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The Effectiveness of Geographical Data in Multi-Criteria Evaluation of Landscape Services †
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Data 2017, 2(2), 16; doi:10.3390/data2020016

Long-Term Land Cover Data for the Lower Peninsula of Michigan, 2010–2050

1
Monsanto, St. Louis, MO 63146, USA
2
Environmental Geoscience, Michigan State University, East Lansing, MI 48824, USA
3
Forestry and Natural Resources Department, Purdue University, West Lafayette, IN 47907, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Juanle Wang
Received: 23 November 2016 / Revised: 3 May 2017 / Accepted: 4 May 2017 / Published: 5 May 2017
(This article belongs to the Special Issue Geospatial Data)
View Full-Text   |   Download PDF [4340 KB, uploaded 5 May 2017]   |  

Abstract

Land cover data are often used to examine the impacts of landscape alterations on the environment from the local to global scale. Although various agencies produce land cover data at various spatial scales, data are still limited at the regional scale over extended timescales. This is a critical data gap since decision-makers often use future and long-term land cover maps to develop effective policies for sustainable environmental systems. As a result, land change science incorporates common data mining tools to create future land cover maps that extend over long timescales. This study applied one of the well-known land cover change models, called Land Transformation Model (LTM), to produce urbanization maps for the Lower Peninsula of Michigan in United States from 2010 to 2050 with five year intervals. Long-term urbanization data in the Lower Peninsula of Michigan can be used in various environmental studies such as assessing the impact of future urbanization on climate change, water quality, food security and biodiversity. View Full-Text
Keywords: land cover; data mining, urbanization; Lower Peninsula of Michigan; long-term; land transformation model land cover; data mining, urbanization; Lower Peninsula of Michigan; long-term; land transformation model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Tayyebi, A.; Smidt, S.J.; Pijanowski, B.C. Long-Term Land Cover Data for the Lower Peninsula of Michigan, 2010–2050. Data 2017, 2, 16.

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