Accuracy of Land Cover Maps Derived From Remotely Sensed Data

Daniel Unger; Bonnie Brown; I-Kuai Hung; Yanli Zhang

Accuracy of Land Cover Maps Derived From Remotely Sensed Data

Daniel Unger, Bonnie Brown, I-Kuai Hung, Yanli Zhang

Forestry

Research output: Other contribution

Abstract

Accurate knowledge of land cover and land cover change is essential for a wide range of objectives. Since the 1970's, remotely sensed data have been used increasingly as a means to classify and characterize the earth's land use and land cover. This project compares the accuracy of results of classifying data from mid-level to very high spatial resolutions (Landsat ETM+, SPOT 4, ASTER, SPOT 5, QuickBird). Data from all of these sensors were classified for both urban and rural settings. The project examines accuracy levels between spatial and spectral resolution.

Original language	Undefined/Unknown
State	Published - Mar 27 2012

Publication series

Name	Faculty Publications

Access to Document

Accuracy of Land Cover Maps Derived From Remotely Sensed Data

http://scholarworks.sfasu.edu/spatialsci/4

Cite this

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title = "Accuracy of Land Cover Maps Derived From Remotely Sensed Data",

abstract = "Accurate knowledge of land cover and land cover change is essential for a wide range of objectives. Since the 1970's, remotely sensed data have been used increasingly as a means to classify and characterize the earth's land use and land cover. This project compares the accuracy of results of classifying data from mid-level to very high spatial resolutions (Landsat ETM+, SPOT 4, ASTER, SPOT 5, QuickBird). Data from all of these sensors were classified for both urban and rural settings. The project examines accuracy levels between spatial and spectral resolution.",

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AU - Brown, Bonnie

AU - Hung, I-Kuai

AU - Zhang, Yanli

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Y1 - 2012/3/27

N2 - Accurate knowledge of land cover and land cover change is essential for a wide range of objectives. Since the 1970's, remotely sensed data have been used increasingly as a means to classify and characterize the earth's land use and land cover. This project compares the accuracy of results of classifying data from mid-level to very high spatial resolutions (Landsat ETM+, SPOT 4, ASTER, SPOT 5, QuickBird). Data from all of these sensors were classified for both urban and rural settings. The project examines accuracy levels between spatial and spectral resolution.

AB - Accurate knowledge of land cover and land cover change is essential for a wide range of objectives. Since the 1970's, remotely sensed data have been used increasingly as a means to classify and characterize the earth's land use and land cover. This project compares the accuracy of results of classifying data from mid-level to very high spatial resolutions (Landsat ETM+, SPOT 4, ASTER, SPOT 5, QuickBird). Data from all of these sensors were classified for both urban and rural settings. The project examines accuracy levels between spatial and spectral resolution.

M3 - Other contribution

T3 - Faculty Publications

ER -