Impervious surface mapping using satellite remote sensing

M. E. Bauer; J. K. Doyle; N. J. Heinert

Impervious surface mapping using satellite remote sensing

M. E. Bauer, J. K. Doyle, N. J. Heinert

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Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Landsat TM data have been used to map the percentage of impervious surface area of the seven-county Twin Cities Metropolitan Area in 1991, 1998 and 2000. Following classification of land cover types, a regression model relating percent impervious surface area to "tasseled cap" greenness was used to estimate the percent impervious surface area for pixels classified as urban or developed. Eighty to 90 percent of the variation in imperviousness is accounted for by greenness. Classification of the Landsat TM data provides a means to map and quantify the degree of impervious surface area, an indicator of environmental quality, over large areas and over time at modest cost.

Original language	English (US)
Title of host publication	International Geoscience and Remote Sensing Symposium (IGARSS)
Pages	2334-2336
Number of pages	3
Volume	4
State	Published - Jan 1 2002
Event	2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002) - Toronto, Ont., Canada Duration: Jun 24 2002 → Jun 28 2002

Other

Other	2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)
Country/Territory	Canada
City	Toronto, Ont.
Period	6/24/02 → 6/28/02

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title = "Impervious surface mapping using satellite remote sensing",

abstract = "Landsat TM data have been used to map the percentage of impervious surface area of the seven-county Twin Cities Metropolitan Area in 1991, 1998 and 2000. Following classification of land cover types, a regression model relating percent impervious surface area to {"}tasseled cap{"} greenness was used to estimate the percent impervious surface area for pixels classified as urban or developed. Eighty to 90 percent of the variation in imperviousness is accounted for by greenness. Classification of the Landsat TM data provides a means to map and quantify the degree of impervious surface area, an indicator of environmental quality, over large areas and over time at modest cost.",

author = "Bauer, {M. E.} and Doyle, {J. K.} and Heinert, {N. J.}",

year = "2002",

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T1 - Impervious surface mapping using satellite remote sensing

AU - Bauer, M. E.

AU - Doyle, J. K.

AU - Heinert, N. J.

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N2 - Landsat TM data have been used to map the percentage of impervious surface area of the seven-county Twin Cities Metropolitan Area in 1991, 1998 and 2000. Following classification of land cover types, a regression model relating percent impervious surface area to "tasseled cap" greenness was used to estimate the percent impervious surface area for pixels classified as urban or developed. Eighty to 90 percent of the variation in imperviousness is accounted for by greenness. Classification of the Landsat TM data provides a means to map and quantify the degree of impervious surface area, an indicator of environmental quality, over large areas and over time at modest cost.

AB - Landsat TM data have been used to map the percentage of impervious surface area of the seven-county Twin Cities Metropolitan Area in 1991, 1998 and 2000. Following classification of land cover types, a regression model relating percent impervious surface area to "tasseled cap" greenness was used to estimate the percent impervious surface area for pixels classified as urban or developed. Eighty to 90 percent of the variation in imperviousness is accounted for by greenness. Classification of the Landsat TM data provides a means to map and quantify the degree of impervious surface area, an indicator of environmental quality, over large areas and over time at modest cost.

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M3 - Conference contribution

AN - SCOPUS:0036402387

VL - 4

SP - 2334

EP - 2336

BT - International Geoscience and Remote Sensing Symposium (IGARSS)

T2 - 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)

Y2 - 24 June 2002 through 28 June 2002

ER -

Impervious surface mapping using satellite remote sensing

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