Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multitemporal Landsat remote sensing

Fei Yuan; Kali E. Sawaya; Brian C. Loeffelholz; Marvin E. Bauer

doi:10.1016/j.rse.2005.08.006

Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multitemporal Landsat remote sensing

Fei Yuan, Kali E. Sawaya, Brian C. Loeffelholz, Marvin E. Bauer

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768 Scopus citations

Abstract

The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing metropolitan areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) data in the seven-county Twin Cities Metropolitan Area of Minnesota for 1986, 1991, 1998, and 2002. The overall seven-class classification accuracies averaged 94% for the four years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, ranged from 80% to 90%. The maps showed that between 1986 and 2002 the amount of urban or developed land increased from 23.7% to 32.8% of the total area, while rural cover types of agriculture, forest and wetland decreased from 69.6% to 60.5%. The results quantify the land cover change patterns in the metropolitan area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.

Original language	English (US)
Pages (from-to)	317-328
Number of pages	12
Journal	Remote Sensing of Environment
Volume	98
Issue number	2-3
DOIs	https://doi.org/10.1016/j.rse.2005.08.006
State	Published - Oct 15 2005

Bibliographical note

Funding Information:
The support of NASA grant NAG13-99002 (Upper Great Lakes Regional Earth Science Applications Center), the Metropolitan Council, and the University of Minnesota Agricultural Experiment Station (project MN-42-037) is gratefully acknowledged. The comments of anonymous reviewers and suggestions by Steven Manson, Department of Geography, University of Minnesota, were most helpful and are appreciated. An earlier version of the paper with 1991 and 1998 results was published in the Proceedings, MultiTemp-2003, Second International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, July 16–18, 2003, Ispra, Italy.

Keywords

Change detection
Land cover classification
Landsat
Multitemporal

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.rse.2005.08.006

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abstract = "The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing metropolitan areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) data in the seven-county Twin Cities Metropolitan Area of Minnesota for 1986, 1991, 1998, and 2002. The overall seven-class classification accuracies averaged 94% for the four years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, ranged from 80% to 90%. The maps showed that between 1986 and 2002 the amount of urban or developed land increased from 23.7% to 32.8% of the total area, while rural cover types of agriculture, forest and wetland decreased from 69.6% to 60.5%. The results quantify the land cover change patterns in the metropolitan area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.",

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note = "Funding Information: The support of NASA grant NAG13-99002 (Upper Great Lakes Regional Earth Science Applications Center), the Metropolitan Council, and the University of Minnesota Agricultural Experiment Station (project MN-42-037) is gratefully acknowledged. The comments of anonymous reviewers and suggestions by Steven Manson, Department of Geography, University of Minnesota, were most helpful and are appreciated. An earlier version of the paper with 1991 and 1998 results was published in the Proceedings, MultiTemp-2003, Second International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, July 16–18, 2003, Ispra, Italy. ",

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N2 - The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing metropolitan areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) data in the seven-county Twin Cities Metropolitan Area of Minnesota for 1986, 1991, 1998, and 2002. The overall seven-class classification accuracies averaged 94% for the four years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, ranged from 80% to 90%. The maps showed that between 1986 and 2002 the amount of urban or developed land increased from 23.7% to 32.8% of the total area, while rural cover types of agriculture, forest and wetland decreased from 69.6% to 60.5%. The results quantify the land cover change patterns in the metropolitan area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.

AB - The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in rapidly growing metropolitan areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) data in the seven-county Twin Cities Metropolitan Area of Minnesota for 1986, 1991, 1998, and 2002. The overall seven-class classification accuracies averaged 94% for the four years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, ranged from 80% to 90%. The maps showed that between 1986 and 2002 the amount of urban or developed land increased from 23.7% to 32.8% of the total area, while rural cover types of agriculture, forest and wetland decreased from 69.6% to 60.5%. The results quantify the land cover change patterns in the metropolitan area and demonstrate the potential of multitemporal Landsat data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.

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Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multitemporal Landsat remote sensing

Abstract

Bibliographical note

Keywords

UN SDGs

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