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Historical land use and land cover for assessing the northern Colorado Front Range urban landscape

Author

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  • Mark A. Drummond
  • Michael P. Stier
  • James (Jay) E. Diffendorfer

Abstract

We describe historical land-use and land-cover (LULC) maps for the northern Colorado urban Front Range. The Front Range urban landscape is diverse and interspersed with highly productive agriculture, as well as natural land cover types including evergreen forest in the Rocky Mountain foothills and Great Plains grassland. To understand the dynamics of urban growth, raster maps were created at a 1-meter resolution for each of four time steps, nominally 1937, 1957, 1977, and 1997. In total, 38 detailed LULC classes were identified using manual interpretation techniques, aerial photographs, historical maps, and other available information. The maps provide high-resolution spatial data for understanding the historical progression of urbanization and will allow further analysis of the effects of urban growth on social and ecological systems.

Suggested Citation

  • Mark A. Drummond & Michael P. Stier & James (Jay) E. Diffendorfer, 2019. "Historical land use and land cover for assessing the northern Colorado Front Range urban landscape," Journal of Maps, Taylor & Francis Journals, vol. 15(2), pages 89-93, July.
    • Handle: RePEc:taf:tjomxx:v:15:y:2019:i:2:p:89-93
    DOI: 10.1080/17445647.2018.1548383
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    Cited by:

    1. Mustafa Erdem Kabadayı & Paria Ettehadi Osgouei & Elif Sertel, 2022. "Agricultural Land Abandonment in Bulgaria: A Long-Term Remote Sensing Perspective, 1950–1980," Land, MDPI, vol. 11(10), pages 1-24, October.
    2. Chengjie Yang & Ruren Li & Zongyao Sha, 2020. "Exploring the Dynamics of Urban Greenness Space and Their Driving Factors Using Geographically Weighted Regression: A Case Study in Wuhan Metropolis, China," Land, MDPI, vol. 9(12), pages 1-21, December.
    3. Denis Krivoguz & Sergei G. Chernyi & Elena Zinchenko & Artem Silkin & Anton Zinchenko, 2023. "Using Landsat-5 for Accurate Historical LULC Classification: A Comparison of Machine Learning Models," Data, MDPI, vol. 8(9), pages 1-17, August.

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