzzo, Dacia M.; Kellerman, Todd A.
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These data were collected using funding from the U.S. Government and Kansas State University – Kansas Forest Service and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
Paull, Darci A.; Whitson, Jakob W.; Marcotte, Abbey L.; Liknes, Greg C.; Meneguzzo, Dacia M.; Kellerman, Todd A. 2017. High-resolution land cover of Kansas (2015). Fort Collins, CO: Forest Service Research Data Archive. Updated 27 November 2017.

*Appropriate use includes fine-scale assessment of tree cover, total extent of tree cover, county-level summaries of tree cover categories, and construction of cartographic products.
This data publication contains 2015 high-resolution land cover data for each of the 105 counties within Kansas. These data are a digital representation of land cover derived from 1-meter aerial imagery from the National Agriculture Imagery Program (NAIP). There is a separate file for each county. Data are intended for use in rural areas and therefore do not include land cover in cities and towns. Land cover classes (tree cover, other land cover, water, or city/town) were mapped using an object-based image analysis approach and supervised classification.

imageryBaseMapsEarthCover; Inventory, Monitoring, & Analysis; Resource inventory; Natural Resource Management & Use; Agroforestry; Water; tree cover; windbreaks; agroforestry; riparian; land cover; Kansas
Related publications:
  • Liknes, Greg C.; Perry, Charles H.; Meneguzzo, Dacia M. 2010. Assessing tree cover in agricultural landscapes using high-resolution aerial imagery. Journal of Terrestrial Observation. 2(1): 38-55.
  • Meneguzzo, Dacia M.; Liknes, Greg C.; Nelson, Mark D. 2013. Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object based classification approaches. Environmental Monitoring and Assessment. 185: 6261-6275.
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